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This paper examines the problem of synthesizing a two-loop control system for a three-phase voltage source inverter designed for an autonomous power supply system. This type of DC/AC converters is an essential part of power supply systems with renewable energy sources as primary sources, and, accordingly, must corresponds to the requirements for the electric power quality. These requirements are met through circuit design solutions, as well as through the construction of high-precision automatic control systems. The system integrates: a hydrogen electrolyzer, a hydrogen storage system, and a hydrogen fuel cell. The paper proposes a method for calculating the parameters of PI controllers with resonant components, based on the time-scale separation method and allowing independent adjustment of the controller components. The introduction of a resonant component ensures high tracking accuracy for a desired main voltage harmonic and selective suppression of external harmonic influences. The proposed approach allows to synthesize an automatic control system that significantly improves the quality of the voltage inverter output parameters. [ABSTRACT FROM AUTHOR]

Hydrogen is emerging as a critical player in transitioning to sustainable and renewable energy systems, serving roles in energy storage, grid balancing, and decarbonization. This paper explores various aspects of hydrogen, including its production through renewable-electricity-driven electrolysis, advanced storage techniques, and incorporation into current energy systems. It highlights primary electrolysis methods like PEM and alkaline, noting their improved efficiency and cost-effectiveness. Various hydrogen storage methods, such as physical, chemical, and advanced porous materials, are examined for their benefits and limitations. The review further explores hydrogen's integration into grid storage systems and microgrids to enhance energy reliability. It discusses hydrogen's application in fuel cells for electricity generation, focusing on technological advancements that improve efficiency and reduce costs. Additionally, the paper underscores hydrogen's crucial role in reducing CO 2 emissions in industrial processes like steel production and its use in residential and commercial energy supply through combined heat and power systems. Economic aspects and supportive policies from regions are analyzed, highlighting the global efforts and policies supporting the potential hydrogen in renewable energy systems. This analysis emphasizes hydrogen's comprehensive role in enhancing renewable energy systems and achieving global sustainability objectives, providing a thorough review of recent progress and challenges. • Identifies PEM and alkaline as efficient electrolysis methods. • Analyzes varied H 2 storage options for mobility and stationarity. • Highlights advancements in H 2 fuel cells for vehicles. • Discusses global policies supporting H 2 integration. • Reviews economic impacts of scaling H 2 infrastructure. [ABSTRACT FROM AUTHOR]

This paper examines the potential of solar and hydrogen (H 2) energy-based hybrid energy systems for residential applications. The growing need for energy and the demand for sustainable energy sources have led to the development of integrated energy systems that combine renewable energy resources to meet energy needs. This paper overviews recent studies on hybrid energy systems for on-grid and off-grid residential utilizations. It discusses the system configuration and components of hybrid energy systems, including solar panels, electrolyzers, fuel cells (FC), and batteries. It also covers the technical optimization of integrated energy systems, including sizing, control strategies, and economic analysis. The key findings of this review paper indicate that hybrid energy systems can offer dependable and sustainable energy for residential applications. Through numerical analyses, the optimal dimensioning of the system elements and control strategies can significantly enhance the system's performance and lower the cost of energy. This study also highlights the challenges and opportunities for integrating hybrid energy systems within residential applications. Overall, it provides in-depth perspectives on the possibilities inherent in solar and hydrogen energy-based hybrid energy systems for residential applications. The findings can guide future research and the advancement of hybrid energy systems for sustainable energy solutions. • Comprehensive review on solar and hydrogen-based residential applications. • Holistic approach to system configuration, optimization, and economics. • Detailed analysis of interconnected components enhancing system efficiency. • Unique focus on real-world residential applications and scenarios. • Broad applicability across diverse geographical regions. [ABSTRACT FROM AUTHOR]

Hydrogen hubs are emerging as strategic solutions to meet governmental emission reduction targets. A critical aspect of hydrogen hub design involves diversifying end uses, encompassing mobility, backup/storage, heating and cooling provision, onsite electricity generation, and grid energy supply. This paper introduces a comprehensive hydrogen hub model catering to these varied applications. Additionally, a novel multi-stage planning framework is proposed to assist hub operators in making informed decisions regarding the integration of diverse renewable energy sources and infrastructure. This framework addresses varying demands efficiently and economically. Moreover, to align with governmental emission reduction policies leading to net-zero targets, a proactive strategy is suggested. Through zoning for commercial, residential, educational, and healthcare sectors, the Sydney hydrogen hub is envisioned under two scenarios: business-as-usual and towards-net-zero design. Notably, CO 2 emissions are projected to decrease from 18.3 ktonnes in the former to 4.7 ktonnes in the latter scenario. [Display omitted] • Introduces a comprehensive hydrogen hub model catering to varied applications. • Multi-stage planning framework to assist hub operators in making informed decisions. • A proactive strategy aligning with governmental emission reduction/net-zero policy. • Determines optimal sizing, scheduling, and timing for a mix of technologies. • Designing Sydney H 2 hub zoned for commercial, residential, and educational tenants. [ABSTRACT FROM AUTHOR]

Extensive research on zero-emissions autonomous surface vehicles has been recently carried out, aiming at increasing autonomy. Due to their small size, unmanned vehicles present unique difficulties in terms of weight and dimensions when powering the vehicle with renewable energy sources. In this paper, photovoltaic source, fuel cell and Li-ion battery multi-source configurations are proposed, demonstrating by physical layout and simulation results the feasibility of the prototype, compliant with strict constraints of the vehicle under test. The energy system model of the vehicle under test is implemented in MATLAB/Simulink. A comparison of multi-source energy system configurations is proposed and validated by simulation results in terms of endurance, weight and size. If compared with the original battery-powered vehicle, as shown by comparing simulation results, the endurance is doubled, extended up to 12 h on the most favorable day of the year. The solution even complies with payload and physical dimensions constraints. • Autonomous surface vehicles: overview of the most competitive prototypes. • The SWAMP case study: experimental characterization of the battery-powered version. • Modelling and simulation of SWAMP PV-fuel cell–battery multi-source power supply. • Feasibility analysis and comparison of Multi-source power configurations. • Assessment of endurance, weight and size of multi-source configurations. [ABSTRACT FROM AUTHOR]

To tackle the carbon emission problem, the exploitation of renewable energy resources (RESs) with zero emissions has gained much importance. In this context, hydrogen has become an important resource to involve itself in distributed energy resources (DERs) to generate electricity, energize vehicles, and heat our living areas. The utilization of hydrogen technologies is indispensable due to their procurement, environmental friendliness, and high efficiency for DERs. A challenging area in the field of hydrogen energy technologies is extracting efficient power and integration to DERs. This paper investigates how to model and operate a proton exchange membrane fuel cell (PEMFC) stack in a DER application to establish a living lab facility for educational and research purposes by covering Power-to-X (P2X). The PEMFC model of the studied system is designed in a MATLAB/Simulink environment and implemented in an experimental testbed. Thus, a fuel cell (FC) unit as a complementary source is preferred to be used near a photovoltaic (PV) array, a small-scale wind turbine (WT), and a lead acid battery energy storage system (BESS) by creating a P2X concept to form a living lab platform. Beyond the model, regarding the experimental part, a PV array, a WT, and a BESS are combined with a PEMFC module that is rated output of 1200 W. Expect for all systems, the FC part is emphasized in this study. Also, a dynamic model of the mentioned PEMFC is proposed and verified. • Importance of hydrogen energy is focused on its advantages, future role, potential, and challenges. • FC unit as a complementary source is evaluated by creating a P2X concept. • This platform is designed to meet the energy needs of research-education, diversify the supply, increase energy independence. • Energy procurement is supplied via green energy during a lesson, which is noteworthy and instructive. • Feasibility of combined PV/WT/BESS/PEMFC system is investigated. [ABSTRACT FROM AUTHOR]

The necessity of employing renewable energy sources within microgrid-based Power-to-X (P2X) systems has been emphasized by the imperatives of reducing global warming and fossil fuel consumption. Due to their numerous advantages, solar and wind energy have acquired prominence in contemporary power systems. However, their intermittent nature presents challenges. To overcome these challenges, energy storage devices are utilized. Batteries, however, are plagued by issues such as high maintenance needs, self-discharge, and diminishing storage capacity with age. Consequently, investigating alternatives such as hydrogen storage has become a financially viable option, especially for high-power applications. However, the intrinsically slow dynamics of hydrogen production from electricity contrast with the rapid responses of contemporary power electronic devices. This paper presents a versatile technique for optimizing hydrogen production in the presence of stochastic fluctuations in solar irradiance and wind speed. The proposed method combines a modified version of the Symbiotic Differential Whale Optimization Algorithm (m-SDWOA) with power converters to maximize production from renewable sources and electrolyzers. Using extensive simulations to demonstrate the efficacy of the proposed method by comparing its performance to that of the Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO). The results demonstrate the superior performance of the m-SDWOA-integrated method and pave the way for improved hydrogen generation in microgrid-based P2X systems. • Innovative control framework coordinates WT, PV, BESS, and HESS. • Maximizes hydrogen production while maintaining power quality. • Efficient controllers stabilize DC-bus voltage amidst WT/PV variability. • Ensures consistent, reliable power supply in microgrid. • Efficient energy management via m-SDWOA for resource optimization. [ABSTRACT FROM AUTHOR]

