Search

Reliable heat and power supply are among the basic household needs nowadays. It is especially topical in rural or distant locations that may be cut off from the energy grid due to extreme weather or other events. Nonetheless, the sustainability of our power production systems has to be considered to sustain our planet's long-term abilities to provide energy resources and a viable environment. Renewable energy resources must be prioritized in rural and remote areas, simultaneously strengthening distributed production ability and self-sufficiency. In this context, the use of the Stirling engine for heat to power generation in households, on the scale of small communities, and by using only renewable resources is becoming increasingly topical. Therefore, this research aims to identify the current state-of-the-art for Stirling engine applications using biomass as a renewable energy source, in the context of sustainability and energy security. The paper summarizes the current research tendencies at the household level in the use of biomass-based Stirling engines for renewable heat and power generation in decentralized energy systems. The methodology applied is a structured literature review and content analysis. The research results corroborate the progress towards the use of renewable resources and towards increased energy efficiency because the keyword and overlay analysis showed more frequent publishing in these areas. The content analysis on two more specific sub-directions of interest, i.e., biomass-fuelled Stirling engine use in households and Stirling engine implications on energy security, showed that though research activity in these directions has increased lately, more profound research is needed, especially on aspects of energy security and independence. The content analysis revealed a lack of in-depth analysis on the effects of Stirling engine use on energy security or energy independence, which is suggested as a topical subject for future research. [ABSTRACT FROM AUTHOR]

This paper's research question is to evaluate the potential impact of large numbers of battery electric vehicles (BEVs) on the future electric grid, and whether the flexibility of BEV charging can induce enough system benefits to remunerate BEV users for the change in their recharging pattern. The considered scenario refers to the Italian situation and what might occur through the year 2040, where a share of BEV stock of 40% can be foreseen, as well as significant increases in PV and wind generation. Although this study is focused on Italy, its results are applicable, with minor differences, to several EU countries. This paper first shows that the future impact of increasing penetration of BEVs appears to be compatible with the expected growth of generation from renewable energy sources (RES) and the corresponding reduction in fossil fuel-based generation. It also gives an estimate of the CO2 emission reduction resulting from these changes, considering an unmanaged BEV charge profile and two different managed profiles that shift the car's charging period to hours of the day when they have no negative impact on the grid and maximize the utilization of RES. Finally, it shows an evaluation of the economic benefits of displacing private car charging ranging from 4 to 10 cEUR/kWh, which could be used as tariff incentives to stimulate this displacing in recharging time. [ABSTRACT FROM AUTHOR]

Bifacial photovoltaic (BPV) panels represent one of the main solar technologies that will be used in the near future for renewable energy production, with a foreseen market share in 2030 of 70% among all the photovoltaic (PV) technologies. Compared to monofacial panels, bifaciality can ensure a gain in energy production per unit panel area together with a competitive cost. However, it is of paramount importance to identify whether there is also an environmental benefit when adopting bifacial technologies as opposed to traditional monofacial ones. To obtain a proper insight into the environmental impact, this paper reviews the Life Cycle Assessment (LCA) studies of bifacial solar panels, identifying the most crucial processes and materials that raise environmental burdens. The analysis also contributes to determining whether the major aspects that influence energy production in real operation scenarios and, most of all, that can ensure the gain associated with bifaciality, are considered and how these can further affect the overall environmental impacts. In this sense, it was found that the installation parameters like the mounting structure, or the choice of ground material to raise the albedo as well as the diffuse irradiation that hits the rear surface of thepanel, are commonly not considered during LCA analysis. However, none of the analyzed studies address the issue in a comprehensive way, hampering an effective comparison between both the different works and traditional monofacial PV panels. Recommendations for future LCAs are finally proposed. [ABSTRACT FROM AUTHOR]

The world is warming, and the demand for cooling is increasing. Developing a future green hydrogen economy will also increase the demand for cooling for hydrogen liquefaction. This increase in cooling demand will happen mainly in tropical and developing countries due to their increase in population, improvements in quality of life, and the export of their renewable potential with liquid hydrogen. To solve this increase in demand for cooling, this paper proposes the use of ammonia airship cooling (AAC). AAC extracts cold from the tropopause (−80 °C) with airships and ammonia refrigeration cycles. The liquid ammonia is then transported back to the surface to provide low temperature cooling services (−33 °C). This cooling service is particularly interesting for lowering the electricity consumption in hydrogen liquefaction plants. If all the technological challenges mentioned in the paper are addressed, it is estimated that the cost of cooling with the technology is 8.25 USD/MWht and that AAC could reduce the electricity demand for hydrogen liquefaction by 30%. AAC is an innovative renewable cooling technology that has the potential to complement other renewable energy sources in a sustainable future. [ABSTRACT FROM AUTHOR]

To achieve a more ecologically friendly energy transition by the year 2050 under the European "green" accord, hydrogen has recently gained significant scientific interest due to its efficiency as an energy carrier. This paper focuses on large-scale hydrogen production systems based on marine renewable-energy-based wind turbines and tidal turbines. The paper reviews the different technologies of hydrogen production using water electrolyzers, energy storage unit base hydrogen vectors, and fuel cells (FC). The focus is on large-scale hydrogen production systems using marine renewable energies. This study compares electrolyzers, energy storage units, and FC technologies, with the main factors considered being cost, sustainability, and efficiency. Furthermore, a review of aging models of electrolyzers and FCs based on electrical circuit models is drawn from the literature and presented, including characterization methods of the model components and the parameters extraction methods, using a dynamic current profile. In addition, industrial projects for producing hydrogen from renewable energies that have already been completed or are now in progress are examined. The paper is concluded through a summary of recent hydrogen production and energy storage advances, as well as some applications. Perspectives on enhancing the sustainability and efficiency of hydrogen production systems are also proposed and discussed. This paper provides a review of behavioral aging models of electrolyzers and FCs when integrated into hydrogen production systems, as this is crucial for their successful deployment in an ever-changing energy context. We also review the EU's potential for renewable energy analysis. In summary, this study provides valuable information for research and industry stakeholders aiming to promote a sustainable and environmentally friendly energy transition. [ABSTRACT FROM AUTHOR]

Aiming to mitigate the impact of power fluctuation caused by large-scale renewable energy integration, coupled with a high rate of wind and solar power abandonment, the multi-objective optimal dispatching of a cascade hydro–wind–solar–thermal hybrid generation system with pumped storage hydropower (PSH) is proposed in this paper. Based on the proposed system, the scheduling operation strategy takes into account the complex restrictions of cascade hydropower as well as the flexibility of the PSH. According to various scenarios, the NSGA-II approach is adopted to address the optimization problem, minimizing the system's residual load variation and operation cost. The Pareto solution sets are contrasted and evaluated, applying the TOPSIS with CRITIC weighting. Additionally, the scheduling output of thermal power, cascade hydropower, and PSH is given in terms of different scenarios. The results demonstrate that the allocation of PSH to a hybrid energy system can significantly reduce the operation cost and the fluctuation in the residual load. [ABSTRACT FROM AUTHOR]

