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The University of Newcastle (UON) and Jord International Pty Ltd. (Jord) have jointly developed a novel concept for the storage of energy from renewable and fossil fuel sources. The process, referred to as the pressurized regenerative calcium cycle (PRC2), relies on cyclic carbonation and calcination of CaO/CaCO3, in which low-cost electrical energy (i.e., off-peak, or excess generation from renewables) drives the calcination reaction and electricity is generated as required through the carbonation reaction. Initial proof-of-concept testing of the process was previously conducted within an existing fluid bed reactor at UON. The PRC2 concept was successfully demonstrated by maintaining the fluid bed reactor at a constant temperature by using the heat released during the reaction of calcium oxide and carbon dioxide. Following proof-of-concept testing, further refinement of the PRC2 process, which is the subject of this paper, was conducted to address its shortcomings and, importantly, facilitate the detailed design, construction, and operation of a large-scale demonstration plant. Nine different configurations were examined for the PRC2 process, for each of which a combined experimental, process modelling, and techno-economic assessment was completed. Experimental investigations were conducted to determine the suitability of carbonate materials for the PRC2 process. Process modelling and levelized cost of storage (LCOS) calculations were concurrently conducted and revealed that the molten salt approach (Option 9) was the most promising, having superior round-trip efficiency and lowest LCOS. For practical reasons (e.g., technical difficulties of working with molten salts), Option 3 (indirect power generation using a fluid bed reactor) was deemed the most feasible option for a demonstration scale plant. The LCOS for Option 3 (assuming a 100 MWe capacity) was calculated to be AUD 245 per MWh, which is on par with the cost of batteries for peak power replacement applications (the cost associated with lithium-ion batteries is AUD 370 per MWh). [ABSTRACT FROM AUTHOR]

Industrial facilities are seeking new strategies that help in providing savings mechanisms for demand charges. Demand charges are the charges incurred by industrial facilities as a result of power usage. Thermal energy storage has advanced significantly with lots of new applications, garnering the interest of many industrial facilities. These applications could be used to shave the industrial facilities' peak electric demand and reduce their demand charges. This paper aims to demonstrate the efficacy of thermal energy storage in reducing demand charges and highlight new developments in the integration of smart control systems with thermal energy storage. The study compares energy consumption and peak demand for a facility equipped with and without thermal energy storage tanks using a fixed schedule for charging and discharging. Additionally, the paper examines the impact of incorporating a smart controller to determine when to charge and discharge the tank based on the facility's real-time power usage and a given setpoint. The results indicate cost savings from the use of thermal energy storage tanks under two proposed scenarios, reflected in the reduced cost of power consumption for the studied facility. The incorporation of a smart controller with the thermal energy storage tank in the facility studied could provide estimated savings of 3.3% per year of power consumption charges, without considering the contribution of any incentives. The estimated savings provided by the fixed schedule scenario are 2.7% per year. [ABSTRACT FROM AUTHOR]

An integrated zero-carbon power plant aggregates uncontrollable green energy, adjustable load, and storage energy resources into an entity in a grid-friendly manner. Integrated zero-carbon power plants have a strong demand response potential that needs further study. However, existing studies ignore the green value of renewable energy in power plants when participating in demand response programs. This paper proposed a mathematical model to optimize the operation of an integrated zero-carbon power plant considering the green value. A demand response mechanism is proposed for the independent system operator and the integrated zero-carbon power plants. The Stackelberg gaming process among these entities and an algorithm based on dichotomy are studied to find the demand response equilibrium. Case studies verify that the mechanism activates the potential of the integrated zero-carbon power plant to realize the load reduction target. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation exhibits stochastic and uncertain characteristics. In order to improve the economy and reliability of a photovoltaic-energy storage system (PV-ESS), it is crucial to optimize both the energy storage capacity size and the charging and discharging strategies of the ESS. An optimal scheduling model for PV-ESS is proposed in this paper, comprehensively considering factors in terms of energy cost and charging/discharging constraints of the PV-ESS. Moreover, the model employs a particle swarm optimization-backpropagation (PSO-BP) neural network to predict the PV power using historical generation data from a factory in Xiamen. The proposed two PV-ESS scheduling strategies are compared under three weather conditions. In the demand management strategy, the ESS can flexibly respond to different weather conditions and load demand changes, and effectively reduce the electricity cost for users. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of the abolition of annual net metering in Slovenia and compares the electric energy costs for the studied active user after the abolition. The article also provides an exploration of the role played by an aggregator, which serves as a central entity that enables individuals to participate in the electric energy market. An analysis of the case study of an active user was made, where an analysis was made of the measurements of household consumption and photovoltaic plant production for the year 2022. This article presents an economic analysis with and without net metering and an analysis of the aggregator involvement strategies. In addition, a battery energy storage system was also considered in the analysis. An important part of the article is the identification of the flexibility potential for shiftable loads, which enable an aggregator to acquire insight into the energy consumption profile and energy production profile of active users. The following indicators were used to compare the strategies: annual electric energy cost and the indicators including self-sufficiency, self-consumption, and grid dependency. The findings indicate that, even in the absence of annual net metering, the active user can lower their costs for electric energy with the help of an aggregator. [ABSTRACT FROM AUTHOR]

With the integration of large-scale renewable energy generation, some new problems and challenges are brought for the operation and planning of power systems with the aim of mitigating the adverse effects of integrating photovoltaic plants into the grid and safeguarding the interests of diverse stakeholders. In this paper, a methodology for allotting capacity is introduced, which takes into account the active involvement of multiple stakeholders in the energy storage system. The objective model for maximizing the financial proceeds of the PV plant, the system for the storage of energy, and a power grid company is studied. Then, in order to maximize the benefit of three stakeholders, a modified particle swarm optimization algorithm is devised, employing the prevailing typical allocation strategy. Finally, a case study is provided based on the modified IEEE 14-bus and the actual power grid from South Xinjiang, China. The simulation results and findings of the case study conclusively illustrate that the proposed methodology adeptly ensures the maximization of interests for the triad of stakeholders. [ABSTRACT FROM AUTHOR]