Hydrogen production from renewable energy sources is one of the important means to solve the world energy crisis. In the past decades, many experts and scholars have made different reviews on electrolyser and hydrogen production power supply. However, few articles have reviewed the actual industrial products of electrolyser and hydrogen production power supply from the perspective of industry. Therefore, this paper reviews the hydrogen production power supply and electrolyser used in practical engineering projects. It is helpful for experts and scholars to understand the development status of hydrogen production power and electrolyser in the industry and to further develop industrial products more suitable for practical applications. • This paper reviews the products of electrolyzers and hydrogen power sources. • This paper expounds the development situation of hydrogen production key products. • This paper summarizes the future development direction of water electrolysis. • This paper helps scholars to propose methods with practical significance. • This paper has guiding value for industrial equipment selection. [ABSTRACT FROM AUTHOR]

Abstract: Coalbed methane (CBM) or coal seam gas (CSG) as it is known in Australia is becoming an increasingly important source of energy around the world. Many countries such as United States, Canada, Australia and China are investing in the CSG industry. A rise in the cost of conventional natural gas and many other energy resources, along with a decline in these conventional resources and issues such as climate change have encouraged a global interest in alternative sources of energy like CSG. The estimated quantity of CSG worldwide is around 1.4×1014 m3, it is clear that coal seam gas is a significant source of energy. The first section of this paper will discuss the production size of CSG worldwide and the future of the industry. The usage of the coal bed seam for the sequestration of CO2 is also an added benefit. The reduction of CO2 released to the environment may help in the future mitigation of global warming. In addition, the re-injecting of the co-produced CO2 enhances the commercial recovery and production of CSG wells. In the second section, the impact of the CSG industry's by-products on the environment, the freshwater ecosystem and human health are analysed. The second section includes issues associated with the large volume of co-produced water with undesirable composition in the CSG industry. The management of this enormous amount of water requires cost effective technologies and methods. Many methods for dealing with water problems are discussed and analysed in this paper. [Copyright &y& Elsevier]

The ongoing transition from fossil fuel-based electricity generation toward green energy relying on the intermittent renewable energy sources indispensably requires development of novel energy conversion and storage methods. Depending on a particular location and local resources, pumped storage, lithium- or sodium-ion batteries, compressed air energy storage, as well as the so called power-to-gas (P2G) technologies may be applied. Taking into account the abundant solar energy resources available in the northwestern China, such as Ningxia hui autonomous region, and local water resources coming from the Yellow River, a power-to-hydrogen (P2H2) distributed energy conversion system is proposed in this paper, which is based on a high-efficiency reversible Solid Oxide Cell (rSOC). The conducted studies comprise tests with simulated current based on the actual photovoltaic power station data, and with usage of the as-obtained Yellow River water for the electrolysis mode without any pretreatment. It is documented that the reversible operation is beneficial, and the tested cell can operate for a prolonged time. Of importance, Na, Ca, Mg, and Si elements remain in an evaporator, and do not contaminate the cell, while higher than the initial boron concentration can be found in the condensed exhaust gases. The respective operational parameters of the system correspond to an electrolysis current density loading up 433.3 mA cm−2 for 4 h, as well as fuel cell operation mode with a current density of 8.3 mA cm−2 for 12 h. It is found that the average voltage losses in the electrolysis cell and fuel cell mode are 0.27 %/cycle and 0.886 %/cycle, respectively, indicating that the lifetime of the cells can be more than 800 h. The reported studies demonstrate validity of applying rSOC-based P2H2 system, especially if abundant photovoltaic power and water resources are available. [Display omitted] • The Yellow River water was utilized by rSOC for the first time. • The designed test current was modeled with local photovoltaics. • The P2H2 nearby consumption system can reversibly operate for over 800 h. • The degradation rates in SOFC mode are lower than those in SOEC mode. • The Yellow River water has no significant effect on the degradation rate. [ABSTRACT FROM AUTHOR]

The global energy issue is undergoing transformation owing to various factors, such as climate change and geopolitics. In the long term, the primary pathways to achieve sustainable energy development remain the clean energy and global cooperation. As the largest energy consumption centers, the Asia Pacific and North America possess complementary energy profiles and developmental needs for cooperation. This paper analyses various electricity or hydrogen transmission technologies suitable for the Pacific Rim energy system. The liquid hydrogen superconducting energy pipelines possess the potential to fulfill the demands of long-distance and large-scale energy transmission. Building upon this technology, a super energy pipeline project connecting East Asia and North America across 12 time zones was proposed. It is composed of pipelines and relay energy stations, which can realize large-scale storage and transportation of renewable energy as well as the diversified energy supply at terminals. The techno-economic evaluation of the project has been comprehensively conducted, and the investment can be recovered within 10 years. The project is expected to boost the progress of renewable energy, ensure regional energy security and promote the sustainable development of global energy. [Display omitted] • Proposes cross-continental energy transmission scheme for Pacific Rim. • Highlights the potential of liquid hydrogen superconducting energy pipelines. • Identifies the future requirements for the energy storage and transmission. • Presents a review of the existing global energy mix. [ABSTRACT FROM AUTHOR]

• This paper integrates DG sources like PV, WT, FC, MT, BESS in the MG. • A stochastic model of actual data is used to create 4 various case studies for RES. • This paper incorporates utility-driven DSM program in the problem for reducing the operational prices more. • The research does not report on the use of quantum-driven computational intelligence for optimizing energy management in MGs. By integrating renewable energy resources and communication technology into the structure, microgrids (MG) have become self-sustaining with less relying of fossil-fuel based units. In this regard, it is significant to have a highly effective energy management system (EMS) to handle the high volatility of clean energy resources, the uncertainty of time-varying loads, and the fluctuating nature of the market price. Due to the technical limitations, the MG's optimal performance is currently restricted to maximizing operational prices. A study must be conducted to appraise the effects of demand-side management (DSM) on the overall operational costs and peak reductions when integrated with EMS. This study investigates the effect of a utility-driven mutable load shaping method on non-dispatchable energy resources in the renewable microgrids considering the digital twin of solar and wind units. It proposes a three-stage stochastic EMS frame in order to solve the optimal day-ahead planning and to minimize the operating price of network-coupled MG. An initial stage involves creating four potential cases for solar and wind energy production profiles based on real-time meteorological information with the aim o time t , the active power interchange to or from utility for. f minimizing the uncertainty. Stage two involves configuring the MG system, determining the operating limitations, and incorporating DSM load participation information into the objective function. Stage 3 involves designing an optimal power dispatch configuration for DG units, increasing exports to utilities, and comparing the outcomes of each scenario including or excluding DSM involvement. According to the simulation results obtained for the suggested stochastic model implementing 20% DSM, the suggested approach could sucessfuly achieve a price decrease of almost 43.8%. [ABSTRACT FROM AUTHOR]

This paper focuses on the design and use of a control system for a renewable energy production plant based on hydrogen. The proposed control system aims at ensuring the stability and smooth functionality of the plant, which consists of a (i) photovoltaic system connected to an electrolyzer through a battery, (ii) a DC/DC step down transformer, and (iii) an electrolyzer heat exchange system. In this study, solar irradiance is the main system input, and hydrogen production the main output. Since the system utilizes solar energy as input, it depends on the random input of solar irradiance, ambient temperature, and wind flow. Furthermore, the electrolyzer's functionality is subject to several operational variables including cell voltage, current, temperature, and pressure. The electrolyzer heat exchange system operates at specified water temperatures and flow rates. The DC/DC output voltage, and therefore the voltage supplied to the electrolyzer, is regulated by changing its duty cycle. To regulate hydrogen production in the renewable energy production plant, an efficient control system is required. Accordingly, in this work, a control system is designed accounting for three different electrolyzer technologies, alkaline, PEM (proton exchange membrane), and E-TAC (electrochemical - thermally activated chemical water splitting). Subsequently, the effectiveness of the control system is analyzed using Matlab and Simulink models. The main results indicate that the battery is a crucial element in the whole system as it supplies the necessary energy to the electrolyzer. By regulating the appropriate components, the proposed control system proved capable of minimizing power fluctuations and increasing system efficiency up to 20% depending on ambient conditions. Additionally, the results indicate E-TAC and PEM efficiencies 13% and 7% higher than alkaline, respectively. [Display omitted] • Design of a control system for three different electrolyzer technologies. • Use of control systems for electrolyzer voltage and heat exchange. • Photovoltaic system connected to an electrolytic one through a battery. • Proposed control system increases system efficiency up to 20%. [ABSTRACT FROM AUTHOR]