This paper describes a new underwater pumped storage hydropower concept (U.PSH) that can store electric energy by using the high water pressure on the seabed or in deep lakes to accomplish the energy transition from fossil to renewable sources. Conventional PSH basically consists of two storage reservoirs (upper and lower lake) at different topographical heights. It needs special topographic conditions, which are only limitedly available in mountain regions. Furthermore, due to the lack of acceptance and the environmental impact, new conventional PSH projects are very unlikely to be built in larger numbers in Europe in the near future. The presented solution solves these issues by placing the storage system on the seabed, thus having other geographical requirements. It operates as follows: in contrast to well-known conventional PSH plants, which use two separated water reservoirs of different heights, the U.PSH concept uses the static pressure of the water column in deep waters by installing a hollow concrete sphere in deep water. Storage of electricity is achieved by using a reversible pump in the hollow sphere. Upon opening a valve, water flows into the sphere, driving a turbine/generator, thereby discharging the storage device. In order to re-charge, the water is pumped out of the sphere against the pressure of the surrounding water. The power and energy, respectively, are proportional to the surrounding water pressure at the seabed. The amount of energy stored depends on the water depth and the volume of the spheres. The spheres need a cable connection to the shore or to a close-by floating transformer station (e.g., an offshore wind plant). No other connections such as pipes are needed. The functional principle of this energy storage technology, its state of the art, its storage capacity and the shape and size of the required spheres are discussed in this paper. [ABSTRACT FROM AUTHOR]

The energy sector plays a crucial role in addressing the global challenges of achieving sustainability by using renewable energy sources as well as by increasing energy efficiency and conservation while gaining energy security and safety. Choosing an appropriate research method to investigate the energy sector's management has become more complex, involving multiple factors such as technical, environmental, social, political and economic. Additionally, considering the important role of energy in modern society, it is imperative to study the current methods used in examining the energy sector and to create an appropriate theory of the managing energy sector enterprises in the future. The main purpose of this review paper is to explore which research methods and approaches are utilized by researchers studying the issues of the managing energy sector enterprises. This article presents a systematic review based on a qualitative synthesis of the accessible publications from the Scopus database. In this review, which also adhered to strict search and filter criteria, a total of 77 articles were selected and synthesized. The selected papers met the inclusion criteria and a bibliometric visualization approach was applied using MAXQDA2020 software. The present paper reveals existing research trends in utilizing various research approaches in the energy sector from the perspective of management sciences in the last ten years and also provides future research avenues in the discussed area of knowledge. [ABSTRACT FROM AUTHOR]

The main aim of this study is to present a systematic literature review (SLR) of the sustainable energy development (SED) and emphasize important activities relevant to this concept. The following set of research tasks was adopted to achieve the main aim: (1) presentation of the distribution of articles by year (both journal and conference papers) on the SED concept; (2) identification of the most frequently cited articles on the SED concept; (3) identification of the countries that have contributed most to the development of the SED concept through publication activities; (4) demonstration of the subject areas most frequently associated with the SED concept; (5) presentation of the various definitions of the SED; (6) identification of the most important activities carried out under the SED; and (7) presentation of future research directions for the SED. It is worth noting that the research tasks undertaken will be both quantitative and qualitative. The data search was conducted on 31 August 2022, and the selected peer-reviewed database was Scopus. The exclusion process resulted in a total of 607 journal and conference papers. The most important conclusion to be derived from this study is that there is no one unified definition of the SED. Moreover, three activities must be undertaken to realize the SED concept: (1) increasing the use of renewable energy sources in the energy mix, (2) enhancing energy efficiency, and (3) reducing emissions of greenhouse gases and air pollutants. The article also presents the authors' conceptual model that can serve as a starting point for further analyses in this area. [ABSTRACT FROM AUTHOR]

In recent years, renewable energy has received extensive attention due to its advantages of sustainability, economy, and environmental protection. However, with the rapid development of renewable energy, the problem of curtailment is becoming increasingly serious. Studying the calculation method and establishing a quantitative evaluation system of renewable energy accommodation capacity are important means to solve this problem. This paper comprehensively considers the factors affecting the accommodation of renewable energy, establishes a accommodation calculation model with the maximum accommodation of renewable energy as the optimization target based on the time series production simulation method, and uses the hybrid particle swarm optimization (PSO) algorithm to solve it. The model is verified with historical data such as load, photovoltaic (PV), and wind power in a certain region throughout the year. The experimental results verify the rationality of the renewable-energy accommodation-capacity model proposed in this paper and the correctness of the theoretical analysis. The calculation results have important reference and guiding significance for the operation and control of power-grid planning and dispatching. [ABSTRACT FROM AUTHOR]

Previously published studies on Australia's energy security did not examine the country's domestic energy security situation in tandem with its international energy statecraft. This paper fills this research gap. In order to provide a robust analysis of a country's strategic options in the energy sector, it is paramount to balance domestic and international dimensions, along with internal and external factors. The paper utilizes the strengths, weaknesses, opportunities, and threats (SWOT) method to review Australia's strategic options by balancing the inward-looking, domestic risk minimization dimension (energy security), with the outward-looking, international power projection dimension (energy statecraft). The paper also applies the 4A framework (availability, accessibility, affordability, and acceptance) to assess Australia's energy security performance. On the one hand, the results demonstrate that Australia has many strengths and opportunities as a reliable and stable energy supplier, endowed with traditional and renewable energy resources, and critical minerals. On the other hand, numerous internal weaknesses and external threats may affect Australia's strategic options in the future. The most pressing issue is the historical lack of strategic government intervention in the energy market, which has, paradoxically, resulted in domestic energy accessibility and affordability crisis. The market-based approach is also the main reason why Australia has not transformed its energy resources into capabilities to be used as instruments of statecraft. The paper uses the SWOT analysis and the 4A assessment as the basis for discussion on how Australia can transform its energy sector weaknesses and threats into strengths and opportunities, to benefit the national interest. [ABSTRACT FROM AUTHOR]

With the increasingly serious problems of energy shortage and environmental degradation, countries around the world are actively developing safe, environmentally friendly, and renewable energy. Biomass energy has become an ideal substitute for fossil fuels due to its abundant reserves, good renewable performance, and zero carbon emissions. This paper discusses the importance and potential of biomass energy as a renewable energy source for China's energy development, mainly including the three biomass conversion methods of physics, chemistry, and biology, seven utilization technologies, such as direct combustion, gasification, and pyrolysis, and five application approaches, such as biomass power generation, biomass gas fuel, biomass liquid fuel, and bio-based materials. This review systematically analyzes the challenges faced by China's development of biomass energy and discusses the future development direction of biomass. The utilization of biomass resources should take a comprehensive and high-value path. China is actively looking for new energy utilization paths, and biomass energy has become a key measure to cope with carbon emission reduction, climate change, and ecological environment protection. [ABSTRACT FROM AUTHOR]