In this paper, a two-stage model of an integrated energy demand response is proposed, and the quantitative relationship between the two main concerns of investors, i.e., investment return and investment cycle and demand response, is verified by the experimental data. Energy storage technology is a key means through which to deal with the instability of modern energy sources. One of the key development paths in the electricity market is the development by energy merchants of energy storage power plants in the distribution network to engage in a grid demand response. This research proposes a two-stage energy storage configuration approach for a cold-heat-power multi-energy complementary multi-microgrid system. Considering the future bulk connections of distributed power generation, the two most critical points of energy storage station construction are the power generation equipment and specific scenarios for serving the community, as well as the purchase and sale price of electricity for serving the community microgrid (which directly affects the investment revenue). Therefore, this paper focuses on analyzing the different impacts caused by these two issues; namely, the two most important concerns for the construction of energy storage configurations. First, the basic model enabling wholesale electricity traders to construct energy storage power plants is presented. Second, for a multi-microgrid system with a complementary cold-heat-power multi-energy scenario, a two-stage optimum allocation model is constructed, whereby the upper model calculates the energy storage allocation problem and the lower model calculates the optimal dispatch problem. The lower model's dispatch computation validates the upper configuration model's reasonableness. Finally, the two-layer model is converted to a single-layer model by the KKT condition, and the nonlinear problem is converted to a linear problem with the big-M method. The validity is proved via mathematical examples, and it is demonstrated that the planned energy storage plants by merchants may accomplish resource savings and mutual advantages for both users and wholesale power traders. [ABSTRACT FROM AUTHOR]

The demand for energy storage systems is rising together with the proportion of renewable energy sources (RES) in power systems. The highest capacity among the various energy storage systems in power systems is provided by pumped-storage hydropower (PSH). In this paper, the ability of the real-time digital simulator (RTDS), e.g., dSpace–SCALEXIO, to emulate a complex pumped-storage hydropower plant with four units, two common penstocks, a surge tank, and a long headrace tunnel is investigated. The RTDS is the smart brain of an advanced lab setup called power hardware in the loop (PHIL), which is an extremely safe and useful lab system for electrical power system research and testing hardware and methods under various conditions. In this research, the capability of an RTDS to emulate the behavior of a pumped-storage hydropower plant including four Francis pump-turbines, four short penstocks, two common penstocks, a surge tank, and a long headrace tunnel is evaluated. Francis pump-turbines are modelled based on the hill chart-based interpolation and waterways including penstocks and headrace tunnel are modelled based on the polynomial approximation of a hyperbolic function. Finally, the results from the RTDS are presented and discussed. According to the results of the paper, we confirm that the RTDS can accurately emulate the hydraulic, mechanical, and electrical transients of a pumped-storage hydropower plant with a complex configuration. [ABSTRACT FROM AUTHOR]

As the climate crisis worsens, power grids are gradually transforming into a more sustainable state through renewable energy sources (RESs), energy storage systems (ESSs), and smart loads. Virtual power plants (VPP) are an emerging concept that can flexibly integrate distributed energy resources (DERs), managing manage the power output of each DER unit, as well as the power consumption of loads, to balance electricity supply and demand in real time. VPPs can participate in energy markets, enable self-scheduling of RESs, facilitate energy trading and sharing, and provide demand-side frequency control ancillary services (D-FCAS) to enhance the stability of the system frequency. As a result, studies considering VPPs have become the focus of recent energy research, with the purpose of reducing the uncertainty resulting from RESs distributed in the power grid and improving technology related to energy management system (EMS). However, comprehensive reviews of VPPs considering their formation, control techniques, and D-FCAS are still lacking in the literature. Therefore, this paper aims to provide a thorough overview of state-of-the-art VPP technologies for building sustainable power grids in the future. The review mainly considers the development of VPPs, the information transmission and control methods among DERs and loads in VPPs, as well as the relevant technologies for providing D-FCAS from VPPs. This review paper describes the significant economic, social, and environmental benefits of VPPs, as well as the technological advancements, challenges, and possible future research directions in VPP research. [ABSTRACT FROM AUTHOR]

Energy management for multi-home installation of solar PhotoVoltaics (solar PVs) combined with Electric Vehicles' (EVs) charging scheduling has a rich complexity due to the uncertainties of solar PV generation and EV usage. Changing clients from multi-consumers to multi-prosumers with real-time energy trading supervised by the aggregator is an efficient way to solve undesired demand problems due to disorderly EV scheduling. Therefore, this paper proposes real-time multi-home energy management with EV charging scheduling using multi-agent deep reinforcement learning optimization. The aggregator and prosumers are developed as smart agents to interact with each other to find the best decision. This paper aims to reduce the electricity expense of prosumers through EV battery scheduling. The aggregator calculates the revenue from energy trading with multi-prosumers by using a real-time pricing concept which can facilitate the proper behavior of prosumers. Simulation results show that the proposed method can reduce mean power consumption by 9.04% and 39.57% compared with consumption using the system without EV usage and the system that applies the conventional energy price, respectively. Also, it can decrease the costs of the prosumer by between 1.67% and 24.57%, and the aggregator can generate revenue by 0.065 USD per day, which is higher than that generated when employing conventional energy prices. [ABSTRACT FROM AUTHOR]

The world is facing many challenges to keep up with growing energy demand and greenhouse gas and pollutant emissions. A possible solution is to integrate renewable energy sources (RESs) into residences and create energy management systems (EMSs) that reduce consumption and relieve the main grid in critical hours. This paper is focused on analyzing different EMSs using solar photovoltaic (PV) modules and three energy storage systems (ESSs) to increase savings without affecting the user's needs, with thirty-three power consumption profiles and three energy tariffs over a 25-year investment to compare which solution presents the best economic result in each of the 297 analyzed scenarios. The results show that the higher the overall daily consumption values, the greater the profits for all EMSs. The lowest demand profiles lead to the best self-consumption and self-sufficiency results. PV-only systems with a tri-hourly tariff have the best overall results. In the case of battery operation, each case should be carefully analyzed in order to choose the correct technologies and tariff. The results also allowed us to verify that even though having more PV modules generates more energy, it can make a project less economically desirable. [ABSTRACT FROM AUTHOR]