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system. • An efficient energy storage system is essential for managing intermittent energy supply. • The fuel cell can generate DC power by combining hydrogen with oxygen. • The amount of power generated by a PV panel depends on temperature and solar radiation intensity. • Deterministic rule-based controllers operate based on pre-defined rules. • Energy Management System coordinate the flow of power between different components. [ABSTRACT FROM AUTHOR]

The instability of renewable energy generation seriously undermines the safe and stable operation of the power system and contributes to the wastage of power resources. Against this background, this paper proposes a hybrid renewable energy system (HRES) coupled with photovoltaic/wind/battery/hydrogen. By considering the minimization of average annual cost as the upper-level objective and the minimization of power shortage and excess generation as the lower-level objective, a bi-level optimization model is constructed. Based on the scenario simulation, this paper analyzes the optimal configuration of HRES under different technology development levels and different power curtailment rate (PCR) constraints. The results indicate the following: (1) At the current technology level, the high installed proportion of wind power and the low cost-effectiveness of energy storage systems enable the high PCR. (2) Increasing the proportion of photovoltaic power generation and expanding the installed capacity of battery storage and hydrogen storage can effectively reduce the PCR of the power system. (3) As technology advances, the growth in levelized cost of electricity (LCOE) driven by declining PCR constraint will diminish, making it possible to fully utilize renewable energy sources. • A coupled photovoltaic-wind-battery-hydrogen energy system is constructed. • A bi-level capacity configuration optimization model is developed. • The optimal configuration at various technology levels is studied. • The impact of the power curtailment rate constraint is considered. • Developing photovoltaic and energy storage could reduce power curtailment rate. [ABSTRACT FROM AUTHOR]

The carbon neutrality goal places greater demands on integrated energy system (IES) in rural areas. In line with this trend, a multi-objective stochastic-robust based selection-allocation-operation cooperative optimization model is established for planning of rural IES in this paper. Firstly, this paper construct three typical IESs at three levels (user, township and user-township interaction) and make economic selection. Secondly, in order to coordinate the objectives of technology-economy-environment and solve the multiple uncertainties existing in the system, a multi-objective stochastic-robust planning model is proposed. In the model, the objective function introduces indicators such as total cost, primary energy resource efficiency and renewable energy consumption rate. Then constructing stochastic hierarchical scenarios to characterize the stochastic uncertainty of parameters in the time dimension. And introducing typical scenarios into the box sets which characterize the supply-demand sides uncertainty. Finally, a sensitivity analysis is performed to discuss the influence of robustness parameters and biogas prices. The annual total cost of the user-township interaction system is 53.8 % and 8.4 % lower than that of the other two systems, respectively. And from the allocation results of selected system, primary energy resource efficiency is 0.57, total cost is 1.81 × 106 USD and renewable energy consumption rate is 99.46 %. In addition, from the operation results, it is analyzed that the output of the equipment is perfectly balanced with the user's load. Finally, it is obtained by sensitivity analysis that uncertainty budget and biogas price have an impact on the selection of discrete equipment, the capacity of continuous equipment and the total cost. And the optimal capacity of the system under different situations is given. [ABSTRACT FROM AUTHOR]

Renewable energy sources play a crucial role in the provision of power supply in active distribution networks. In networks that rely on renewable energy sources, it may become imperative to curtail the power generated by such units due to a variety of factors. The curtailment of renewable energy generation can be attributed to various factors such as overgeneration, voltage limitations at the network bus, and power limitations at the network line. As per the specified parameters, it is possible for the power generation of renewable units to exceed the load consumption at certain intervals throughout the operational duration. Hence, it is essential to devise a solution that mitigates the frequency and duration of power generation curtailments of renewable units. It is feasible to redistribute overgeneration of renewable energy sources from periods of excess to periods of insufficient capacity to meet demand. This study demonstrates that the provision of power to loads from the sub-distribution substation experiences a reduction in power supply and cost. It is feasible to transmit surplus power from a single bus to multiple other buses. The term used to refer to the ability to transfer power across different locations and time periods is known as spatiotemporal flexibility. The presence of data centers in distribution networks enables a reduction in costs and the frequency of power interruptions associated with renewable energy sources, through the utilization of spatiotemporal flexibility. The objective of this paper is to present a methodology for achieving temporal and spatial flexibility in data centers, with the aim of minimizing costs and curtailing the output generation of renewable energy units. Undoubtedly, this approach can also be executed by incorporating mobile batteries; however, it is noteworthy that mobile batteries entail additional costs on the network. Consequently, the implementation of the spatiotemporal flexibility approach in data centers has been adopted as a substitute for the utilization of mobile batteries. This approach, also referred to as virtual battery, effectively eliminates the costs associated with the use of mobile batteries. This study examines overgeneration of renewable units, bus voltage limitations, and line power restrictions on the standard IEEE 33-bus network. Three scenarios are considered, each involving changes in data center power in response to varying load profiles. The implementation of equitable power distribution across data centers, both in terms of temporal and spatial dimensions, as well as the adoption of flexible spatiotemporal flexibility scenario for data centers, have been observed. The findings of this study indicate that the approach employed in this paper leads to a decrease in costs and the output power of renewable units in the examined scenarios. The implementation of spatiotemporal flexibility mode has resulted in a reduction of power supply expenses ranging from 12 to 37 percent when compared to the basic case. Ultimately, the sensitivity analysis pertaining to the placement of data centers and the associated uncertainty index is presented. • Implementing a model of spatiotemporal flexibility within data centers to function as a virtual storage device. • The curtailment of power generation in renewable energy units has been executed under three different distinct circumstances. • The robust optimization method has been employed to demonstrate the uncertainties inherent in the operation problem. [ABSTRACT FROM AUTHOR]

In view of the weak energy supply stability of the single regional integrated energy system (RIES), the ability to deal with uncertainties is poor. To solve the problem of equilibrium optimization among system economy, robustness and efficiency, this paper interconnects multiple RIES with different resource to form multi-RIES through peer-to-peer energy trading. The control strategy of energy interactive operation involving multiple RIES is optimized. Using the uncertainty confidence set of renewable energy to depict the uncertainty on the source side, a two-stage distributed robust optimal control model for RIES based on data-driven is proposed, and the column and constraint generation (C&CG) algorithm is adopted to significantly improve the solution efficiency. Then, a multi-RIES cooperative game model with uncertain scenarios is proposed, and according to this model, a coupled C&CG-alternating direction multiplier method (ADMM) algorithm is proposed, which realizes the privacy protection of RIES and makes the system have good convergence performance. Finally, the case analysis proves that the strategy proposed in this paper can not only realize energy coordination and complementarity among multiple RIES, but also improve the stability of the system operation and significantly reduce the dependence of the system on the distribution network. • Data-driven RIES two-stage distributed robust optimization model is used to consider the uncertainty of renewable energy. • The multi-RIES cooperative game model based on data-driven two-stage distributed robust optimization is proposed. • A coupled C&CG-ADMM algorithm is proposed. [ABSTRACT FROM AUTHOR]

The construction of a virtual power plant (VPP) represents a powerful approach for harnessing the adjustable capacity of flexible resources. VPP actively participates in transmission network dispatching by aggregating these flexible resources. However, existing practical implementations and research cannot describe the influence of renewable energy's inherent unpredictability on the dispatching boundaries of VPPs. This shortfall leads to a lack of organic coordination between flexible resources and the power transmission network. Therefore, this paper suggests a way to characterize the dispatching boundaries of VPPs based on the concept of flexible operation region (FOR), aiming to better incorporate the flexible resources of decentralized access and lessen the issue of insufficient computing power caused by unified optimization. Initially, an analytical model for the VPP's FOR is presented, followed by dimensionality reduction of the FOR to the VPP's gateway. Subsequently, participation in transmission network scheduling is facilitated using an equivalent dimensionality reduction model. Based on standard example testing, the proposed method's effectiveness and accuracy have been verified in this paper. • This paper proposes a method to characterize the dispatching boundary of VPP based on the FOR. • Constructs the static voltage security region (SVSR) related to each node. • Thermal security region (THSR) related to each branch in the cluster in the power injection space. • This paper proposes a strategy to identify and eliminate the ineffective constraint • The boundary construction method of VPP is applied to the cooperative optimal dispatching. [ABSTRACT FROM AUTHOR]