The ongoing replacement of synchronous machine generators (SMs) with converter-interface generators (CIGs) is raising the voltage unbalance of power systems, affecting power quality and grid stability. This paper focuses on a key power quality index for power systems, i.e., the voltage unbalance factor. The purpose of this work is twofold. First, it presents the generalization of a three-phase power flow algorithm developed by University of Padova, named PFPD_3P, to assess the voltage unbalance factors of power systems supplied by CIGs. In particular, it is demonstrated that CIGs can be modelled as three-phase PV/PQ constraints embedding their positive-, negative- and zero-sequence admittances. Then, the concept of three-phase contingency analysis is introduced. Indeed, for static security evaluation, the classical single-phase contingency analysis may no longer be sufficient, as it lacks power quality computations, e.g., voltage/current unbalance factors. Numerical simulations evaluating the unbalance factors due to different generation mix scenarios and contingencies are tested on the Italian extra-high-voltage/high-voltage (EHV/HV) grid. The choice of this network relies on its representativeness, as CIGs are the majority of new installations in the Italian generation mix. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) sources play a special role in the operation of active energy networks. The microgrid (MG) is known as a suitable substrate for the development and installation of DGs. However, the future of energy distribution networks will consist of more interconnected and complex MGs, called multi-microgrid (MMG) networks. Therefore, energy management in such an energy system is a major challenge for distribution network operators. This paper presents a new energy management method for the MMG network in the presence of battery storage, renewable sources, and demand response (DR) programs. To show the performance of each connected MG's inefficient utilization of its available generation capacity, an index called unused power capacity (UPC) is defined, which indicates the availability and individual performance of each MG. The uncertainties associated with load and the power output of wind and solar sources are handled by employing the chance-constrained programming (CCP) optimization framework in the MMG energy management model. The proposed CCP ensures the safe operation of the system at the desired confidence level by involving various uncertainties in the problem while optimizing operating costs under Mixed-Integer Linear Programming (MILP). The proposed energy management model is assessed on a sample network concerning DC power flow limitations. The procured power of each MG and power exchanges at the distribution network level are investigated and discussed. [ABSTRACT FROM AUTHOR]

This research study aims to develop a system which ensures the mobility of a floating dock and its stability in position during docking operations. The dock is designed for operation in a river canal. In order to dock a ship, it is moved away from the quay over a dock trench. Initial requirements and design criteria for the system were determined. The most important of them include docking in the maximum weather conditions, corresponding to a wind speed of 5° Beaufort (5°B), and a zero-emission target for the power supply system (use of a renewable energy source). A wire and winch system was designed to move the dock and stabilise it in position during docking operations. The system comprises mooring wires which are tied to bollards on both quays, and wire winches mounted on both sides of the dock. The wire winches are hydraulically driven, and the hydraulic pumps, run by electric motors, are powered with batteries charged using photovoltaic panels. Statistical environmental parameters (wind, river current) were analysed and the probability of certain mooring wire loads and the corresponding wire winch power output were quantified. Based on these calculations, the power of photovoltaic panels and capacity of the batteries required to power the dock moving system were determined. This paper discusses the system design as well as the results of trials. [ABSTRACT FROM AUTHOR]

Microgrids have emerged as a pivotal solution in the quest for efficient, resilient, and sustainable energy systems. Comprising diverse distributed energy resources, microgrids present a compelling opportunity to revolutionize how we generate, store, and distribute electricity, while simultaneously reducing carbon footprints. This paper proposes an optimal battery energy storage system (BESS) management scheme, along with capacitor placement for reactive power (Q)-compensation, and scheduling for the purpose of a renewable-based microgrid's loss minimization. The proposed model evaluates the impact of BESS management on energy efficiency and analyzes how optimal scheduling of BESS influences system losses. Furthermore, it investigates the coordinated planning and operation of active assets within the microgrid, such as controllable capacitor banks, in enhancing overall efficiency. The model is formulated as a mixed-integer second-order cone programming (MISOCP) problem which is solved for both deterministic and stochastic generation and consumption data. The proposed model is tested on a 21-bus microgrid comprising photovoltaic and hydropower energy resources, and the efficacy of the model is approved by several case studies. The simulation results show that the proposed method can reduce microgrid energy losses by approximately 12 percent using the deterministic approach and around 14 percent with the stochastic approach. [ABSTRACT FROM AUTHOR]

This paper presents a two-stage hybrid stochastic–robust coordination of energy management and self-healing in smart distribution networks with multiple microgrids. A multi-agent systems approach is first used for coupling energy management and self-healing strategies of microgrids, based on expert system rules. The second stage problem, a framework similar to that of the first stage, is then established for the smart distribution networks. Then, hybrid stochastic–robust optimization is used to model the uncertainties of demand, energy price, power generation of renewable energy sources, demand of electric vehicles, and accessibility of zone agents. Further, the grey wolf algorithm is used to solve the formulated optimization problem and achieve an optimal and reliable solution. The proposal is validated on a 69-bus distribution network consisting of three microgrids. The results validate that the proposal minimizes microgrids' utilization indices, such as energy costs, energy losses, and network voltage drops, while simultaneously managing a flexible distribution network. It is also verified that the proposed multi-agent system design provides a high-speed and optimized self-healing solution for the network. [ABSTRACT FROM AUTHOR]

This research proposes the utilization of Peltier modules to convert electrical energy from thermal energy to show its potential as a renewable energy source for residential and commercial application. The study, whose results are presented in this manuscript, was conducted in the city of Monterrey, located in the northeast of Mexico. The energy source was tested and analyzed utilizing a set of statistical metrics and further comparison against experimental test results. The Distrito Tec area in Monterrey city is an academic complex and it was chosen for this study, which consisted of the indirect measurement of the average annual heat energy stored within the buildings' cement structure. The aim was to obtain the annual accumulated electrical power in Wh per year that Peltier modules could provide in Distrito Tec, which is located in a city with solar irradiation levels above the world average. The proposal in this paper could encourage further investigation regarding this energy that is currently waste heat. More specifically, the results of this research highlight the importance of thermoelectric modules and seek to motivate research to improve their properties and make them more efficient and more viable as well. Thermoelectric modules have the potential to be part of the solution to sustainable development as presented in the United Nations SDG-7—ensure access to affordable, reliable, sustainable and modern energy for all. [ABSTRACT FROM AUTHOR]

This paper investigates whether the Paris Agreement affects renewable energy deployment and how institutional quality moderates this relationship. According to a generalized method of moments estimation for panel data for both developed and developing countries over the period 2000–2022, the Paris Agreement positively influences renewable energy deployment, suggesting that countries are promoting renewable energy to align with institutional expectations to maintain their reputations. The results further show that governance quality is the main determinant of renewable energy deployment. However, the moderating role of governance underscores the less-pronounced impact of the Paris Agreement on countries with high governance indicators, suggesting that these countries may have shifted their focus toward other avenues of climate management beyond the deployment of renewable energy. Furthermore, there is strong evidence of the relationship between forest area, CO2 emission, trade openness, domestic credit, and renewable energy deployment. The results are robust with the use of a dynamic panel threshold model. [ABSTRACT FROM AUTHOR]