Electrical energy is critical to the advancement of both social and economic growth. Because of its importance, the electricity industry has historically been controlled and operated by governmental entities. The power market is being deregulated, and it has been modified throughout time. Both regulated and deregulated electricity markets have benefits and pitfalls in terms of energy costs, efficiency, and environmental repercussions. In regulated markets, policy-based strategies are often used to deal with the costs of fossil fuel resources and increase the feasibility of renewable energy sources. Renewables may be incorporated into deregulated markets by a mix of regulatory and market-based approaches, as described in this paper, to increase the systems economic stability. As the demand for energy has increased substantially in recent decades, particularly in developing nations, the quantity of greenhouse gas emissions has increased fast, as have fuel prices, which are the primary motivators for programmers to use renewable energy sources more effectively. Despite its obvious benefits, renewable energy has considerable drawbacks, such as irregularity in generation, because most renewable energy supplies are climate-dependent, demanding complex design, planning, and control optimization approaches. Several optimization solutions have been used in the renewable-integrated deregulated power system. Energy storage technology has risen in relevance as the usage of renewable energy has expanded, since these devices may absorb electricity generated by renewables during off-peak demand hours and feed it back into the grid during peak demand hours. Using renewable energy and storing it for future use instead of expanding fossil fuel power can assist in reducing greenhouse gas emissions. There is a desire to maximize the societal benefit of a deregulated system by better using existing power system capacity through the implementation of an energy storage system (ESS). As a result, good ESS device placement offers innovative control capabilities in steady-state power flow regulation as well as dynamic stability management. This paper examines numerous elements of renewable integrated deregulated power systems and gives a comprehensive overview of the most current research breakthroughs in this field. The main objectives of the reviews are the maximization of system profit, maximization of social welfare and minimization of system generation cost and loss by optimal placement of energy storage devices and renewable energy systems. This study will be very helpful for the power production companies who want to build new renewable-based power plant by sighted the present status of renewable energy sources along with the details of several EES systems. The incorporation of storage devices in the renewable-incorporated deregulated system will provide maximum social benefit by supplying additional power to the thermal power plant with minimum cost. [ABSTRACT FROM AUTHOR]

Nowadays, with the increasingly prominent contradiction between environment and development, renewable energy technology has received extensive attention. However, due to natural fluctuation, there are many challenges in safety and stationarity in an electric power system with a large-scale portion of renewable energy. Meanwhile, the conventional electric power system in which the power supply follows the load change paradigm is gradually broken. Thanks to advanced information and communication technology, energy storage technology, and automatic control technology, the power supply, grid, load, and energy storage interactive electric power system regulation paradigm came into being. A virtual power plant (VPP) is a concrete realization of this regulation paradigm. In this paper, based on the characteristics of VPP service requirements, we propose a data-driven method to estimate and predict the network latency. First, we investigate and summarize the characteristics of a VPP participating in various auxiliary services and their demand for communication networks. Second, the practical implementation of a VPP network architecture, which combines the local network and the backhaul network, is presented based on a secure access gateway and VPP monitoring and scheduling platform for flexible resource aggregation and regulation. Then, based on a delay probe, a network latency acquisition method is proposed for a public backhaul network. Finally, a data-driven network latency processing method is proposed to support the VPP's participation in different communication requirements of auxiliary services. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) offer a feasible solution for integrating various types of distributed energy resources (DERs) into the power grid in the electricity market. This paper proposes a multi-time-scale rolling optimal scheduling for VPPs, enabling optimal self-scheduling plans across intra-week rolling scheduling, intra-day rolling dispatch, and real-time dispatch. The proposed method facilitates participation in energy and flexible ramping product (FRP) markets while considering the specific characteristics with complementary advantages for the aggregated renewable resources, gas turbines, energy storages, and flexible demands of each time scale. The flexible ramping products within the VPP framework are established, while the energy storage systems address fluctuations during dispatch periods. Case studies are conducted to verify the efficiency of the proposed method. The results show that the proposed method can obtain optimal self-scheduling plans within the multi-time framework and has better performance in economy and security operation in comparisons among cases. [ABSTRACT FROM AUTHOR]

Aiming to combat the problems of slow speed and poor accuracy of reliability evaluation of the power system in wind farms with energy storage, this paper proposes a method of reliability evaluation based on Latin hypercube important sampling (LHIS). Firstly, we aimed to establish the Latin hypercube important sampling evaluation model by combining the Latin hypercube sampling method with the important sampling method. Secondly, we aimed to optimize the sample probability distribution of the components and conduct hierarchical sampling of the system. Then, the comprehensive risk indicator (CRI) was proposed to evaluate the operational risk and the wind storage generation interrupted energy benefit (WSGIEB) was proposed to evaluate the contribution of the reliability. Finally, simulation experiments were carried out through various power system operation scenarios. The simulation results show that the proposed method is 47% higher than the improving importance sampling method (IM-IS) in evaluation speed and 33% higher than the improving importance sampling method in calculation accuracy. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) are a critical technology for distribution systems that can integrate various renewable energy resourcescontrollable loads and energy storage systems into one specific power plant through a distributed energy management system. This paper proposes a coordinated dispatch optimization model between the main grid and VPPs aiming to minimize both the power generation cost and total system active loss. When the time of the equivalent dispatching model is not divisible due to the existence of a time coupling constraint inside the VPPs, this model can obtain the global optimal solution through iteration between the main grid and the VPPs. By employing multi-parametric quadratic programming to obtain accurate critical domains and optimal cost functions, the convergence speed and stability are significantly improved. Additionally, a reactive power and voltage optimization technique leveraging the generalized Benders decomposition is presented for the coordination of the main grid and the VPPs. Moreover, the impact of distributed energy resource (DER) clusters on the main grid was studied, from which we proved that the proposed approach can expeditiously abate energy production expenditure and system active dissipation whilst enhancing the system equilibrium. [ABSTRACT FROM AUTHOR]

The world is targeting fully sustainable electricity by 2050. Energy storage systems have the biggest role to play in the 100% renewable energy scenario. This paper presents an optimal method for energy storage sizing and allocation in a power system including a share of wind farms. The power system, which is used as a test system, is a modified version of the IEEE 39 bus system. The optimization is applied using novel pharmacophore modeling (PM), which is compared to state-of-the-art techniques. The objective of the optimization is to minimize the costs of power losses, peak demand and voltage deviation. The PM optimization is applied using two methods, namely, weighting factor and normalization. The optimization and simulation are applied in the DIgSILENT power factory software application. The results show that normalization of PM optimization drives the power system to less cost in terms of total power losses by up to 29% and voltage deviation by up to 4% and better covers peak demand than state-of-the-art optimization techniques. [ABSTRACT FROM AUTHOR]

