Search

A comprehensive review of uncertainties in power systems, covering modeling, impact, and mitigation, is essential to understand and manage the challenges faced by the electric grid. Uncertainties in power systems can arise from various sources and can have significant implications for grid reliability, stability, and economic efficiency. Australia, susceptible to extreme weather such as wildfires and heavy rainfall, faces vulnerabilities in its power network assets. The decentralized distribution of population centers poses economic challenges in supplying power to remote areas, which is a crucial consideration for the emerging technologies emphasized in this paper. In addition, the evolution of modern power grids, facilitated by deploying the advanced metering infrastructure (AMI), has also brought new challenges to the system due to the risk of cyber-attacks via communication links. However, the existing literature lacks a comprehensive review and analysis of uncertainties in modern power systems, encompassing uncertainties related to weather events, cyber-attacks, and asset management, as well as the advantages and limitations of various mitigation approaches. To fill this void, this review covers a broad spectrum of uncertainties considering their impacts on the power system and explores conventional robust control as well as modern probabilistic and data-driven approaches for modeling and correlating the uncertainty events to the state of the grid for optimal decision making. This article also investigates the development of robust and scenario-based operations, control technologies for microgrids (MGs) and energy storage systems (ESSs), and demand-side frequency control ancillary service (D-FCAS) and reserve provision for frequency regulation to ensure a design of uncertainty-tolerance power system. This review delves into the trade-offs linked with the implementation of mitigation strategies, such as reliability, computational speed, and economic efficiency. It also explores how these strategies may influence the planning and operation of future power grids. [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]

Penetration of renewable energy resources (RERs) in the power grid continues to increase as we strive toward a greener environment for the future. While they have many advantages, most RERs possess little or no rotational kinetic energy, thereby threatening the frequency stability of future power grids. Energy storage systems (ESSs) can be used to mitigate this problem, as they are capable of providing virtual inertia to the system. This paper proposes a novel analytical approach for sizing ESSs to provide inertial support to the grid and maintain frequency stability in presence of RERs. This method analytically estimates the total inertia of the system using probability distributions of the outage states of conventional generators and RERs. RERs are modeled as multi-state units, considering the variability of their output power due to changes in weather conditions and also the forced outages of their equipment. The ESS is utilized to provide virtual inertia to the grid in the form of active power once the estimated system inertia falls below the minimum required during a disturbance. The efficacy of the proposed approach is tested on the IEEE 39 bus system and the results obtained by the analytical approach are validated using Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

In the modern world, the consumption of oil, coal natural gas, and nuclear energy has been causing by a serious environmental problem and an ongoing energy crisis. The generation and consumption of renewable energy sources (RESs) such as solar and wind tidal, can resolve the problem but the nature of the RESs is fluctuating and intermitted. This evolution brings a lot of challenges in the management of electrical grids. The paper reviewed the advancements in energy storage technologies for the development of a smart grid (SG). More attention was paid to the classification of energy storage technologies based on the form of energy storage and based on the form of discharge duration. The evaluation criteria for the energy storage technologies have been carried out based on technological dimensions such as storage capacity, efficiency, response time, energy density, and power density, the economic dimension such as input cost and economic benefit; and the environmental dimension such as emission and stress on ecosystem, social demission such as job creation and social acceptance were also presented in this paper. [ABSTRACT FROM AUTHOR]

This paper presents a techno-economic analysis of 'Picogrid' in hilly remote areas of North-East India, where availability of conventional grid power is either none or limited. A Picogrid is a small microgrid (typically a few tens of kW) containing renewable energy sources like solar, wind, small hydro etc. with battery based energy storage of limited capacity. A hybrid solar PV-Hydro based Picogrid of 7.2 kW capacity in a remote hilly area is analyzed, where the solar irradiance varies between 3.5 and 6.2 kWh/Day/m2, a water fall head lies between 1 and 30 m and water flow rate varies from 100 to 50,000 L/h. The study reveals that, the annual total energy generation varies between 1200 and 5000 kWh/kW/Year. Whereas the annual average daily yield and Capacity Utilization Factors for such system are 9 kWh/kWp/Day and 40%, respectively at highest possible water head and flow rate as mentioned above. The optimized Picogrid system is shown to have a levelised cost of electricity of 1.4 INR (0.017 USD) and 1.8 INR (0.022 USD) per kWh for 100% and 30% equity investment, respectively. The energy produced by these methods can be provided in rural areas thereby making electricity and revenue producing probabilities concurrently. [ABSTRACT FROM AUTHOR]

Vanadium Flow Batteries (VFBs) are a stationary energy storage technology, that can play a pivotal role in the integration of renewable sources into the electrical grid, thanks to unique advantages like power and energy independent sizing, no risk of explosion or fire and extremely long operating life. The first part of this paper presents the main features and the basic performance parameters of VFB, which determine their electric, hydraulic, thermal, and aging feature. The latter part outlines the strengths and weaknesses of the technology, the services that it can provide to the grid, and a short economic analysis. After presenting the fundaments of the technology, prospects and trends of VFBs deployment are outlined. Most of the considerations highlighted in this paper are inspired to studies performed on an industrial-size VFB operated at the Electrochemical Energy Storage and Conversion Lab (EESCoLab) at the University of Padua (Italy). [ABSTRACT FROM AUTHOR]