The increase in renewable energy sources (RESs) in power systems is causing significant changes in their dynamic behavior. To ensure the safe operation of these systems, it is necessary to develop new methods for preserving transient stability that follow the new system dynamics. Fast-response devices such as flexible AC transmission systems (FACTSs) can improve the dynamic response of power systems. One of the most frequently used FACTS devices is the Static Var Compensator (SVC), which can improve a system's transient stability with a proper control strategy. This paper presents a reactive power control strategy for an SVC using synchronized voltage phasor measurements and particle swarm optimization (PSO) to improve the transient stability of a multimachine power system. The PSO algorithm is based on the sensitivity analysis of bus voltage amplitudes and angles to the reactive power of the SVC. It determines the SVC reactive power required for damping active power oscillations of synchronous generators in fault conditions. The sensitivity coefficients can be determined in advance for the characteristic switching conditions of the influential part of the transmission network, and with the application of the PSO algorithm, enable quick and efficient finding of a satisfactory solution. This relatively simple and fast algorithm can be applied in real time. The proposed control strategy is tested on the IEEE 14-bus system using DIgSILENT PowerFactory. The simulation results show that an SVC with the proposed control strategy effectively minimizes the rotor angle oscillations of generators after large disturbances. [ABSTRACT FROM AUTHOR]

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications. [ABSTRACT FROM AUTHOR]

SMEs are asked to incorporate sustainable energy solutions into their organizations' processes to be environmentally friendly and operate more effectively. In this regard, IoT-based technologies seem to have the potential to monitor and optimize energy use. However, more extensive research is required to assess the efficacy of such solutions in the context of SMEs. Despite the growing interest in the Internet of Things (IoT) for renewable energy, there is a lack of information on how well these solutions work for small and medium-sized enterprises (SMEs). While much of the existing literature addresses the application of new technologies in SMEs, the social background underlying their transformation received relatively little attention in previous years. The present research adopts a quantitative approach, employing time series forecasting, specifically long short-term memory networks (LSTM). This paper uses IoT-based approaches to collect and preprocess an energy consumption dataset from various SMEs. The LSTM model is intended to forecast energy consumption in the future based on experience. In terms of analysis, the study adopts Python for data preprocessing, constructing, and assessing models. The main findings reveal a strong positive correlation (r = 0.85) between base energy consumption and overall energy usage, suggesting that optimizing base consumption is crucial for energy efficiency. In contrast, investment in RETs and staff training demonstrate weak correlations (r = 0.25 and r = 0.30, respectively) with energy consumption, indicating that these factors alone are insufficient for significant energy savings. The long short-term memory model used in the study accurately predicted future energy consumption trends with a mean absolute error of 5%. However, it struggled with high-frequency variations, showing up to 15% of mistakes. This research contributes to the literature in line with IoT-based sustainable energy solutions in SMEs, which has not been widely addressed. The findings highlight the critical role of integrating renewable energy technologies (RETs) and fostering a culture of energy efficiency, offering actionable insights for policymakers and business owners. With the application of Python in data analysis and model creation, this research shows a real-world approach to handling issues in sustainable energy management for SMEs. [ABSTRACT FROM AUTHOR]

Renewable energy communities foster the users' engagement in the energy transition, paving the way to the integration of distributed renewable energy sources. So far, the scientific literature has focused on residential users in energy communities, thus overlooking the opportunities for industrial and commercial members. This paper seeks to bridge this gap by extending the analysis to the role of non-residential users. The proposed methodology develops an effective clustering approach targeted to actual non-residential consumption profiles. It is based on the k-means algorithm and statistical characterization based on relevant probability density function curves. The employed clusterization procedure allows for effectively reducing a sample of 49 real industrial load profiles up to 11 typical consumption curves, whilst capturing all the relevant characteristics of the initial population. Furthermore, a peer-to-peer sharing strategy is developed accounting for distributed and shared storage. Three scenarios are considered to validate the model with different shares of non-residential users, and the results are then evaluated by means of shared energy, self-consumption, and self-sufficiency indices. Moreover, the results show that the integration of a large non-residential prosumer in a REC may increase the self-sufficiency of residential members by 8.2%, self-consumption by 4.4%, and the overall shared energy by 37.3%. Therefore, the residential community consistently benefits from the presence of non-residential users, with larger users inducing more pronounced effects. [ABSTRACT FROM AUTHOR]

Substantial breakthroughs in renewable energy have been made in order to reduce energy-induced climate change. Yet our reliance on these sources is still insufficient. The UK's objective of attaining net-zero emissions by 2050 is highly dependent on shifting to an electrical system that exclusively relies on zero-carbon generation. This entails integrating renewable energy sources, along with other low-carbon sources such as nuclear power, into the energy mix. However, the primary barrier to incorporating additional renewable energy sources into the grid is their intermittent and volatile nature. Therefore, there is a pressing need to stabilise the generation of renewables and manage this volatility by enhancing the balancing mechanism between microgrids and the national grid. This paper examines previous research on microgrids and smart grids, specifically from a supply chain perspective. It has been observed that the majority of the current literature focuses on documenting selfish microgrids that strive to optimise performance at the microgrid level. However, there is an alternative approach that draws inspiration from the field of supply chain management. Consequently, it is possible to enhance a microgrid's performance within the broader system that it belongs to by reconsidering the timing and location of storage utilisation. [ABSTRACT FROM AUTHOR]

With the explosion in energy consumption demand, the deep penetration of renewable energy into the grid is inevitable and has become trend across the world today. Microgrids with integrated renewable energy are the core components of smart grids and will permeate all areas of human activity. Although this grid has a very flexible working principle, its heavy reliance on renewable energy sources can cause significant disturbances to the electric transmission system. Therefore, the control and monitoring processes for microgrids must be implemented through various mechanisms to ensure the microgrid system operates safely, stably, and effectively. In this paper, the research team will introduce and synthesize the multilevel control scheme of current types of microgrids. We will evaluate the advantages and disadvantages of each type of MG, providing a reference for further research in the field of microgrid control applications, both current and in the near future. [ABSTRACT FROM AUTHOR]

The rapid progress in renewable energy sources and the increasing complexity of energy distribution networks have highlighted the need for efficient and intelligent energy management systems. This paper presents a comparative analysis of two optimisation algorithms, P and M70, used for the optimal control of the operation of microgrids in islanded mode. The main objective is to minimise production costs while ensuring a reliable energy supply. Algorithm P prioritises the use of photovoltaic (PV) and battery storage and operates the diesel generator at minimum capacity to reduce fuel consumption and maximise the use of renewable energy sources. Algorithm M70, on the other hand, uses a heuristic approach to adaptively manage energy resources in real time. In this study, the performance of both algorithms is evaluated through simulation in different operating scenarios. The results show that both algorithms significantly improve the efficiency of the microgrid, with the M70 algorithm showing better adaptability and cost efficiency in dynamic environments. This research contributes to ongoing efforts to develop robust and scalable energy management systems for future smart grids. [ABSTRACT FROM AUTHOR]