The aim of this paper is to evaluate the overall life cycle environmental impact of an adiabatic compressed air energy storage (ACAES) system, which is designed to achieve the best match between the power production of a photovoltaic (PV) power plant and the power demand from the final user. The electrical energy demand of a small town, with a maximum power load of about 10 MW, is considered a case study. The ACAES system is designed with a compressor-rated power of about 10 MW and charging and discharging times of 10 and 24 h, respectively. Different sizes of the PV plant, ranging from 20 to 40 MWp, and two different solutions for the compressed air storage, an underground cavern, and a gas pipeline, are analyzed. The aim of this analysis is to compare the impacts on human health, ecosystem quality, climate change, and resource consumption of the PV power generation plant and the integrated PV-ACAES system with those of a reference scenario in which the end user demand is met entirely by the grid. The best results in terms of a reduction in environmental impact in comparison to the reference scenario are obtained for a small PV plant (20 MW) without the ACAES section, with reductions of about 85–95% depending on the category of impact. The integration of the ACAES system improves energy self-consumption but worsens the environmental impact, especially for air storage in gas pipelines. The best configuration in terms of environmental impact is based on a 30 MW PV plant integrated with an ACAES section using an underground cavern for air storage and allows for improvements in the energy self-consumption of between 38% and 61%, with a reduction in the environmental impact compared to the reference scenario of about 80–91% depending on the impact category. [ABSTRACT FROM AUTHOR]

The present paper proposes the implementation of a new algorithm for the control of the speed regulators of Pelton wheel turbines, used in many of the pumped hydroelectric energy storage systems that operate in isolated electrical systems with high renewable energy participation. This algorithm differs substantially from the standard developments which use PID or PI governors in that, in addition to acting on the nozzle needles and deflectors, it incorporates a new inner-loop pressure stabilization circuit to improve frequency regulation and dampen the effects of the pressure waves that are generated when regulating needle position. The proposed algorithm has been implemented in the Gorona del Viento wind–hydro power plant, an installation which supplies the primary energy needs of the island of El Hierro (Canary Islands, Spain). Although, as well as its wind and hydro generation systems, the plant also has a diesel engine based generation system, the validation of the results of the study presented here focuses on situations in which frequency control is provided exclusively by the hydroelectric plant. It is shown that implementation of the proposed algorithm, which replaces the previous control system based on a classical PI governor, is able to damp the pressure wave that originates in the long penstock of the plant in the face of variations in non-dispatchable renewable generation, a situation which occurred with a high degree of relative frequency in the case study. The damper has enabled a substantial reduction in the cumulative time and the number of times that frequency exceeded different safety margins. Damper incorporation also reduced the number of under-frequency pump unit load shedding events by 93%. [ABSTRACT FROM AUTHOR]

Virtual Power Plants (VPPs) are efficient structures for attracting private investment, increasing the penetration of renewable energy and reducing the cost of electricity for consumers. It is expected that the number of VPPs will increase rapidly as their financial return is attractive to investors. VPPs will provide added value to consumers, to power systems and to electricity markets by contributing to different services such as the energy and load-following services. One of the capabilities that will become critical in the near future, when large power plants are retired, is grid-forming capability. This review paper introduces the concept of grid-forming VPPs along with their corresponding technologies and their advantages for the new generation of power systems with many connected VPPs. [ABSTRACT FROM AUTHOR]

The use of the conventional dual closed-loop control strategy by photovoltaic (PV) plants with grid-connected inverters may weaken the damping of a power system, which may aggravate low-frequency oscillations (LFOs). This influence will become more severe as the penetration of PV plants increases. Therefore, it is necessary to incorporate damping controls into PV plants to suppress LFOs. This paper proposed an additional compound damping control (ACDC) system that combines additional damping control (ADC) for the inverter with ADC-based dynamic power compensation control (DPCC), allowing hybrid energy storage systems (HESSs) to suppress LFOs. First, the feasibility of suppressing low-frequency oscillations in PV plants is demonstrated by the torque method and a small signal model. Then, an additional damping controller is added to the active power control link of the PV inverter to enhance the damping abilities of the system. However, given that the damping performance of PV plants with only ADC is limited by the compensated power, PV plants require devices that can rapidly compensate for the damping power. Therefore, we added the HESS to the DC bus and proposed DPCC. Finally, a three-machine nine-node system for a PV plant was modeled and simulated in the PSCAD platform. The simulation results showed that the proposed control strategy could provide effective damping for interarea oscillation. [ABSTRACT FROM AUTHOR]

The random nature of wind energy is an important reason for the low energy utilization rate of wind farms. The use of a compressed air energy storage system (CAES) can help reduce the random characteristics of wind power generation while also increasing the utilization rate of wind energy. However, the unreasonable capacity allocation of the CAES system results in high capital investment and a long payback period. In order to improve the economic benefits of energy storage, this paper studies the capacity configuration of compressed air energy storage systems under the condition of wind energy uncertainty. First, the typical hourly power distribution of wind power generation was obtained using historical data. Factors such as user load demand, time-of-use price of the power grid, system investment cost, power shortage cost, and power sales revenue were considered. Then, a model was built with the charging and discharging power and gas storage capacity of the CAES system as constraints, and the maximum return on investment and the minimum volume of the gas storage tank as targets. NSGA-II and TOPSIS optimal selection methods were used to solve the problem. Finally, the model was used to optimize a power operation case. The results show that in the case of an hourly load power demand of a factory using 3.2 MW, a wind farm would need to keep four wind turbines running every day, and a compressed air energy storage system with a rated power of 1 MW and a rated capacity of 7 MW would ensure the best project benefit. In this mode, 1.24 × 103 MWh of wind abandoning power could be reduced annually, 2.6 × 104 kg of carbon emissions could be reduced by increasing energy storage within the operation cycle, and the payback period of investment would only be 4.8 years. [ABSTRACT FROM AUTHOR]

This paper presents a model predictive approach to the energy-aware control of tasks' execution in an assembly line. The proposed algorithm takes into account both the need for optimizing the assembly line operations (in terms of the minimization of the total cycle time) and that of optimizing the energy consumption deriving from the operations, by exploiting the flexibility added by the presence of a local source of renewable energy (a common scenario of industries that are often equipped, e.g., with photovoltaic plants) and, possibly, also exploiting an energy storage plant. The energy-related objectives we take into account refer to the minimization of the energy bill and the minimization of the peaks in the power injected and absorbed from the grid (which is desirable also from the perspective of the network operator). We propose a mixed-integer linear formulation of the optimization problem, through the use of H-infinite norms, instead of the quadratic ones. Simulation results show the effectiveness of the proposed algorithm in finding a trade-off that allows keeping at a minimum the cycle time, while saving on the energy bill and reducing peak powers. [ABSTRACT FROM AUTHOR]

This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model's objective is to maximize benefits for the participating agents in a transactive energy context. The model's effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simulation results showed that the approach could effectively manage the operation of biogas systems and their interaction with the network operator. The developed model is suitable for systems fostering net metering charging and real-time pricing. [ABSTRACT FROM AUTHOR]