Solar photovoltaic thermal system (SPTS) can fully tap solar energy resources to realize thermal and electric supply for users simultaneously, but the volatility and uncertainty of renewable energy and load cause the imbalance of energy supply. This paper proposes a multi-time scale optimal scheduling method for SPTS based on event-triggered model predictive control (ET-MPC) considering battery performance deterioration. Firstly, SPTS is divided into day-ahead and day-in optimization layers from different time scales. Day-ahead scheduling takes the minimization economic cost as the optimization function to obtain pre-scheduling plan, and day-in scheduling adapts rolling optimization scheme based on model predictive control (MPC) to reduce power fluctuations and achieve optimal scheduling adjustment. Moreover, the battery performance decay parameter is introduced into the MPC model and embedded into the optimization problem to prolong the cyclic life deterioration, and an event-triggered mechanism is introduced into MPC to improve the computational efficiency and reduce the communication frequency. Finally, the results show that the proposed double-layer scheduling method improves 4.15 %, 66 % and 13.39 % respectively regarding cost, power fluctuation and battery maintenance, and improve the calculation efficiency of 48.89 % compared with standard MPC method, which indicates that the proposed method has good economy, stability and execution efficiency. • This paper proposed energy scheduling for solar photovoltaic thermal system (SPTS). • Double-layer optimal scheduling is proposed to realize the economy and stability. • Battery service time is prolonged through defining performance index. • An event-triggered mechanism is introduced to MPC to reduce the communication burden. • The proposed method improves performance from different perspectives. [ABSTRACT FROM AUTHOR]

The global energy sector is currently undergoing a fundamental transformation as it shifts away from fossil fuels towards renewable energy sources. Green hydrogen is one of the most promising energy carriers of the future in the worldwide effort to reduce the carbon footprint of energy systems. The advancement and uptake of green hydrogen technologies depend on various technological, environmental, and economic factors. In this paper, a comprehensive review of recent studies in green hydrogen energy systems (GHES) is conducted, highlighting technoeconomic aspects from the component to the technology and broader system level. Firstly, the technological principles and recent progress of different green hydrogen generation, storage, and utilization technologies are summarized. Subsequently, an in-depth analysis of various technoeconomic modeling and experimental activities focused on integrated GHES is undertaken. By examining applications in the stationary and transport sectors, this review paper offers an assessment of the current state-of-the-art in terms of development and integration options. The technical challenges, key factors, and future research directions of green hydrogen technologies and systems are outlined, demonstrating that an effective, intelligent, and innovative integration of GHES with other technologies will encourage a more efficient use of resources and enhanced energy system flexibility, resilience, and energy security. • Characteristics, components and configurations of green hydrogen systems are presented. • Technoeconomic studies are collected in tabulated form and exhaustively analyzed. • State-of-the-art applications in stationary and transport sectors are discussed. • A critical review is provided to assess green hydrogen economic viability potential. • Challenges and prospects are evaluated, and future research directions are suggested. [ABSTRACT FROM AUTHOR]

Renewable energy communities with members which own electric vehicles (EVs) can benefit financially from the flexibility that EVs provide to distributed energy resources, such as photovoltaic generators. However, in residential environments, this benefit is often lost because during working hours, most EVs are not plugged in at the premises of the community. In this paper, we hypothesize that such communities can regain some of this lost benefit by offering membership to outside EV owners which are interested in charging their vehicles using the community's charging stations during these periods. This paper introduces an optimization model for energy communities consisting of prosumers, electric vehicles, and EV chargers. The model aims to evaluate the potential advantages of integrating external EV owners into an energy community. A hypothetical community representing a multi-apartment building is analyzed, considering scenarios both with and without external members. The analysis focuses on assessing the technical and economic benefits. The findings indicate that the economic benefits for the examined community are relatively small. However, a notable increase in these benefits is observed when the community is incentivized to share energy among members in the form of a flat network charge reduction for shared energy. [ABSTRACT FROM AUTHOR]

Hydropower has played an important role in Europe in recent decades, offering a unique combination of safe, low-cost, and clean power generation. Today, it is still one of the largest renewable energy sources (RES), accounting for about 35 % of RES electricity generation. However, grid stability is threatened by the increasing amount of undispatchable RES. Flexibility and dynamics such as energy storage and rapid response are urgently needed to achieve EU policy goals. In such a context, hydropower can play a key role, not only as a provider of regulated renewable energy but also due to its ability to balance a renewable energy system in the short term and the medium/long term by pumped storage technology. All these aspects underline the new role of hydropower, which aims to strengthen grid stability and power supply resilience and to enable higher penetration of volatile RES. In this context, the aim of this paper is to demonstrate the role of hydropower at the European level as well as the needs and opportunities of modernization to fully exploit its potential. In particular, this study provides, the assessment of the today flexibility offered by hydropower to the power system at the European level by leveraging a database of information collected through the participants to the working groups of the COST Action Pen@Hydropower which includes stakeholders in the hydropower sector of 34 European countries. The study confirms the key role of hydropower in future energy scenarios with 30 % of the flexibility demand at all time scales met by hydropower. Furthermore, the paper presents a review of the digitalization solutions and innovative technologies that support the growth of a new generation of sustainable hydropower together with the modernization opportunities for existing hydropower plants. The results of this work have practical implications for stakeholders in the hydropower sector and policymakers as it provides evidence at the European scale of the role of hydropower technology in balancing the power system and the need to have supportive frameworks and adequate markets to fully exploit the European hydropower potential to achieve the energy transition goals. [ABSTRACT FROM AUTHOR]

Urban energy supply includes more renewable energy, but renewable energy, such as wind and photovoltaic, is intermittent and connected to the grid and impacts the safe operation of the power system. For urban multi-type energy dispatching, this paper proposed a day-ahead multi-energy robust optimization dispatching method for an urban power grid with a high proportion of renewable power. Firstly, the power supply and load operation scenarios of the urban energy supply system are constructed. Multiple typical scenarios are formed based on fully considering the uncertainties caused by renewable energy and load prediction. A robust optimal scheduling model with system constraints was constructed based on the tuning capacity of adjustable generator sets and energy storage devices in the power grid, with multi-system functional cost optimization as the objective function. Extending the augmented Lagrange multiplier Method, the Alternating Direction Method of Multipliers (ADMM) is proposed to solve the constructed model. The effectiveness of the proposed method is verified by some examples based on the data of an actual power grid in China. [ABSTRACT FROM AUTHOR]

This paper presents a study that focuses on alleviating the impacts of grid outages in Ethiopia. To deal with grid outages, most industrial customers utilize backup diesel generators (DG) which are environmentally unfriendly and economically not viable. Grid-integration of hybrid renewable energy systems (HRES) might be a possible solution to enhance grid reliability and reduce environmental and economic impacts of utilizing DG. In this study, an optimization of grid integrated HRES is carried out for different dispatch and control strategies. The optimal power supply option is determined by performing comparative analysis of the different configurations of grid integrated HRES. The result of the study shows that grid integrated HRES consisting of photovoltaic and wind turbine as renewable energy sources, and battery and hydrogen as hybrid energy storage systems is found to be the optimal system to supply the load demand. From the hydrogen produced on-site, the FC generator and FCEVs consume 143 620 kg/yr of hydrogen which is equivalent to 394 955 kg/yr gasoline fuel consumption. This corresponds to saving 1 184 865 kg/yr of CO 2 emissions and 605 703 $/yr revenue. Besides, this system yields 547 035.4 $/yr revenue by injecting excess electricity to the grid. The study clearly shows the economic and environmental viability of this new technology for implementation. • Modeling and optimization of grid-integrated HRES including grid-reliability and dispatch control. • Storage of excess electricity produced from renewable energy sources in batteries. • Onsite production of renewable hydrogen with excess electricity produced from renewable energy sources. • The role of renewable hydrogen for simultaneous decarbonization of electricity and transportation sectors. • Minimizing overall operating costs by injecting excess electricity to the grid. [ABSTRACT FROM AUTHOR]

Hydropower plants play an integral role in energy supply and are one of the main renewable energy sources. The efficiency of hydropower reservoir systems is controlled by operating rules that need to be optimized to maximize energy production. Here, a novel optimization algorithm, influential flower pollination algorithm (IFPA), is developed in this paper. IFPA has three enhancements: an efficient exploration mechanism based on an adaptive coefficient, a new exploitation mechanism around the best solution, and a rank-based strategy to smoothly transition from exploration to exploitation. IFPA is tested in two benchmark multi-reservoir systems and a real-world five-reservoir hydropower system in Iran. The results show IFPA outperforms other advanced methods in terms of convergence speed and preciseness to achieve the global solution. The tested algorithms include adaptive guided differential evolution (AGDE), composite DE (CODE), hybridizing sum-local search optimizer (HSLSO), improved teaching learning-based optimization (ITLBO), self-adapting control parameters in DE (jDE), self-adaptive TLBO (SATLBO), and a multi-strategy hybrid of DE and particle swarm optimization (MS-DEPSO). IFPA also achieved better total power production in the real-world case study compared to other algorithms. Overall, IFPA can provide better solutions with less power deficit and shows as a promising method for optimizing hydropower reservoir problems. [ABSTRACT FROM AUTHOR]