The climate crisis necessitates a global shift to achieve a secure, sustainable, and affordable energy system toward a green energy transition reaching climate neutrality by 2050. Because of this, renewable energy sources have come to the forefront, and the research interest in microgrids that rely on distributed generation and storage systems has exploded. Furthermore, many new markets for energy trading, ancillary services, and frequency reserve markets have provided attractive investment opportunities in exchange for balancing the supply and demand of electricity. Artificial intelligence can be utilized to locally optimize energy consumption, trade energy with the main grid, and participate in these markets. Reinforcement learning (RL) is one of the most promising approaches to achieve this goal because it enables an agent to learn optimal behavior in a microgrid by executing specific actions that maximize the long-term reward signal/function. The study focuses on testing two optimization algorithms: logic-based optimization and reinforcement learning. This paper builds on the existing research framework by combining PPO with machine learning-based load forecasting to produce an optimal solution for an industrial microgrid in Norway under different pricing schemes, including day-ahead pricing and peak pricing. It addresses the peak shaving and price arbitrage challenges by taking the historical data into the algorithm and making the decisions according to the energy consumption pattern, battery characteristics, PV production, and energy price. The RL-based approach is implemented in Python based on real data from the site and in combination with MATLAB-Simulink to validate its results. The application of the RL algorithm achieved an average monthly cost saving of 20% compared with logic-based optimization. These findings contribute to digitalization and decarbonization of energy technology, and support the fundamental goals and policies of the European Green Deal. [ABSTRACT FROM AUTHOR]

With the gradual emergence of trends such as the asynchronous interconnection of power grids and the increasing penetration of renewable energy, the issues of ultra-low-frequency oscillations and low-frequency stability in power grids have become more prominent, posing serious challenges to the safety and stability of systems. The voltage-source converter-based HVDC (VSC-HVDC) interconnection is an effective solution to the frequency stability problems faced by regional power grids. VSC-HVDC can participate in system frequency stability control through a frequency limit controller (FLC). This paper first analyses the basic principles of how VSC-HVDC participates in system frequency stability control. Then, in response to the frequency stability control requirements of the sending and receiving power systems, a droop FLC strategy is designed. Furthermore, a multi-objective optimization method for the parameters of the droop FLC is proposed. Finally, a large-scale electromagnetic transient simulation model of the VSC-HVDC interconnected power system is constructed to verify the effectiveness of the proposed droop FLC method. [ABSTRACT FROM AUTHOR]

This paper presents the evolution and role of energy communities in the context of the transition to renewable energy sources. Such communities are presented as an innovative and resilient response to the challenges posed by climate change. Their importance emerges from their ability to decentralize energy production, increasing local security and reducing dependence on non-renewable energy sources and external suppliers. However, despite the obvious benefits, this contribution highlights several challenges, such as the need for significant upfront investment and the presence of regulatory barriers that may hinder the integration of these solutions into existing energy systems. A detailed bibliometric analysis is used, focusing on specific research areas and using tools to map the most relevant keywords and emerging trends. The results of the bibliometric analysis highlight how energy communities are emerging as key players in the sustainability landscape, capable of addressing and overcoming contemporary environmental challenges. The research reaffirms the transformative potential of energy communities in promoting a more sustainable and resilient future. [ABSTRACT FROM AUTHOR]

In recent years, the energy industry has increased the proportion of renewable energy sources, which are sustainable and carbon-free. However, the increase in renewable energy sources has led to grid instability due to factors such as the intermittent power generation of renewable sources, forecasting inaccuracies, and the lack of metering for small-scale power sources. Various studies have been carried out to address these issues. Among these, research on Virtual Power Plants (VPP) has focused on integrating unmanaged renewable energy sources into a unified system to improve their visibility. This research is now being applied in the energy trading market. However, the purpose of VPP aggregators has been to maximize profits. As a result, they have not considered the impact on distribution networks and have bid all available distributed resources into the energy market. While this approach has increased the visibility of renewables, an additional method is needed to deal with the grid instability caused by the increase in renewables. Consequently, grid operators have tried to address these issues by diversifying the energy market. As regulatory method, they have introduced real-time energy markets, imbalance penalty fees, and limitations on the output of distributed energy resources (DERs), in addition to the existing day-ahead market. In response, this paper proposes an optimal scheduling method for VPP aggregators that adapts to the diversifying energy market and enhances the operational benefits of VPPs by using two Mixed-Integer Linear Programming (MILP) models. The validity of the proposed model and algorithm is verified through a case study analysis. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) aggregate a large number of distributed energy resources (DERs) through IoT technology to provide flexibility to the grid. It is an effective means to promote the utilization of renewable energy, and enable carbon neutrality for future power systems. This paper addresses the evaluation issue of DERs' low-carbon benefits, proposes a flexibility assessment model for self-organized VPP to quantify the low-carbon value of DERs' response behavior in different time periods. Firstly, we introduce the definition of zero-carbon index based on the curve simultaneous rate of renewable energy and load demand. Then, we establish a multi-level self-organized aggregation method for virtual power plants, define the basic rules of DER, and characterize its self-organized aggregation as a Markov game process. Moreover, we use QMIX to achieve a bottom-up, hierarchical construction of VPP from simple to complex. Experimental results show that when users track the zero-carbon curve, they can achieve zero carbon emissions without reducing the overall load, significantly enhancing the grid's regulation capabilities and the consumption of renewable energy. Additionally, self-organized algorithms can optimize the combinations of DERs to improve the coordination efficiency of VPPs in complex environments. [ABSTRACT FROM AUTHOR]

This paper deals with the optimal scheduling of the resources of a renewable energy community, whose coordination is aimed at providing flexibility services to the electrical distribution network. The available resources are renewable generation units, battery energy storage systems, dispatchable loads, and power-to-hydrogen systems. The main purposes behind the proposed strategy are enhancement of self-consumption and hydrogen production from local resources and the maximization of the economic benefits derived from both the selling of hydrogen and the subsidies given to the community for the shared energy. The proposed approach is formulated as an economic problem accounting for the perspectives of both community members and the distribution system operator. In more detail, a mixed-integer constrained non-linear optimization problem is formulated. Technical constraints related to the resources and the power flows in the electrical grid are considered. Numerical applications allow for verifying the effectiveness of the procedure. The results show that it is possible to increase self-consumption and the production of green hydrogen while providing flexibility services through the exploitation of community resources in terms of active and reactive power support. More specifically, the application of the proposed strategy to different case studies showed that daily revenues of up to EUR 1000 for each MW of renewable energy generation installed can be obtained. This value includes the benefit obtained thanks to the provision of flexibility services, which contribute about 58% of the total. [ABSTRACT FROM AUTHOR]