With the increasing share of variable and limitedly predictable renewable energy in power systems worldwide, ensuring reserve capacity to maintain the balance of supply and demand becomes more important. On the other hand, the development of the virtual power plant model (VPP) allows renewable sources and energy storage to participate in reserve service. This paper addresses the optimal reserve bidding strategy problem of a VPP comprising of renewable energy resources (RESs), energy storage systems (ESSs), and several customers. The VPP participates in balance capacity (BC), day-ahead (DA), and intra-day (ID) markets. The scheduling problem is formulated as a two-stage chance-constrained optimization model taking the uncertainty of RESs production, load consumption, and probability of reserve activation into account. The response of VPP after its reserve capacity is called and generated is also considered to increase the operational flexibility of VPP. The proposed model is implemented on a test VPP system, and the effects of RESs sizing, ESSs sizing, and the probability of reserve activation are analyzed. Results indicate that the proposed model can perform well under real-world conditions. [ABSTRACT FROM AUTHOR]

A virtual power plant takes advantage of interactive communication and energy management systems to optimize and coordinate the dispatch of distributed generation, interruptible loads, energy storage systems and battery switch stations, so as to integrate them as an entity to exchange energy with the power market. This paper studies the optimal dispatch strategy of a virtual power plant, based on a unified electricity market combining day-ahead trading with real-time trading. The operation models of interruptible loads, energy storage systems and battery switch stations are specifically described in the paper. The virtual power plant applies an optimal dispatch strategy to earn the maximal expected profit under some fluctuating parameters, including market price, retail price and load demand. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and is solved by the fruit fly algorithm. [ABSTRACT FROM AUTHOR]

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation, such as wind and solar, is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and a lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that the flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on the flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that energy storage systems integrated with a thermal power plant improve plant flexibility and participation in the energy and ancillary services markets, which improves plant financial performance. The study was funded by the U.S. Department Office of Fossil Energy FE-1 under award number DE-FE0031903. [ABSTRACT FROM AUTHOR]

Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential. [ABSTRACT FROM AUTHOR]

This research aims to optimize and compare the annual costs of energy services in buildings with critical loads and analyze case studies for hospitals and higher education institutions in the United States. Besides electricity and natural gas costs, the study considers all the infrastructure costs of capital amortization and maintenance. In addition, it studies energy resilience improvement due to distributed generation, including solar photovoltaic, solar thermal, internal combustion engine, and fuel cell sources. The optimization considers the electrical consumption, the heating and cooling demands, and the operational strategy of the energy storage systems. To simulate real scenarios, energy tariffs were modeled and considered, and final optimization results were produced. Some of the microgrid load was considered critical to model resilience benefits. The results show that if favorable energy tariffs are applied, the benefits of increasing energy resilience represent a novel market with high potential in facilities with significant critical loads. This methodology can be used in similar scenarios, adapting each particular load profile and critical load to provide a combined optimal solution regarding resilience and economic benefits. [ABSTRACT FROM AUTHOR]

Based on the Sustainable Development Goals outlined in the 2030 agenda of the United Nations, affordable and clean energy is one of the most relevant goals to achieve the decarbonization targets and break down the global climate change effects. The use of renewable energy sources, namely, solar energy, is gaining attention and market share due to reductions in investment costs. Nevertheless, it is important to overcome the energy storage problems, mostly in industrial applications. The integration of photovoltaic power plants with hydrogen production and its storage for further conversion to usable electricity are an interesting option from both the technical and economic points of view. The main objective of this study is to analyse the potential for green hydrogen production and storage through PV production, based on technical data and operational considerations. We also present a conceptual model and the configuration of a PV power plant integrated with hydrogen production for industry supply. The proposed power plant configuration identifies different pathways to improve energy use: supply an industrial facility, supply the hydrogen production and storage unit, sell the energy surplus to the electrical grid and provide energy to a backup battery. One of the greatest challenges for the proposed model is the component sizing and water electrolysis process for hydrogen production due to the operational requirements and the technology costs. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid increase in renewable energy sources (RESs), a Virtual Power Plant (VPP) concept has been developed to integrate many small-scale RESs, energy storage systems (ESSs), and customers into a unified agent in the electricity market. Optimal coordination among resources within the VPP will overcome their disadvantages and enable them to participate in both energy and balancing markets. This study considers a VPP as an active agent in reserve provision with an upward reserve capacity contract pre-signed in the balancing capacity (BC) market. Based on the BC contract's requirements and the forecasted data of RESs and demand, a two-stage stochastic optimization model is presented to determine the VPP's optimal scheduling in the day-ahead (DA) and balancing energy (BE) markets. The probability of reserve activation in the BE market is considered in this model. The ESS's reserve provision model is proposed so as not to affect its schedule in the DA market. The proposed optimal scheduling model is applied to a test VPP system; then, the effects of the BC contract and the probability of reserve activation on the VPP's trading schedule are analyzed. The results show that the proposed model has practical significance. [ABSTRACT FROM AUTHOR]

The paper proposes a coordinated frequency control strategy for Virtual Power Plant (VPPs), with the inclusion of Distributed Energy Resource (DERs), e.g., Solar Photo-Voltaic Generation (SPVG), Wind Generator (WG) as well as Energy Storage System (ESS). The objective is to improve the short-term dynamic response of the overall power system. The robustness of the proposed control is evaluated through a Monte Carlo analysis and a detailed modeling of stochastic disturbances of loads, wind speed, and solar irradiance. The impact of communication delays of a variety of realistic communication networks with different bandwidths is also discussed and evaluated. The case study is based on a modified version of the WSCC 9-bus test system with inclusion of a VPP. This is modeled as a distribution network with inclusion of a variety of DERs. [ABSTRACT FROM AUTHOR]

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development. [ABSTRACT FROM AUTHOR]

This paper aims to compute the performances of a smaller version of Solana power plant, with half the solar field, and 1 of 2 turbines in the power cycle, that can be built in Amman or Ma'an in Jordan. The climate conditions for both Amman and Ma'an are discussed thoroughly in the paper. Furthermore, a preliminary validation exercise performed by using measured monthly average values of electricity production from existing plants, a system advisor model (SAM) is used to predict the performances of the proposed Solana-like plants in Ma'an and Amman. The validation shows a good agreement with the measured data for different existing power plants. The simulation results including the monthly capacity factors suggest the annual operation in Ma'an maybe even better than the operation in Gila Bend, for an annual average capacity factor of about 41% for Ma'an vs. a capacity factor of about 39% for Gila Bend. This is mainly due to the best combination of direct normal irradiance (DNI) and the dry bulb temperature across the year in Ma'an versus Gila Bend. [ABSTRACT FROM AUTHOR]