In this paper, the authors present a two-step model to obtain quasi-optimal solutions for the storage and transportation of renewable energy as its installation becomes more widespread in remote areas. The model is formulated as a total cost minimization linear programming problem and considers both renewable energy facilities and the energy supply and demand of the entire country. The first step of the model optimizes the entire country, while the second step determines the marginal capacity of energy storage and transportation facilities when the excess production capacity of remote renewable energy is added. This approximation for reducing computational complexity is shown to be sufficiently accurate under realistic conditions. The authors apply the model to analyze energy storage and hydrogen production at renewable energy power plants in Japan in 2050. The study shows that photovoltaic power generation uses storage batteries attached to the power plant for electricity transmission. In contrast, wind power generation transmits most electricity directly without storage batteries and converts some into hydrogen for consumers. The proposed lightweight model allows for numeral sensitivity analyses, which provide valuable insight into optimizing energy storage and transport of renewable energy. • We developed a 2-step model for quasi-optimization of equipment at VRE site. • This model optimizes energy storage and transport with VRE deployment. • If additional VRE is sufficiently small, the model division retains sufficient accuracy. • Energy supply costs minimized by combining power transmission and H 2 transportation. • PV has large LIB, while WT has direct transmission and H 2 production. [ABSTRACT FROM AUTHOR]

The fundamental way for China to achieve carbon peak and carbon neutrality is to continuously improve the penetration of renewable energy (RE) in the power system and establish an electricity mix dominated by RE power. According to China's 14th Five-Year Plan, the proportion of non-fossil energy power generation should reach about 39% by 2025. However, the impact of the increase in share of RE power on carbon emissions of the electricity sector remains to be estimated. To this end, the purpose of this paper is to capture the nonlinear characteristics of RE on electricity-related carbon emissions by using panel smooth transition regression (PSTR) model and provincial panel data covering the period 1991–2020 under the background of provincial RE quota system. The estimation results indicate that, (i) in the four transition variables of PSTR model such as the installed capacity of power generation, substation equipment capacity, total electricity consumption and total power generation, the nexus between RE deployment and electricity-related carbon emissions was detected as nonlinear. (ii) The heterogeneous RE carbon abatement effect is reflected in its increasing penetration in provincial power systems. (iii) Carbon abatement performance of RE generation decreases in the negative range with the increase of transition variables. (iv) The estimation coefficient of RE is positive at the higher value of the transition variable in the PSTR model of carbon emissions per capita. As a result, the RE quota with the best emission abatement performance should be designed based on the provincial power resource endowment and the medium and long-term expected electricity consumption. [ABSTRACT FROM AUTHOR]

The integration of converter-based renewable energy resources in a power system leads to reduced inertia, creating a multitude of challenges relating to stability and reliability. On the positive side, the faster response of converter-based renewable energy resources to frequency disturbances, compared to the conventional synchronous-based generators, reduces the required minimum level of inertia in future low-inertia power systems. Accordingly, grid support from distributed photovoltaic (DPV) systems is one of the emerging solutions to overcome the challenges of these systems. This paper demonstrates how adaptive power system frequency support, which modifies the dynamic of frequency support in DPV systems according to the available level of power system inertia, improves overall system operation. In this way, for lower values of power system inertia, a higher amount of power reserve is maintained across DPV systems. Additionally, a faster frequency–Watt response is implemented to provide a larger amount of grid support under frequency disturbances. Simulation results on a composite load model of distribution feeder show that applying for adaptive frequency support from DPV systems improves the frequency nadir during under-frequency events. Experimental results show the effectiveness of the proposed approach in providing a faster dynamic response and higher amount of power support from DPV systems under low inertia conditions. • Proposing an adaptive approach for frequency support with distributed photovoltaic systems. • Obtaining faster frequency response with injection of higher amount of power to grid during under-frequency. • Demonstration of improved frequency response using the composite load model of a distribution feeder. [ABSTRACT FROM AUTHOR]

• The basic reasoning model used by permit officers is condition-based aggregation. • It is hard to add disadvantages when performing value difference-based aggregation. • It is hard for permit officers to assess the value of renewable energy. • Multi-criteria reasoning models could be practical tools for application assessment. Assessment of an application for wind power establishment is a multi-criteria problem including the core problem: whether to grant permission or not. In Sweden, County Administrative Boards decide the outcomes of these kinds of applications. Five permit officers were interviewed to investigate the difficulties and the type of value aggregation in this work, and to test reasoning models as possible decision support tools. The commonly used type of aggregation was condition-based aggregation. Aggregation based on value differences, which means weighing together aspects for and against the wind power establishment, was considered difficult to apply by the respondents. Most of them agreed that some of the aspects that speak against granting permission could be aggregated but that aggregation of all aspects would be hard due to differences between aspects. In addition, the value of the main aspect that speaks for permission, climate friendly energy supply, is very difficult to estimate. Thus, aggregation based on value differences is a difficult question and how it could be performed is discussed in the paper. If policymakers wish to make it possible to take both positive and negative aspects into consideration and to discuss the trade-offs transparently, the investigated method can be a way forward. [ABSTRACT FROM AUTHOR]

Challenges and future perspectives of desalination integration are presented. [Display omitted] • Different optimized models for desalination technologies integration are summarized. • The control strategies of RES-desalination for reducing environmental are discussed. • Impact of desalination process innovation on energy saving and emission reduction. In the present framework, desalination, as an energy-intensive industry, has garnered increased attention due to the imperative need for reducing energy consumption. In this paper, various challenges in the integration and optimal design of desalination processes have been presented. The energy consumption, energy supply method, water production method and improvement measures of various desalination are studied in detail, of which energy consumption is a major aspect. This article summarizes the integration modes of different desalination technologies. Low integration density, inadequate energy utilization and unsystematic theory guidance have been the focus of research. Operational strategies and optimal design methods for the integration of renewable energy and desalination technologies are studied in detail. The integration of renewable energy emerges as a pivotal trend, contributing significantly to the reduction of carbon footprints and costs. Additionally, the significance of recently developed desalination processes, such as pre-treatment process, equipment enhancements and advanced materials have been discussed. Furthermore, various unresolved issues in de integration desalination technologies system have been investigated in the paper along with the possible solutions to address the reported open issues. By exploring the integration of desalination technologies, the paper aims to provide valuable insights for enhancing the efficiency of commercial desalination plants. [ABSTRACT FROM AUTHOR]

Increasing the demand for water and energy resources as well as the clean energy policies and the need for pollution emission reduction has developed the research on the renewable energy resources. This paper reviews the recent advances in multi-generation units for heat, electricity, and desalinated water production. It tries to investigate the new papers in this arena which were not mentioned in the previous reviews. The main parts of this work introduce the co-generation systems for the production of "water and electricity", "heat and water", and "electricity, water, and heat". The results show that among the solar energy receiving devices, Photovoltaic/Thermal panels (PV/Ts) and parabolic trough solar collectors are the most used in co-generation systems. On the other hand, a combination of solar collectors and power cycles makes them a suitable choice for the establishment of a large-scale co-generation plant. Therefore, solar collector-based electricity and water co-generation systems have at least 10 times more output capacity than PV- or PV/T-based systems. On the other hand, most heat and water co-generation systems can achieve an output temperature of 60 °C or more and produce around 10000 kg/year of freshwater based on system size. Examining the co-generation systems of water, electricity and heat also shows that these systems have a high production capacity compared to other co-generation systems. Systems based on heliostat solar tower can produce maximum powers of more than 18 MW and fresh water of 90 kg/s. • Recent advances in solar multi-generation units are reviewed. • PV/Ts and parabolic trough solar collectors are most used collectors in cogeneration systems. • RO and MED have more applications in solar-based co-generation units. • Using waste heat can increase technical and economic performance of system. [ABSTRACT FROM AUTHOR]