Hydrogen produced from renewable energy sources is a valuable energy carrier for linking growing renewable electricity generation with the hard-to-abate sectors, such as cement, steel, glass, chemical, and ceramics industries. In this context, this paper presents a new model of hydrogen production based on solar photovoltaics and wind energy with application to a real-world ceramics factory. For this task, a novel multipurpose profit-maximizing model is implemented using GAMS. The developed model explores hydrogen production with multiple value streams that enable technical and economical informed decisions under specific scenarios. Our results show that it is profitable to sell the hydrogen produced to the gas grid rather than using it for self-consumption for low-gas-price scenarios. On the other hand, when the price of gas is significantly high, it is more profitable to use as much hydrogen as possible for self-consumption to supply the factory and reduce the internal use of natural gas. The role of electricity self-consumption has proven to be key for the project's profitability as, without this revenue stream, the project would not be profitable in any analysed scenario. [ABSTRACT FROM AUTHOR]

This paper presents a capacity planning framework for a microgrid based on renewable energy sources and supported by a hybrid battery energy storage system which is composed of three different battery types, including lithium-ion (Li-ion), lead acid (LA), and second-life Li-ion batteries for supplying electric vehicle (EV) charging stations. The objective of this framework is to determine the optimal size for the wind generation systems, PV generation systems, and hybrid battery energy storage systems (HBESS) with the least cost. The framework is formulated as a mixed integer linear programming (MILP) problem, which incorporates constraints for battery ageing and the amount of unmet load for each year. The system uncertainties are managed by conducting the studies for various scenarios, generated and reduced by generative adversarial networks (GAN) and the k-means clustering algorithm for wind speed, global horizontal irradiation, and EV charging load. The studies are conducted for three levels of unmet load, and the outputs are compared for these reliability levels. The results indicate that the cost of hybrid energy storage is lower than individual battery technologies (21% compared to Li-ion, 4.6% compared to LA, and 6% compared to second-life Li-ion batteries). Additionally, by using HBESS, the capacity fade of LA batteries is decreased (for the unmet load levels of 0, 1%, 5%, 4.2%, 6.1%, and 9.7%, respectively), and the replacement of the system is deferred proportional to the degradation reduction. [ABSTRACT FROM AUTHOR]

This paper provides a survey of the literature on the application of Multi-agent Systems (MAS) technology for Smartgrids. Smartgrids represent the next generation electric network, as communities are developing self-sufficient and environmentally friendly energy production. As a cyber-physical system, the development of the vision of Smartgrids requires the resolution of major technical problems; this has fed over a decade of research. Due to the stochastic, intermittent nature of renewable energy resources and the heterogeneity of the agents involved in a Smartgrid, demand and supply management, energy trade and control of grid elements constitute great challenges for stable operation. In addition, in order to offer resilience against faults and attacks, Smartgrids should also have restoration, self-recovery and security capabilities. Multi-agent systems (MAS) technology has been a popular approach to deal with these challenges in Smartgrids, due to their ability to support reasoning in a distributed context. This survey reviews the literature concerning the use of MAS models in each of the relevant research areas related to Smartgrids. The survey explores how researchers have utilized agent-based tools and methods to solve the main problems of Smartgrids. The survey also discusses the challenges in the advancement of Smartgrid technology and identifies the open problems for research from the view of multi-agent systems. [ABSTRACT FROM AUTHOR]

A multi-area power system requires coordination to enhance reliability and reduce operating costs. Economic dispatch in such systems is crucial because of the uncertainties associated with variable loads and the increasing penetration of renewable energy sources. This paper presents a hierarchical consensus algorithm designed to determine the economic dispatch in a multi-area power system, accounting for the uncertainties in load and renewable generation. The proposed algorithm, which utilizes distributed agents, operates across three levels. Level 1 coordinates all areas, while levels 2 and 3 form a leader–follower consensus algorithm for overall economic dispatch. Breadth-first search is employed to identify the leader agent within each area. To address the uncertainties in loads and renewable generation, Monte Carlo simulations are performed. The efficacy of the proposed method is validated using the IEEE 39-bus and 118-bus systems, as well as a realistic 1968-bus power system in Taiwan. The traditional equal lambda method is employed to verify that the proposed approach is suitable for multi-area power systems using distributed computation. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources in the European power system is one of the main goals set by the European Union. In order to ease this integration, in recent years, Renewable Energy Communities (RECs) have been introduced that aim to increase the exploitation of renewable energy at the local level. This paper presents an Energy Management System (EMS) for an industrial microgrid owned and operated by a greentech company located in the north of Italy. The company is a member of an REC. The microgrid is made of interconnected busbars, integrating photovoltaic power plants, a fleet of electric vehicles, including company cars and delivery trucks supporting Vehicle-to-Grid (V2G), dedicated charging stations, and a centralized battery energy storage system. The industrial site includes two warehouses, an office building, and a connection to the external medium-voltage network. The EMS is designed to optimize the operation of the microgrid and minimize the operating costs related to the sale and purchase of energy from the external network. Furthermore, as the company is a member of an REC, the EMS must try to follow a desired power exchange profile with the grid, suggested by the REC manager, with the purpose of maximizing the energy that is shared within the community and incentivized. The results demonstrate that, when minimizing only costs, local self-consumption is favored, leading to a Self-Sufficiency Rate (SSR) of 65.37%. On the other hand, when only the adherence to the REC manager's desired power exchange profile is considered in the objective function, the SSR decreases to 56.43%, net operating costs increase, and the energy shared within the REC is maximized. [ABSTRACT FROM AUTHOR]

Ecofuels and their feedstock come in three main product classes: electrofuels (e-Fuels), biofuels, and non-biowaste-derived fuels. Ecofuels originate from non-fossil sources, derived from circular raw materials such as non-food organic waste, renewable hydrogen, and captured CO2 through a rapid process of carbon fixation. Proposed regulation drafts under discussion indicate that new fuels would need to reach a substantial degree of climate neutrality. The manufacture of all ecofuels, however, requires energy input to accomplish the conversion of the initial feedstock; their climate neutrality claims stem from the use of renewable electric energy and/or biomasses in the production process, but fossil fuels are still the main primary sources of global (and the EU's) electric power, and most biofuels consumed in the EU transport mix are still crop-based, with potential conflicts with food and land use. Furthermore, entirely neglecting GHG emissions from renewable energy generation is scientifically debatable, as the impact of the energy (and the related GHG emissions) embedded in the materials used to build renewable energy facilities is small, but not nil. The paper reports ecofuel trends according to the above-mentioned originating technologies and discusses the issues related to their development. [ABSTRACT FROM AUTHOR]

The popularity of nuclear power as a high-availability energy source is increasing in countries that currently rely on coal-based energy. The growing use of renewable energy sources emphasizes the need for greater energy supply security and grid stability. However, nuclear reactors remain the most expensive commercially available power-generation technology, which limits investment in this field. This paper explores the feasibility of investing in Coal-to-Nuclear conversion at selected coal-fired power plant sites in Poland. By converting coal-fired infrastructure, it is possible to reduce the financial cost of constructing a nuclear power plant. The study included an analysis of hydrological conditions from 2010 to 2023 at selected locations, which determined the potential for siting high-power nuclear reactors. An analytical model was used to calculate the required water intake for cooling, and the results were compared with actual river flow measurements. The findings suggested that constructing an inland nuclear power plant in Poland is feasible while complying with legal standards regarding maximum cooling water temperature. The assessment of the four sites allowed appropriate recommendations to be made concerning further research into the implementation of Generation III reactors. [ABSTRACT FROM AUTHOR]