Nowadays, the industrial world is undergoing a disruptive transformation towards more environmentally sustainable solutions. In the blue economy, this new approach is not only expressed in the domain of actual vessels, but also in the development of charging infrastructure, displaying a notable transition towards more eco-friendly solutions. The key focus lies in adopting flexible power systems capable of integrating renewable energy sources and storage technologies. Such systems play a crucial role in enabling a shift towards low-emission maritime transport. The emissions reduction goal extends beyond onboard shipboard distribution systems, encompassing also the design of supplying platforms and marinas. This study explores the implementation of a controlled DC microgrid tailored to efficient management of power flows within a yacht marina. Once having established the interfaces for the vessels at berth, the integration between the vessels, the onshore photovoltaic plant and the battery storage unit is made possible thanks to the coordinated management of multiple power converters. The overarching goal is to curtail reliance on external energy sources. Within this DC microgrid framework, a centralized controller assumes a pivotal role in orchestrating the power sources and loads. This coordinated management is essential to achieve sustainable operations, ultimately leading to the reduction of emissions from both ships and onshore power plants. [ABSTRACT FROM AUTHOR]

During the operation of solar and wind power plants, it is necessary to solve issues related to the guaranteed capacity of these plants, as well as the frequency stabilisation in the power system where they operate, and maintain an operating mode of self-sufficiency conditions. One of the solutions to these problems is the use of energy storage systems. This article proposes a mathematical model for the study of frequency and power regulation processes in power systems with distributed generation, which includes renewable energy resources and energy storage systems. The novelty of the model lies in the possibility of determining energy cost indicators based on instantaneous energy power data. The model allows us to estimate the conditions under which distributed generation becomes self-sufficient. The results of the model calculations of two variants of power system operation, which includes wind generators with a capacity of 1500 MW, demonstrate the ability of the proposed model to accurately reproduce the dynamics of the frequency stabilisation process. The calculation results of the energy-economic indicators of a real power system combined with a powerful subsystem of wind generation and a battery-type energy storage system prove the competitiveness of self-sufficient renewable energy power plants. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions and increasing the integration of new energy sources are key steps towards achieving sustainable development. Virtual power plants (VPPs) play a significant role in enhancing grid security and promoting the transition to clean, low-carbon energy. The core equipment of the VPP, the CHP unit, utilizes a thermal engine or power station to generate electricity and useful heat simultaneously. However, the intermittent and volatile nature of renewable energy sources, as well as the "heat-driven power generation" mode of combined heat and power (CHP) units, presents contradictions that severely affect their peak-shifting capability and lead to high carbon emissions. To address these issues, a novel VPP is established by integrating traditional power plants with carbon capture and hydrogen energy storage. This approach utilizes a "hydrogen energy storage–electric boiler" decoupling method to address the operational mode of CHP, strengthens the coupling relationship between electric and thermal hydrogen loads, and considers a tiered carbon-trading mechanism. With the net profit of the VPP as the optimization objective, the model balances economic and environmental considerations and establishes a low-carbon economic dispatch model for the VPP. A genetic algorithm is employed for solving, and three different dispatch strategies are set for simulation in three distinct seasonal scenarios. The comprehensive comparative analysis of the dispatch results reveals a reduction in carbon emissions and an increase in net profit to varying degrees across all three seasons. Overall, the proposed dispatch strategy demonstrates the ability to enhance the new energy-integration capacity and total revenue of a VPP while simultaneously achieving the goal of reducing carbon emissions. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RESs) and electric vehicles (EVs) have been introduced as efficient technologies to address environmentally friendly and sustainable energy sources. However, the widespread integration of distributed renewable sources into the power grid and the growing adoption of EVs pose new challenges for distribution network operators. These challenges necessitate careful management to mitigate their impacts, particularly in meeting the additional demand arising from EV charging. To achieve these targets, it is necessary to strategically integrate RESs and EVs. This study focuses on the optimal allocation and energy management of distributed energy resources (DERs) and electric vehicle parking lots (EVPLs), taking into account the inherent uncertainty in the output power of these resources. Notably, parking lots (PLs) utilize vehicle-to-grid (V2G) technology of EVs and aggregate and inject their power into the distribution system. Therefore, EVs as a motion type of energy storage system play a significant role, especially in the on-peak hours. The optimization problem is addressed using the salp swarm algorithm (SSA) while adhering to operational constraints related to the power system, as well as both DERs and EVPLs. The main goal is to simultaneously enhance the technical, economic, and environmental performance of the system, by solving a multi-objective optimization problem. The effectiveness of this approach is evaluated using the IEEE 33-bus distribution system, with the study considering five different scenarios. The simulation results reveal that the planned deployment of DERs, given their proximity to the load centers, has effectively mitigated the overload impacts resulting from EVs' charging. Furthermore, the implementation of a demand response program (DRP), cooperatively with the aforementioned resources, has significantly improved all key operating indicators of the system. [ABSTRACT FROM AUTHOR]

The rapid increase of electric vehicles (EVs) would lead to a rise in load demand on power grids but create different potential benefits as well. Those benefits comprise EVs serving as a mobile energy storage system to participate in adjusting the load on the power grids and helping manage renewable energy resources. This paper evaluates the effect of dynamic electricity prices and home photovoltaic (PV) system incentives on users' EVs charging behavior and potential impacts on grid load and household economy. This has been done by establishing and assessing three different optimized charging configurations and comparing them to an uncontrolled charging strategy. In this study, the charging incentives are applied to a representative sample of 100 households with EVs and PV systems in a metropolitan area. The results show that an optimized charging strategy based on the dynamic electricity tariff can reduce charging costs by 18.5%, while a PV-based optimized strategy can reduce the costs by 33.7%. Moreover, the PV-integrated optimization strategies significantly increase the utilization of PV energy by almost 46% on average, compared to uncontrolled charging. In addition, the simulations of this research have depicted the capability of using home PV systems' incentives to smoothen the charging profiles and hence significantly reduce the maximum grid load. However, the electricity price optimization strategy increases the aggregated charging peaks, which can only be slightly reduced by peak shaving. Therefore, an identical price signal for all households might be critical. Further analyses have shown that direct charging occurs simultaneously with household electricity assigned to a specific low-voltage grid while PV and price incentive charging configurations shift the charging peaks away from household load peaks. [ABSTRACT FROM AUTHOR]