Renewable energy attracts increasing attention from both industry and academia under the context of carbon neutrality. For wind and solar energy, the strong dependence on natural processes results in the imbalance between energy production and real demands. Energy storage technologies, e.g., Compressed Air Energy Storage (CAES), are promising solutions to increase the renewable energy penetration. However, the CAES system is a multi-component structure with multiple energy forms involved in the process subject to high temperature and high-pressure working conditions. The CAES system is a complex process flowsheet consisting of charging and discharging process. The process should be optimized to achieve the best thermodynamic and economic performance. Under the optimal design conditions, it might lead to severe consequences once a failure occurs, e.g., harm to humans, the environment, and assets. Limited attention and scarce available information have been paid to the CAES system risk management yet. Hence, this paper applies the System-Theoretic Process Analysis (STPA), which is a top-down method based on system theory, to identify the CAES system safety hazards. The results are expected to provide a preliminary guideline for practitioners regarding the safety and reliability of the CAES system. As a result, a more reliable CAES system can contribute to a more flexible energy system with more efficient and economic utilization of fluctuating renewable energy. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective mixed-integer linear programming model is developed to design a hybrid PV-hydrogen renewable energy system considering two objective functions; minimizing total life costs and loss probability of power supply. The decisions of the hybrid system include the number of PV panels, the number of hydrogen tanks, the number of electrolyzers, the number of fuel cells, and quantity of hydrogen stored over time. An exact method embedded in GAMS software is used to solve the developed model. The model is validated using an electrical testing lab in Saudi Arabia with hourly power demand. Different plans are chosen from the obtained optimal Pareto solutions. For example, one of the plans found that a hybrid system with 212 PV panels, 617 hydrogen tanks, 30 electrolyzers, and 21 fuel cells is sufficient to satisfy the electrical testing lab load with an annual cost of $61663, the loss of power supply probability is 10%, and the CO 2 saving of 214,882 kg of CO 2. The results indicated the feasibility of combining an electrolyzer, hydrogen tank storage, and fuel cell with a renewable energy system; however, the cost of energy generated is still high because of the high investment cost. Furthermore, the findings revealed that hydrogen technologies are appealing as an energy storage solution for intermittent renewable energy systems and in other applications such as transportation, residential, and industrial sectors. In addition, the findings demonstrated the possibility of using renewable energy as a source of energy, namely, in Saudi Arabia. However, weather conditions, geomorphological conditions, and climatic dependence on hydrogen fuel cell technology can harm the energy yields produced by renewable energy systems. • Design a multi-objective hybrid PV-Hydrogen storage renewable energy system. • Evaluate the performance of the proposed model based on a real case study. • Help the decision-maker in analyzing alternative trade-offs. • The LCOE ranges between 0.143 and 0.160 $/kWh for generated plans. • The annual CO 2 savings range between 197,351 and 227,905 kg of CO 2. [ABSTRACT FROM AUTHOR]

Population growth and the expansion of industries have increased energy demand and the use of fossil fuels as an energy source, resulting in release of greenhouse gases (GHG) and increased air pollution. Countries are therefore looking for alternatives to fossil fuels for energy generation. Using hydrogen as an energy carrier is one of the most promising alternatives to replace fossil fuels in electricity generation. It is therefore essential to know how hydrogen is produced. Hydrogen can be produced by splitting the water molecules in an electrolyser, using the abondand water resources, which are covering around ⅔ of the Earth's surface. Electrolysers, however, require high-quality water, with conductivity in the range of 0.1–1 μS/cm. In January 2018, there were 184 offshore oil and gas rigs in the North Sea which may be excellent sites for hydrogen production from seawater. The hydrogen production process reported in this paper is based on a proton exchange membrane (PEM) electrolyser with an input flow rate of 300 L/h. A financially optimal system for producing demineralized water from seawater, with conductivity in the range of 0.1–1 μS/cm as the input for electrolyser, by WAVE (Water Application Value Engine) design software was studied. The costs of producing hydrogen using the optimised system was calculated to be US$3.51/kg H 2. The best option for low-cost power generation, using renewable resources such as photovoltaic (PV) devices, wind turbines, as well as electricity from the grid was assessed, considering the location of the case considered. All calculations were based on assumption of existing cable from the grid to the offshore, meaning that the cost of cables and distribution infrastructure were not considered. Models were created using HOMER Pro (Hybrid Optimisation of Multiple Energy Resources) software to optimise the microgrids and the distributed energy resources, under the assumption of a nominal discount rate, inflation rate, project lifetime, and CO 2 tax in Norway. Eight different scenarios were examined using HOMER Pro, and the main findings being as follows: The cost of producing water with quality required by the electrolyser is low, compared with the cost of electricity for operation of the electrolyser, and therefore has little effect on the total cost of hydrogen production (less than 1%). The optimal solution was shown to be electricity from the grid, which has the lowest levelised cost of energy (LCOE) of the options considered. The hydrogen production cost using electricity from the grid was about US$ 5/kg H 2. Grid based electricity resulted in the lowest hydrogen production cost, even when costs for CO 2 emissions in Norway, that will start to apply in 2025 was considered, being approximately US$7.7/kg H 2. From economical point of view, wind energy was found to be a more economical than solar. • Overview of hydrogen production technologies. • Assessment of cost of desalination processes in relation to the total hydrogen production costs. • Investigation of applicability of offshore hydrogen production from seawater. • To assess the green hydrogen production potential offshore. [ABSTRACT FROM AUTHOR]

[Display omitted] • Areas with the potential of Brackish water resources were identified. • To identify the type of water sources, the soil type investigation method was used. • The energy required for RO water desalination devices is supplied by sunlight. • The potential of solar power plant in Iran was calculated to generate electricity. • Four factors were used to identify suitable areas. Iran has 985,798 square kilometers of desert areas, equivalent to 59.8 percent of the country's total area. This factor causes the creation of salt marshes and, accordingly, the salinization of surface and groundwater. For the first time in this paper, an indirect method is presented to identify areas of Brackish water sources with 3000–10000 mg/L TDS in the entire country of Iran and simultaneously identify the area's potential in terms of the solar energy to provide energy for desalination by reverse osmosis devices. Other types of sources of water, such as seawater, which has more salinity than Brackish water (about 35000 mg/liter) are not investigated in this research, because the primary purpose of this article is to use water that exists in the form of ponds, wells, or surface water that water cannot be used for residential or agricultural purposes, at the same time, this water is not seawater. Simultaneously 16 data layers that include economic, environmental, technical, and geological parameters have been considered.The proposed methodology provides a structured decision aid, which can be used in other countries to identify the mentioned areas and produce fresh water using reverse osmosis devices. Geographic Information Systems (GIS) are used to generate layers of data and to apply the elimination criteria and constraints. Multiple Criteria Decision Analysis (MCDA) is then used to rank and sort the grids via the identified evaluation criteria. This research can also have two other applications. The first is for professionals who want to identify areas with saline water potential, and the second is for organizations that want to launch reverse osmosis desalination plants that work with solar renewable energy. Technically, there are about 160 cities in Iran that have an area of about 144440685120.498077 square meters, have saline water sources, and simultaneously have the potential to use solar energy as one of the renewable energy sources to power reverse osmosis desalination devices. Most of these areas are located in the east of Iran and these areas have high water stress. In this research, the city of Khansar with an area of 95917147.16 square meters, which is located in the province of Isfahan and in the central part of Iran, has surface and underground saline water resources that both technically and operationally, has the highest potential. [ABSTRACT FROM AUTHOR]

This paper presents and compares three approaches to deal with the uncertain nature of energy supply and demand in the problem of optimal sizing of a stand-alone, reliability-constrained hybrid renewable energy system. The system is composed of wind turbines, photovoltaic solar panels, a battery bank, and a diesel generator. The proposed approaches are: (a) adaptive robust optimization with unmet demand as the (un)-reliability metric, (b) scenario-based robust satisficing, and (c) stochastic-free robust satisficing. A column-and-constraint generation algorithm is developed to solve the adaptive robust optimization problem. Furthermore, the theoretical connection between the proposed approaches is drawn, and their numerical performances are compared, in terms of optimal solution cost and reliability, through computational experimentation on a realistic case study. Numerical results show that both the computational times and the out-of-sample performances of the optimal solutions obtained from the two proposed robust satisficing approaches outperform that of the adaptive robust optimization approach, providing a strong justification for their application • Robust optimal design of a stand-alone hybrid renewable energy system. • Adaptive robust optimization versus robust satisficing optimization. • Optimization under the uncertainty of demand and supply. [ABSTRACT FROM AUTHOR]

Economic, technological, and environmental causes are moving energy toward smart distribution networks. The change from fossil fuels to renewable energy sources is extremely environmentally friendly in both the building and transport sectors. Microgrids could be efficiently used in remote areas utilizing renewable energy resources for supplying different energy demands namely power, heat and cold. This paper presents a mixed-integer linear programming (MILP) model for optimizing planning and sizing decisions in microgrids connected to main grid. Planning decisions the amount of generation of each distributed generation (DG) technology and the amount of power transmission to other nodes. Also, sizing of different DGs including photovoltaic and combined heat and power facilities are performed by the proposed model. According to the results, the model is able to optimize sizing and planning decisions in grid-connected microgrids. [ABSTRACT FROM AUTHOR]