Socioeconomic growth and population increase are driving a constant global demand for energy. Renewable energy is emerging as a leading solution to minimise the use of fossil fuels. However, renewable resources are characterised by significant intermittency and unpredictability, which impact their energy production and integration into the power grid. Forecasting models are increasingly being developed to address these challenges and have become crucial as renewable energy sources are integrated in energy systems. In this paper, a comparative analysis of forecasting methods for renewable energy production is developed, focusing on photovoltaic and wind power. A review of state-of-the-art techniques is conducted to synthesise and categorise different forecasting models, taking into account climatic variables, optimisation algorithms, pre-processing techniques, and various forecasting horizons. By integrating diverse techniques such as optimisation algorithms and pre-processing methods and carefully selecting the forecast horizon, it is possible to highlight the accuracy and stability of forecasts. Overall, the ongoing development and refinement of forecasting methods are crucial to achieve a sustainable and reliable energy future. [ABSTRACT FROM AUTHOR]

As the main contributor of carbon emissions, the low-carbon transition of the industrial sector is important for achieving the goal of carbon dioxide peaking. Hydrogen-enabled industrial energy systems (HIESs) are a promising way to achieve the low-carbon transition of industrial energy systems, since the hydrogen can be well coordinated with renewable energy sources and satisfy the high and continuous industrial energy demand. In this paper, the long-term capacity expansion planning problem of the HIES is formulated from the perspective of industrial parks, and the targets of carbon dioxide peaking and the gradual decommissioning of existing equipment are considered as constraints. The results show that the targets of carbon dioxide peaking before different years or with different emission reduction targets can be achieved through the developed method, while the economic performance is ensured to some extent. Meanwhile, the overall cost of the strategy based on purchasing emission allowance is three times more than the cost of the strategy obtained by the developed method, while the emissions of the two strategies are same. In addition, long-term carbon reduction policies and optimistic expectations for new energy technologies will help industrial parks build more new energy equipment for clean transformation. [ABSTRACT FROM AUTHOR]

With the development of the economy and society, the importance of a secure and stable electricity supply continues to increase. However, the power grid is facing the test of excess installed capacity, the waste of renewable energy, and a low comprehensive utilization rate. This problem stems from the inconsistent peak–valley differences between power production and consumption, and the lack of clear electricity price signals, which disrupts the safe and stable operation of the power market. This paper combines the interactive transactions among clean energy power generation companies, users, and energy storage, explores how the system optimization model can be reflected in the power market through regulatory measures, and formulates the optimal output scheme of the system under the constraints of clean energy power generation forecast data, user base load forecast data, demand-side resource regulation ability, and energy storage system regulation ability to achieve the goals of comprehensive clean energy power consumption and minimum cost for users. A comprehensive analysis of the proposed model was conducted using actual data from a certain province in China, the results show that the consumption of clean energy will increase by 3% to full consumption and the total cost of users will be 32% lower than that of time-of-use (TOU) power prices, which proves the potential of the proposed joint optimization model in absorbing clean energy and the effectiveness of the market mechanism. [ABSTRACT FROM AUTHOR]

In the context of power system decarbonization, the demand-side strategy for increasing the share of renewable energy is studied for two constrained energy systems. This strategy, which is currently widely suggested in policies on the energy transition, would impact consumer behavior. Despite the importance of studying the latter, the focus here is on decisions regarding the type, location, and timeframe of implementing the related measures. As such, solutions must be assessed in terms of cost and feasibility, technological learning, and by considering geographical and environmental constraints. Based on techno-economic optimization, in this paper we analyze the evolution of the power system and elaborate plausible long-term trajectories in the energy systems of two European islands. The case studies, Procida in Italy and Hinnøya in Norway, are both electrically connected to the mainland by submarine cables and present issues in their power systems, which are here understood as relatively isolated power systems. Renewable energy integration is encouraged by legislative measures in Italy. Although not modeled here, they serve as a backbone for the assumptions of increasing these investments. For Procida, rooftop photovoltaics (PV) coupled with energy storage are integrated in the residential, public, and tertiary sectors. A price-based strategy is also applied reflecting the Italian electricity tariff structure. At a certain price difference between peak and off-peak, the electricity supply mix changes, favoring storage technologies and hence decreasing imports by up to 10% during peak times in the year 2050. In Norway, renewable energy resources are abundant. The analysis for Hinnøya showcases possible cross-sectoral flexibilities through electrification, leading to decarbonization. By fine-tuning electric vehicle charging tactics and leveraging Norway's electricity pricing model, excess electricity demand peaks can be averted. The conclusions of this double-prospective study provide a comparative analysis that presents the lessons learnt and makes replicability recommendations for other territories. [ABSTRACT FROM AUTHOR]

The focus of this paper is the relationship between sustainable energy sources and financial development. The main research hypothesis assumes a positive link between these areas, with inevitable differences across countries and business sectors. The following research questions were asked: Is the impact of financial development on sustainable energy resources the same in different EU countries advanced in green transition processes? How is transition towards renewable energy sources progressing in different economic sectors? Does financial development influence sectoral transition in particular countries? This study uses the TOPSIS method and 25 variables for EU countries from 2013 to 2021. Key findings reveal that the link between sustainable energy sources and financial development varies across EU countries, country size affects energy autonomy, and the transition also differs by business sector. Surprisingly, higher financial development correlates with less progress in sustainable energy initiatives. The results of our research may be useful for government decision-makers in the process of designing and controlling the country's transition to sustainable energy. The original contribution of the study is expressed in its the diagnosis of the relationship between financial development and sustainable energy sources, while most studies have focused on the relationship between the energy market and financial development. [ABSTRACT FROM AUTHOR]

A large number of ground-source heat pump (GSHP) systems have been used in residential and commercial buildings throughout the world due to their attractive advantages of high energy and environmental performances. In particular, GSHPs constitute a proven renewable energy technology for space heating and cooling. This paper provides a detailed literature review of the primary aspects of GSHP systems. These include the technological characteristics of HPs and the main types and variations in GSHPs, along with their environmental impact. Other aspects addressed are the integration of GSHPs with other systems, as well as their optimal design and control and energy analysis. The important aspect of the system's performance is also dealt with through case studies and also the barriers hindering the further adoption of GSHPs in buildings. Two important challenges for the adoption of GSHPs is their cost and environmental efficiency. Studies have shown that GSHPs can reach a >>24% lower environmental impact than air-source HPs, while today's technology can allow for a payback period for installing a GSHP of <<5 years. Finally, based on the above review, the future challenges and prospects for the successful uptake of GSHPs is discussed. It seems that through the right steps, the wide adoption of GSHPs as an important form of 'implemented' renewable energy system can become a reality. [ABSTRACT FROM AUTHOR]