The integration of an increasing share of Renewable Energy Sources (RES) requires the availability of suitable energy storage systems to improve the grid flexibility and Compressed Air Energy Storage (CAES) systems could be a promising option. In this study, a CO2-free Diabatic CAES system is proposed and analyzed. The plant configuration is derived from a down-scaled version of the McIntosh Diabatic CAES plant, where the natural gas is replaced with green hydrogen, produced on site by a Proton Exchange Membrane electrolyzer powered by a photovoltaic power plant. In this study, the components of the hydrogen production system are sized to maximize the self-consumption share of PV energy generation and the effect of the design parameters on the H2-CAES plant performance are analyzed on a yearly basis. Moreover, a comparison between the use of natural gas and hydrogen in terms of energy consumption and CO2 emissions is discussed. The results show that the proposed hydrogen fueled CAES can effectively match the generation profile and the yearly production of the natural gas fueled plant by using all the PV energy production, while producing zero CO2 emissions. [ABSTRACT FROM AUTHOR]

The demand for decarbonization calls for building up a nearly 100% renewable electricity resulting in Grid-forming (GFM) capability requirements. The foregoing paradigm shifts from synchronous AC systems to converter-based systems that need to remain stable and self-synchronous while providing GFM services. However, as this article's analysis in the introduction, achieving such goals inevitably necessitates the implementation of a PLL controller and energy storage in a wind turbine, whereas it is not suitable to operate in a weak energy system. To tackle this issue, a novel grid-forming method is proposed. The suggested idea calls for creating a DC voltage controller in a grid-side converter that mimics inertia response and applying a Rotor kinetic energy storage (RKES) controller in a Generator-side converter. Moreover, a coordinated controller of RKES controllers and conventional low voltage ride-through (LVRT) is proposed to gain increases in dynamic performance and maintain grid-forming capabilities in the transient process. Extensive modeling, experimental results based on a semi-physical platform, and an actual wind farm demonstration project are provided to validate the proposed controls. The results demonstrate the effectiveness of the presented method when applied to the future 100% renewable electricity. [ABSTRACT FROM AUTHOR]

In this paper, the appropriate rated power of battery energy storage system (BESS) and the operating limit capacity of wind farms are determined considering power system stability, and novel output control methods of BESS and wind turbines are proposed. The rated power of BESS is determined by correlation with the kinetic energy that can be released from wind turbines and synchronous generators when a disturbance occurs in the power system. After the appropriate rated power of BESS is determined, a novel control scheme for quickly responding to disturbances should be applied to BESS. It is important to compensate the insufficient power difference between demand and supply more quickly after a disturbance, and for this purpose, BESS output is controlled using the rate of change of frequency (ROCOF). Generally, BESS output is controlled by the frequency droop control (FDC), however if ROCOF falls below the threshold, BESS output increases sharply. Under this control for BESS, the power system’s stability can be improved and the operating limit capacity of wind farms can be increased. The operating limit capacity is determined as the smaller of technical limit and dynamic limit capacity. The technical limit capacity is calculated by the difference between the maximum power of the generators connected to the power system and the magnitude of loads, and the dynamic limit capacity is determined by considering dynamic stability of a power system frequency when the wind turbines drop out from a power system. Output of the dynamic model developed for wind turbine is based on the operating limit capacity and is controlled by blade pitch angle. To validate the effectiveness of the proposed control method, different case studies are conducted, with simulations for BESS and wind turbine using Power System Simulation for Engineering (PSS/E). [ABSTRACT FROM AUTHOR]

Research on energy storage plants has gained significant interest due to the coupled dispatch of new energy generation, energy storage plants, and demand-side response. While virtual power plant research is prevalent, there is comparatively less focus on integrated energy virtual plant station research. This study aims to contribute to the integrated energy virtual plant station research by exploring the relationship between the integrated energy electro-thermal coupling capacity, various forms of electro-thermal integrated energy response, and electro-thermal integrated energy storage. Analyzing the attributes of an integrated energy microgrid, including energy storage characteristics, time-of-use tariffs, and electric and thermal loads, is crucial. A grid-connected microgrid with cogeneration systems, electric boilers, fuel cells, and energy storage systems is used as an illustrative example. The dispatching method prioritizes multiple complementary energy sources while considering the integrated energy demand response. The study presents different models for the electricity demand and thermal energy demand response and introduces the design of a wholesale power trader involved in building energy storage facilities and participating in the demand response. To verify the feasibility and rationality of the integrated energy demand response scenario, three different schemes are compared, and an economic analysis is conducted. [ABSTRACT FROM AUTHOR]

As the share of highly variable photovoltaic (PV) and wind power production increases, there is a growing need to smooth their fast power fluctuations. Some countries have set power ramp rate (RR) limits that the output powers of power plants may not exceed. In this study, the effects of RR limit on the sizing of energy storage systems (ESS) for PV, wind, and PV–wind power plants are examined. These effects have been studied prior for PV power plants. However, for the wind and PV–wind power plants, the effects of the RR limit are studied comprehensively for the first time. In addition, the effects of the size of the power plant are considered. The study is based on climatic measurements carried out with a sampling frequency of 10 Hz for a period of 153 days. The modeling of the PV and wind powers and the simulation of the RR-based control algorithm of the ESS were completed using MATLAB. The results show that as the applied RR limit increased from 1%/min to 20%/min, the required relative energy capacities of the ESSs of the PV, wind, and PV–wind power plants decreased roughly 88%, 89%, and 89%, respectively. The required relative power capacities of the ESSs of the PV, wind, and PV–wind power plants decreased roughly 15%, 12%, and 20%, respectively. The utilization of the ESSs was found to decrease as the applied RR limit increased and as the size of the power plant grew. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a methodology for dimensioning an energy storage system (ESS) to the generation data measured in an operating wave energy generation plant connected to the electric grid in the north of Spain. The selection criterion for the ESS is the compliance of the power injected into the grid with a specific active-power ramp-rate limit. Due to its electrical characteristics, supercapacitor (SC) technology is especially suitable for this application. The ESS dimensioning methodology is based on a mathematical model, which takes into account the power generation system, the chosen ramp-rate limit, the ESS efficiency maps and electrical characteristics. It allows one to evaluate the number of storage cabinets required to satisfy the needs described, considering a compromise between the number of units, which means cost, and the reliability of the storage system to ensure the grid codes compliance. Power and energy parameters for the ESS are obtained from the calculations and some tips regarding the most efficient operation of the SC cabinets, based on a stepped switching strategy, are also given. Finally, some conclusions about the technology selection will be updated after the detailed analysis accomplished. [ABSTRACT FROM AUTHOR]