Nowadays the trend of increasing the generation units based on renewable energy sources in the electric power system can be observed. Obviously, this is due to the intensifying level of consumer load and demand for electricity. However, renewable generation is characterized by intermittent energy production, which can cause and potential imbalance between generation and demand, especially during off-peak periods. Therefore, in order to ensure a reliable power supply to consumers, it is necessary to use a maneuverable reserve of capacity, such as energy storage systems, in conjunction with the renewable energy source unit. Over the past 10 years, the energy storage market has grown by almost 50%: the installed capacity of energy storage system in the world is about 5 GW. Analysis of the literature on the subject determines the need to study the impact of these devices on the parameters of electric power systems and one of the primary tasks is to determine the optimal location and capacity of energy storage system in the power system. This paper presents the result of solving the task of determining the optimal parameters of a hydrogen energy storage system using the particle swarm optimization method for example a test scheme radial distribution system – 33 bus IEEE. The choice of the type of energy storage is based on such advantages of a hydrogen energy storage system as environmental friendliness, high energy capacity and the ability to store electricity for a long period of time. In addition, compared to lithium-ion batteries, hydrogen energy storage systems have a long life time of about 25 years, during this period of time there is no degradation and significant deterioration of its properties. All these advantages of hydrogen as an energy carrier allow to take into account not only the criterion of total value of active power losses and its maximum reduction respectively, but the possibility and economic efficiency of partial use of the stored hydrogen for other needs when determining the optimal scenario of their operation in the process of discharge. [ABSTRACT FROM AUTHOR]

Life Cycle Climate Performance (LCCP) is a widely accepted metric to evaluate the carbon footprint of air conditioning (AC) systems "from cradle to grave." This paper: (1) reviews the invention and evolution of LCCP, including a comprehensive timeline and bibliography; (2) documents the successful application of LCCP in the replacement of HFC-410A with HFC-32 in room air conditioners; (3) compares the conceptual frameworks and the operational approaches; and 4) reflects on the drawbacks of current LCCP research and points out possible future work. The major policy-relevant findings are: 1. The indirect emissions caused by energy consumption is 70 to 80 percent of the LCCP of AC systems in most countries but will decline in importance as electric power supply shifts rapidly from fossil fuel to renewable energy sources, which have near-zero carbon intensity; 2. The embodied greenhouse gas (GHG) emissions in refrigerant manufacture are, in most cases, negligible but the physical and chemical properties are crucial for system optimization for low carbon footprint; 3. The LCCP metric can be used for multiple purposes such as refrigerant selection and AC system architecture optimization; and 4. Data limitations in material manufacturing and the carbon intensity of electric power are the most significant challenges. Finally, this paper describes a variety of methods to fill in data gaps, including the correction factor method , the data-driven method , and the database searching method. The next-generation LCCP will be an enhanced evaluation process considering local climate, heat islands, and local power supply characteristics. [ABSTRACT FROM AUTHOR]

Distributed energy systems are becoming increasingly popular worldwide. The 100% renewable energy system can be an important energy supply alternative to reduce the carbon emissions and address energy shortage, especially for remote areas. However, the performance of 100% renewable energy system (RES) at community level needs further detailed analysis, which is affected by the climates, availability of renewable energy and local energy markets. This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. To investigate the integration and performance of 100% RES, thirty typical cities located in different regions of China were chosen considering different climates, geographical features, and renewable energy distributions. By taking the economic performance as the optimization objective, the optimal design for the 100% RES is obtained, and the energy and economic performance is analyzed. Results show that, under the current energy market conditions, the 100% RES is feasible for low-density communities in most regions of China. The payback periods of the systems in most cities are less than six years. When the cost of PV is reduced by half considering future technological developments, the payback period of a 100% RES can be reduced by 30%–60%. This paper would provide design suggestions and application recommendations in regard to promoting 100% RES in China. • Application of 100% renewable energy system at community level is studied. • 30 zones are selected considering climates, renewable energy sources and markets. • Solar energy and biomass can contribute to over 90% of the total energy supply. • Investment of 100% RES can be paid back in 6 years for most regions. • Payback periods can be reduced by 30%–60% when PV technology is further developed. [ABSTRACT FROM AUTHOR]

In modern power systems, the reliability of energy supplies is a real challenge for the operators. The emergence of renewable energy resources, along with multi-career users, requires multi-career systems. In this regard, the energy hub (EH) as an integrated system can be used to increase the reliability of the system. The power-to-gas (P2G) and P2G storage are two practical technologies to achieve high efficiency in energy systems. In this paper, the contribution is optimal scheduling of stochastic problem in EH system amalgamated with CHP unit, P2G storage, thermal storage, boiler, wind power, and electrical storage to supply the heat, gas, and power loads by regarding demand response program (DRP). For the electrical loads, the load shifting strategy is considered to minimize the operational cost of the EH system. In order to manage related uncertainties about electricity price, wind power, and electrical loads, the downside risk constraint (DRC) method is applied to investigate the EH system function. According to the obtained results, by increasing approximately 2.8% of the operational cost, the risk level can be reduced remarkably. And also, almost 10% of the energy shifted from peak hours to the off-peak time after DRP is applied. • Optimization of power, heat and gas energy consumption in an energy hub. • Energy hub system is integrated with power-to-gas storage. • All uncertainty parameter are modeled via scenario based stochastic programming. • Downside risk constrained approach is proposed for risk modeling in energy hub. • Risk-averse and risk-neutral strategies are compared with each other. [ABSTRACT FROM AUTHOR]

Hydroelectric power plants have been losing competitiveness to renewable resources in Brazil, specifically wind and solar power resources, given the current water crisis in the country, which has left main reservoirs in the Brazilian hydroelectric power system depleted. However, other renewable energy resources show disadvantages in terms of intermittence and energy storage. Pumped Hydropower Storage (PHS) can help mitigate this problem, supplying energy with fewer variations. This paper studied using PHS concepts together with solar and/or wind renewable resources to recover water levels at the Furnas reservoir in terms of energy and economic performance. The energy studies were developed by sizing the PHS and identifying solar and wind resource potential for supplying energy for pumps in the hydropower plant. The economic analyses considered three different scenarios (I; II and III), and used the NPV (Net Present Value), and LCOE (Levelized Cost of Electricity) methods for a period of 30 years. Energy calculations showed that 1692 MWh/day of energy could be generated using PHS. However, 2729 MWh/day of energy would be needed to store generated energy, and a 1037 MWh negative energy balance will be compensated for by using daily wind and/or solar photovoltaic power production. This would allow the Furnas reservoir to regain 0.45 m of its water level per year. The economic studies showed economic viability for PHS scenarios I and III, with estimated NPV at 151.5 million dollars, and 64.5 million dollars for the last year of the project, respectively. Scenario II was unviable, giving rise to several strong discussions on this application within Brazil. • Wind and solar sources were considered for the pump energy supply. • The proposed system can recover 0.45 m/year of the level in the Furnas reservoir. • The energy production of the reversible power plant was estimated as 1,692MWh/day. • Economic feasibility was evaluated in many scenarios using NPV and LCOEmethods. • Market regulation is required for the diffusion of this technology in Brazil. [ABSTRACT FROM AUTHOR]

Conflict can increase the risk profile of fossil fuel-oriented projects due to disruptions in the energy supply chain and potentially impact the clean energy transition in G7 economies. Thus, the paper investigates the unexplored connections between energy uncertainty, geopolitical conflict, and the militarization index with renewable and non-renewable energy in G7 (1997–2022). The application of advanced econometric algorithms, notably the Methods of Moment Quantile Regression, reveals that energy uncertainty has a positive effect on renewable energy consumption and a negative effect on non-renewable energy consumption. Furthermore, the current geopolitical landscape poses unfavorable conditions for both the expansion of renewable energy usage and the utilization of non-renewable energy sources. The global militarism index relies on non-renewable rather than renewable energy sources. The study employed the Impulse Response Function using Bayesian vector autoregression. The study discovered that variations in energy uncertainty initially enhance the usage of renewable energy but ultimately have adverse consequences for renewable and non-renewable energy consumption. Geopolitical risk unfavorably affects both types of energy, but trade positively influences the growth of renewable energy use in G7. The study recommends transparent economic strategies as essential for governments to reduce uncertainty and facilitate a transition to clean energy. • Evaluate energy uncertainty, geopolitical risk, and militarization for REN & NONREN. • G7's reliance on Russian fossil fuels has disrupted the energy supply. • Energy uncertainty first raises the use of RNE, eventually reducing REN & NONREN. • Geopolitical risk adversely affects both types of energy consumption. • Militarization index heavily relies on non-renewable rather than renewable energy. [ABSTRACT FROM AUTHOR]