As renewable energy becomes more widespread, the uncertainty of its output poses serious challenges for peak and frequency regulation of the power system. Evaluating a grid's capacity to integrate renewable energy sources can provide an early-warning and decision-making basis for grid operation and scheduling. This paper presents a method for evaluating the hosting capacity of renewable energy, considering frequency security constraints. Introducing the system frequency nadir constraint into a system ensures that the frequency does not drop to a dangerous level in the event of power disturbances. The analytical characterization relation equation for the system frequency nadir constraint is constructed based on polynomial chaos expansion (PCE) theory. Furthermore, with the goal of minimizing the reduction in renewable energy, considering multiple flexible resources, like demand response (DR), Combined Heat and Power (CHP), energy storage, and Power-to-Gas (P2G), a renewable energy hosting capacity evaluation model that considers frequency security and flexibility resources is established. Finally, based on the concept of the feasible region, the maximum hosting capacity of a system's renewable energy is visualized using the progressive vertex enumeration method. It identifies the safe operating region for renewable energy output that meets the safety constraints of power grid operations. The simulation results were validated using a modified IEEE 39 bus system. [ABSTRACT FROM AUTHOR]

Hybrid power plants have recently emerged as reliable and flexible electricity generation stations by combining multiple renewable energy sources, energy storage systems (ESS), and fossil-based output. However, the effective operation of the hybrid power plants to ensure continuous energy dispatch under challenging conditions is a complex task. This paper proposes a dispatch engine (DE) based on mixed-integer linear programming (MILP) for the planning and management of hybrid power plants. To maintain the committed electricity output, the dispatch engine will provide schedules for operation over extended time periods as well as monitor and reschedule the operation in real time. Through precise prediction of the load and the photovoltaic (PV) and wind power outputs, the proposed approach guarantees optimum scheduling. The precise predictions of the load, PV, and wind power levels are achieved by employing a predictor of the Feed-Forward Neural Network (FFNN) type. With such a dispatch engine, the operational costs of the hybrid power plants and the use of diesel generators (DGs) are both minimized. A case study is carried out to assess the feasibility of the proposed dispatch engine. Real-time measurement data pertaining to load and the wind and PV power outputs are obtained from different locations in the Sultanate of Oman. The real-time data are utilized to predict the future levels of power output from PV and from the wind farm over the course of 24 h. The predicted power levels are then used in combination with a PV–Wind–DG–ESS–Grid hybrid plant to evaluate the performance of the proposed dispatch engine. The proposed approach is implemented and simulated using MATLAB. The results of the simulation reveal the proposed FFNN's powerful forecasting abilities. In addition, the results demonstrate that adopting the proposed DE can minimize the use of DG units and reduce a plant's running expenses. [ABSTRACT FROM AUTHOR]

The assumptions of contemporary energy policies are increasing the share of renewable energy sources. Biomass combustion is developing as an alternative to fossil fuels. However, it faces challenges such as limited corrosion resistance of steel boiler components due to chloride compounds in flue gases and fly ash. This paper provides a comprehensive thermodynamic analysis of chloride-induced corrosion in steel in the Fe-O-Cl-Na environment, focusing on the influence of steam concentration in the gas phase. The study was performed by using the general thermodynamic rules, the thermodynamic properties of the pure components involved in the reaction, and the properties of the solutions formed in the liquid and gas phases. The study also examined the impact of alkali metal chlorides, particularly NaCl, on the formation of NaFeO2 in the passive oxide scale layer Fe3O4/Fe2O3. Furthermore, it investigated the condensation of NaCl vapour formation of low-melting eutectic mixtures in deposits and the resulting consequences on the corrosion process. The role of HCl in the chlorination and oxidation process of steel in melted ash deposits was also discussed. The presented thermodynamic analysis was compared with assumptions of an "active oxidation" model. This study can be a valuable resource for experimental research planning and a guide for preventing corrosion in industrial settings. [ABSTRACT FROM AUTHOR]

This paper explores an interesting approach to wind energy technology, focusing on a novel type of drag-driven vertical-axis wind turbines (VAWTs). Studied geometries employ rotor-shaped cross-sections, presenting a distinctive approach to harnessing wind energy efficiently. The rotor-shaped cross-section geometries are examined for their aerodynamic efficiency, showcasing the meticulous engineering behind this innovation. The drag-driven turbine shapes are analyzed for their ability to maximize energy extraction in a variety of wind conditions. A significant aspect of these turbines is their adaptability for diverse applications. This article discusses the feasibility and advantages of utilizing these VAWTs in fence configurations, offering an innovative integration of renewable energy generation with physical infrastructure. The scalability of the turbines is highlighted, enabling their deployment as a fence around residential properties or as separators between highway lanes and as energy-generating structures atop buildings. The scientific findings presented in this article contribute valuable insights into the technological advancements of rotor-shaped VAWTs and their potential impact on decentralized wind energy generation. The scalable and versatile nature of these turbines opens up new possibilities for sustainable energy solutions in both urban and residential settings, marking a significant step forward in the field of renewable energy research and technology. In particular, it was shown that among the proposed rotor geometries, the five-blade rotor was characterized by the highest efficiency and, working in a palisade configuration with a spacing of 10 mm to 20 mm, produced higher average values of the torque coefficient than the corresponding Savonius turbine. [ABSTRACT FROM AUTHOR]

In the context of the "Dual-Carbon Strategy", the seamless integration and optimal utilization of renewable energy sources present a pressing challenge for the emerging power system. The advent of demand-side response technology offers a promising solution to this challenge. This study proposes a two-stage response control strategy for multiple DR clusters based on the specific response time characteristics of industrial and residential loads. The strategy enhances the utilization rate of wind power, harnesses the joint response capability of various types of loads on the demand side, and ensures the overall revenue of the load aggregator (LA). It underscores the importance of industrial loads in large-scale energy consumption control throughout the overall consumption response process, while residential load clusters exhibit quick response flexibility. A homogeneous energy consumption sorting unit response strategy is established from the perspective of a residential load variable-frequency air conditioning cluster unit. This strategy addresses the challenge faced by industrial electrolytic aluminum plants in coping with long-term response intervals amidst significant fluctuations in wind power consumption demand, which may lead to incomplete consumption. This study constructs a response model based on industrial and residential time-sharing tariffs, as well as the aggregator consumption penalty price, with the optimal load energy economy index serving as the evaluation criterion. A series of simulations are conducted to comprehensively evaluate the energy consumption of the two load clusters at all times and the total revenue of the aggregator in the response zone. The objective is to achieve a win–win situation for the total wind power energy consumption rate and the aggregator's economy. The results of the simulations demonstrate that the response control strategy proposed in this study enhances the overall energy consumption rate by nearly 4 percentage points compared to a single industrial cluster. The total benefit of the load aggregator can reach CNY 941,732.09. The consumption response scheduling strategy put forward in this paper bolsters wind power consumption, triggers demand response, and significantly propels the comprehensive construction and development of the dual-high power grid. [ABSTRACT FROM AUTHOR]