The increasing limitations in the use of fossil fuels due to their limited availability and pollution have increased the use of renewable energies and storage systems for electricity generation. To achieve the goals of the integration of renewable energy, sizing and management methods for hybrid plants are needed to make investments profitable and attractive in these resources. This work presents an optimization method for the sizing and operation of hybrid plants with storage, choosing the best combination of technologies based on resource availability, installation costs and market prices, maximizing an economic index such as the net present value. One of the main contributions of this work is to reduce the oversizing that occurs in traditional methods through a penalty term for lost energy, encouraging investment in batteries to store excess energy above the point of interconnection (POI). In addition, it is intended to cover gaps such as the operation in coupled markets with different execution periods to maximize the benefits of the investment made and to contemplate different generation alternatives together with storage. The presented method is tested through sizing and operation simulations to demonstrate its potential. The presented method is tested through sizing and operation simulations to demonstrate its potential. In scenario A, the best combination of solar energy, photovoltaic energy and storage, is chosen. In scenario B, it is shown how the curtailment of the oversizing is reduced in some months by more than 5%. In scenario C, for daily operation in coupled markets, it is possible to improve the benefits from 0.7% to 37.04% in the days of the year. [ABSTRACT FROM AUTHOR]

The integration of distributed energy resources, such as wind farms (WFs) and energy storage systems (ESSs), into distribution networks can lower the economic cost of power generation. However, it is essential to consider operational constraints, including loading margin, which ensures the security line contingency. This study aims to develop a comprehensive hourly distribution network reconfiguration (HDNR) model to minimize the economic cost for the power generation company. The model considers the optimal allocation of WFs and ESSs in terms of capacity and location, as well as the hourly status of the distribution network switches, based on security constraints. The proposed model is applied to an IEEE 33-bus distribution test system, and the capacities and locations of WFs and ESSs are determined. The impacts of security constraints on the optimal capacities and locations of WFs and ESSs, and the hourly configuration of the distribution network, are analyzed based on two case studies. In Case Study I, the model is solved with HDNR conditions, while Case Study II is solved without these restrictions, for comparison purposes. The results show that the optimal allocation of WFs and ESSs is affected by security constraints when HDNR is considered and highlight the crucial role of security constraints under contingency conditions, such as line outages. In the test system, three WFs and two ESSs are optimally allocated, with changes in capacity and location as the loading margin varies. [ABSTRACT FROM AUTHOR]

This article addresses the development of the energy compensation method used for the design of hybrid energy storage systems—HBESS. The combination of two battery technologies offers better cost and performance when considering microgrid systems to provide uninterrupted power to sensitive loads (substation auxiliary system) and also provides greater energy security. In the event of a failure, the load needs to continue operating, and batteries such as lithium ions have a fast response, but are expensive for large-scale systems. However, some technologies offer low-cost and good availability of energy for long hours of discharge, such as lead–acid batteries. Consequently, different battery technologies can be used to meet all the needs of the sensitive loads. A specific method for sizing a HBESS was developed for islanded microgrids to support sensitive loads. This method was developed to meet the demand for substations outside the Brazilian standard of power systems that lack an uninterrupted and reliable energy source. The method is validated by designing a microgrid to support the auxiliary systems of a transmission substation in northeastern Brazil. The results showed a system with a capacity of 1215 kWh of lead-carbon and 242 kWh of lithium ions is necessary to maintain an islanded microgrid for at least 10 h. Furthermore, the microgrid comprises a PV plant with an AC output power of 700 kW in connected operation and 100 kW when islanded from the grid. [ABSTRACT FROM AUTHOR]

Complexity is a widely acknowledged feature of urban areas. Among the different levels to which this definition applies, the energy sector is one of the most representative of this way of conceiving cities. An evidence of this complexity can be detected in the growing impact of prosumers. Prosumers produce energy to meet their own demands, distribute it directly to neighbors and, eventually, store the energy neither consumed nor distributed. The modelling of distribution networks is a challenging task that requires ad hoc models to simulate the mutual energy exchanges occurring among prosumers. To serve at this scope, this paper proposes an agent-based model aiming at determining which operating conditions enhance the energy distribution among prosumers and diminish the supply from traditional power plants. An application of the model within a residential territory is then presented and simulations are conducted under two scenarios: the first investigating the distribution among prosumers equipped with photovoltaics (PV) systems, the second integrating energy storage systems to PV panels. Both scenarios are studied at varying the installed PV capacity within the territory, the allowed distance of connection among prosumers, as well as the rate of utilization of the links of the network. Results from the simulated case study reveal that the energy distribution among prosumers can be enhanced by providing short-range links for the electricity exchange. Similar advantages can be achieved by integrating storage systems to PV, along with a significant reduction in the electricity requested to the centralized grid. [ABSTRACT FROM AUTHOR]

The decarbonisation targets of the People's Republic of China are ambitious. Their achievement relies on the large-scale deployment of variable renewable energy sources (VRES), such as wind and solar. High penetration of VRES may lead to balancing problems on the grid, which can be compensated by increasing the shifting flexibility capacity of the system by integration with energy storage, e.g., by installing additional electricity storage. Pumped Hydro Storage (PHS) is the most diffused electricity storage technology at the global level and the only fully mature solution for long-term electricity storage. China already has the highest PHS capacity installed worldwide and plans to increase it strongly before 2030. The present study, based on the data from the "Pumped Storage Tracking Tool" of the International Hydropower Association, investigates the potential for technological improvement of the existing and future PHS fleet in China. The aims of adopting advanced PHS solutions allow China to better cope with the task of balancing the VRES production. The potential for adopting advanced PHS solutions is evaluated through five different intervention possibilities (here referred to as scenarios). These scenarios consider revamping part of the operational Pumped Storage Plant (PSP) fleet and redesigning future installations that are already planned. As a result, considering all the major technical and authorisation process constraints, 4.0% (5.2 GW) of the 132 GW fleet expected to be commissioned before 2035 could additionally adopt advanced PHS in a high-potential scenario. Meanwhile in the medium and low potential scenarios, the quota can reach 11.1% (14.6 GW) and 26.2% (34.5 GW), respectively. Furthermore, policy recommendations are elaborated to promote, facilitate, and support the adoption of these advanced PHS solutions. [ABSTRACT FROM AUTHOR]