A current challenge in energy system modelling is integrating high temporal and spatial resolution with a detailed representation of technologies and sector coupling within a single model. This paper presents a pioneering sectoral optimisation approach for transformation pathways in the German federal states. Spatial resolution in the energy system model REMod is increased and the model is extended from a single-node to a multi-node model for Germany by integrating energy exchanges between regions into a simulation-based optimisation. The approach highlights the challenge of adjusting energy distribution to address the mismatch between high final energy demand in some states and the potential for renewable energy resources in others. The extended model was compared with the results of the single-node model with the same boundary conditions. The comparison showed that increasing the spatial resolution did not significantly affect the overall cost of energy system transformation. However, the composition of the energy system changes, leading to approximately 6% more renewable capacity being installed in a scenario with ten regions. The results for the German federal states indicate a concentration of onshore wind development in the northern federal states with higher full load hours, especially in Lower Saxony/Bremen with 36 GW and Schleswig-Holstein/Hamburg/Mecklenburg-Vorpommern with 38 GW in 2045. The expansion of photovoltaic capacity in densely populated states such as North Rhine-Westphalia (73 GW), Bavaria (71 GW), and Baden-Württemberg (54 GW) reflects the need to meet growing electricity demand. The solar photovoltaic to wind power ratio varies between the federal states and influences the choice of flexibility options, including power-to-x technologies or gas and hydrogen turbines. By 2045, Germany's primary energy supply will shift to states with abundant renewable resources. Spatial flexibility is essential to balance electricity demand and solar and wind potential, mainly through state interconnections. • Sector-coupled energy system model with high temporal and spatial resolution developed. • Simulation-based optimisation as alternative to linear optimisation techniques. • Transformation path on federal states level for Germany modelled. • Transmission grid expansion is needed to transmit renewable energy from Northern to Southern Germany. [ABSTRACT FROM AUTHOR]

[Display omitted] • Improvement of IPP's benefit structure using power to X stations. • Incorporating uncertainty with chance constrained two-stage stochastic optimization. • Contribution analysis according to the hierarchical level of power to X stations. • Enhancing energy operational efficiency through power to X utilization. The carbon neutrality policy aiming for net zero carbon emissions has led to a significant increase in the use of renewable energy sources (RES) globally. However, due to their uncertain nature, RES can cause imbalances in power demand. Recently, Power-to-X (P2X) station technology has gained attention as a solution to the uncertainties of RES and as a means to enhance the capacity and efficiency of RES operations. P2X stations can be utilized when power demand imbalances occur due to the uncertain output of RES or when the power system cannot accommodate the power supply from RES due to various stability issues. Specifically, when supply disruptions occur in the power system due to RES uncertainties, P2X stations contribute to preventing RES curtailment by supplying power to electric vehicle (EV) fuel sources, producing heat using electric heat pumps (EHP), or producing hydrogen using electrolyzers (ELZ), thus improving the uncertain financial benefits for independent power producers (IPP). This paper proposes a mixed-integer linear programming (MILP) based chance-constrained two-stage stochastic optimization (CCTS) approach to address imbalances in power demand from RES and to enhance the profitability of IPP by finding the optimal planning and operational solutions for P2X stations. The proposed method provides hierarchical level results, demonstrating that economic benefits can increase by up to 60.2% with the application of P2X stations and that curtailed energy from RES can be reduced by up to 76.5%. The proposed methodology is also validated for its superior performance by being compared with both the non-linear stochastic chance constraint method and the stochastic method. [ABSTRACT FROM AUTHOR]

This paper proposes a sequential co-optimization (SCO) framework for the design of greenfield energy hubs, aiming to achieve net zero emissions. The SCO framework offers an evolutionary approach to long-term planning and operation, taking into account various evolving factors such as carbon emission policies, technological and economic advancements in energy supply components, changes in land-use, and developments at different stages of the design horizon. The framework ensures that the design of greenfield developments aligns with their evolving characteristics, determining the optimal dispatch flow for firming renewable energy through co-generation and demand flexibility options like smart loads, electric vehicles, and hydrogen-based systems. A sensitivity analysis is conducted to study the impact of emissions, evolving characteristics of greenfield developments, and techno-economic aspects of supply units on the energy hub design. Case studies demonstrate that the proposed design enables large-scale distributed energy systems to meet local energy demand and participate in the electricity market. The SCO framework provides a robust and flexible platform for the correlated optimization of planning and operation of greenfield energy hubs, for advancing towards net zero emissions. • A SCO framework is proposed for greenfield energy hub design. • Dynamic SCO focuses on decarbonization and greenfield evolution. • Correlated optimization in SCO for long-term planning and operation. • Renewable firming in SCO through co-generation and demand flexibility. • Sensitivity analysis of emissions and techno-economic effects in energy supply. [ABSTRACT FROM AUTHOR]

• Linear OPFs are requested for the most recent challenges of distribution systems. • Traditional linear OPFs for distribution grids do not manage closed-loops and OLTCs. • Linear OPF can be improved to manage modern distribution system challenges. • Improved OPF preserves accuracy and numerical performance of the traditional one. • Stability and scalability properties of improved linear OPF are experimented. Modern distribution systems face new challenges due to the rise of small-scale renewable energy resources and the electrification of energy demand. Additionally, the complexity of network management increases with the exchange of flexibility services between distribution and higher voltage levels. The system operator's role involves optimizing the planning and operation of the distribution network. In current scenarios, this includes managing flexibility resources (such as generators, demand response, and on-load tap changers) and implementing new operating strategies (such as closed-loop topologies and dynamic reconfiguration). This paper proposes a reformulation of one of the most used linear approximations of the Optimal Power Flow model for distribution networks. The novelty of this reformulation lies in integrating equations to handle tap-changing transformers with closed-loop/meshed network operation, while preserving the original linear formulation and computational tractability. [ABSTRACT FROM AUTHOR]

In the context of a real electrical distribution network in Puerto Carreño, Colombia, this paper addresses the challenge of enhancing power supply reliability through the strategic integration of Renewable Energy Sources with Hydrogen Energy Systems. The planning problem is reformulated as a Mixed-Integer Quadratically Constrained Programming problem, enabling the use of efficient solvers with global optimal solution. Considering the extensive curtailment options and numerous allocation components, the optimization problem naturally scales up. To address this computational intensity, representative scenarios are derived from the original high-dimensional probability distribution employing the Gaussian Mixture Model. These scenarios are used in conjunction with the proposed optimization framework to achieve cost-effective power grids while reducing fossil fuel dependency. • MIQCP optimizes renewable and hydrogen energy components. • Reduces optimization samples using Gaussian Mixture Model. • Enhances grid stability and cost-effectiveness in remote areas. [ABSTRACT FROM AUTHOR]

Complementary operation has been proven an effective way to handle the increasing levels of renewable energy sources (RESs) integration into the grid. However, due to the relative higher levels of forecast uncertainty associated with RESs outputs, when the hybrid power system operates according to the day-ahead plan in real-time operation, the performance of the system may deviate significantly from the initial expectation in the day-ahead plan. Few research works gauge the effectiveness of the day-ahead plan from the perspective of real-time operation, which inadvertently makes this problem under explored. To handle this problem, in this study, using the wind-hydro hybrid power system (WHHPS) as an example, a novel tighten-constraint method is proposed to guarantee the effectiveness of the day-ahead plan in real-time operation. First, the conventional day-ahead planning model and the real-time operation model are proposed to guide the operation of the WHHPS. Second, considering the lack of connection between day-ahead planning and real-time operation in current research, a novel metric, i.e. Reliability , denoted by R , is proposed to evaluate the performance of the day-ahead plan from the perspective of real-time operation given inherent prediction errors of wind power. Third, a data-driven tighten-constraint method is proposed by introducing an adjustment parameter, denoted by λ , to improve the reliability of the day-ahead plan and eventually guarantee the effectiveness of the day-ahead plan from the perspective of real-time operation. Finally, a bilevel Stackelberg model is proposed and reformulated to calculate the adjustment parameter and the whole procedure of using the proposed method is clarified. The effectiveness of the proposed method is tested and verified through a series of case studies at the end of this paper. The results show that (1) the proposed method can improve the reliability of the day-ahead plan under different reservoir status; (2) the proposed method can guarantee a high reliability level of the day-ahead plan without adding any additional computation burden; (3) improving the prediction precision of the adjustment parameter can enhance the efficiency of resource utilization for power generation; (4) over time, the increase in available historical data can enhance prediction accuracy of adjustment parameter and improve the effectiveness of the proposed method even further. • Method to improve the performance of the day-ahead plan in real-time operation for WHHPS. • A metric to evaluate the day-ahead plan from the perspective of real-time operation. • A bilevel game theory based model to provide the data-driven base. [ABSTRACT FROM AUTHOR]