With the large-scale access of renewable energy, the randomness, fluctuation and intermittency of renewable energy have great influence on the stable operation of a power system. Energy storage is considered to be an important flexible resource to enhance the flexibility of the power grid, absorb a high proportion of new energy and satisfy the dynamic balance between the supply and demand of a system. At present, the cost of energy storage is still high, and how to achieve the optimal energy storage configuration is the primary problem to be solved. Therefore, the current research progress in energy storage application scenarios, modeling method and optimal configuration strategies on the power generation side, grid side and user side are summarized in this paper. On this basis, the shortcomings that still exist of energy storage configuration research are summarized, and the future research direction for energy storage configuration is prospected. This review can provide reference for the latest development and future research and innovation direction for energy storage configuration. [ABSTRACT FROM AUTHOR]

The loss of distribution networks caused by various electrical motors including transformers and generators can significantly affect the efficiency and economical operation of the power grid, especially for new power systems with high penetration of renewable energies. In this paper, the potential of using an energy storage system (ESS) for loss reduction is investigated, where a novel two-stage method for key-bus selection and ESS scheduling is proposed. At the first stage, the most sensitive key buses to the variation of load are selected by using the loss sensitive factors (LSF) method. At the second stage, ESS scheduling is conducted by solving an optimization problem with uncertainties caused by high penetration of renewable energies, where the uncertainties are characterized by confidence levels. The optimal scheduling of ESS including locations, capacities, and working modes are obtained at the second stage. The effectiveness of the proposed method is demonstrated via numerical simulations. The influences of capacities of ESS and confidence levels with respect to uncertainties are also analyzed. It is demonstrated that the loss-reduction performances can be improved if the ESSs are deployed on the buses selected by the LSF method and operated under the developed optimal scheduling method. [ABSTRACT FROM AUTHOR]

Studies have shown that the role of energy storage systems in human life is increasing day by day. Therefore, this research aims to study the latest progress and technologies used to produce energy storage systems. It also discusses and compares the most recent methods used by researchers to model and optimize the size of these tools and evaluates the strengths and weaknesses of each. Investigations have shown that using energy storage systems in hybrid stand-alone power generation systems based on renewable energy increases the reliability of the power generation systems and increases their efficiency. It has also reduced the cost of transmitting the power grid to remote areas. Furthermore, this study showed that advances in energy storage technology in recent years have led to the development and promotion of clean microgrids. In addition, this review paper also addresses energy storage technology issues and proposes practical and applied solutions. [ABSTRACT FROM AUTHOR]

The economic development of any country is closely linked with the consumption of energy. Therefore, international policies encourage increasing penetration of renewable energy sources (RES) into the electrical grid in order to reduce CO2 emissions and cover ever-increasing demands. However, high variance of RES complicates their integration into power systems and complicates their transition from central to distributed energy sources. On the other hand, increasing the penetration of RES in electrical networks stimulates the demand for large capacity for energy storage. This paper presents a new approach to optimize the size of on-grid renewable energy systems integrated to pumped storage system using Salp Swarm Algorithm (SSA). This approach allows the examination of various energy sources and their combination to handle the optimal configuration of the hybrid system. The simulation and optimization process of the studied system have been carried out by MATLAB programming. The impact of the system under study on the grid is examined according to the power exchange values between the system and the grid. Moreover, different scenarios have been introduced for optimal operation. The simulation results indicate that these hybrid systems can reduce power exchange with the grid and ensure that the proposed system is economically and environmentally feasible. Furthermore, the results indicate the technical feasibility of seawater hydroelectric power plants in increasing the capacity of the electric grid to allow for high penetration of RES. Finally, the results showed that the best minimum value of the objective function is 3.9113 and showed that CO2 emission can be reduced about 29.65% per year compared to the conventional power plants. [ABSTRACT FROM AUTHOR]

Electrical Energy Storage (EES) technologies have received considerable attention over the last decade because of the need to reduce greenhouse gas emission through the integration of renewable energy sources. Renewable sources have an intermittent power output to the electrical grid, thus EES represents a strategic solution in balancing electrical grids and enables the decarbonisation of the energy sector. Cryogenic Energy Storage (CES) is a novel method of EES falling within the thermo-mechanical category. It is based on storing liquid cryogenic fluids after their liquefaction from an initially gaseous state. A particular form of CES, Liquid Air Energy Storage (LAES), has gained growing attention respect to other cryogens. The current state of LAES is still at the development and demonstration stage since no commercial or pre-commercial plants have been built. This technology has been developed in different ways throughout its history (from 1977), and, to the best of our knowledge, no review paper has been published so far about the CES topic. Therefore, the present paper intends to provide a clear picture of the CES/LAES virtues in the literature as well as the challenges associated to the system to be commercially viable. For this purpose, this review includes: an investigation of the properties of cryogens and different CES processes as well as the main ways the system could be combined to other facilities to further enhance the energy efficiency, in particular the combination to a refrigerated warehouse with cold energy recovery from the cryogen evaporation. [ABSTRACT FROM AUTHOR]

The rise of electric vehicles (EVs) has initiated a significant transformation in both the transportation and energy sectors. With the increasing adoption of EVs, their interaction with the power grid is becoming more critical. A notable and innovative concept emerging in this context is Vehicle-to-Home (V2H) operations, which utilize the battery storage capabilities of EVs to meet residential energy demands. Our research provides a way of economically evaluating V2H operations under various environmental conditions including pricing, seasonal differences, and EV operations. The proposed model aids in understanding the optimal operation of V2H and identifying the factors that encourage its adoption. Furthermore, optimizing V2H use can promote renewable energy utilization, providing an additional solution to address its intermittent nature. The findings highlight the potential of V2H operations to contribute to more economically efficient energy systems, provided that supportive policies and adaptive technologies are in place. [ABSTRACT FROM AUTHOR]

A new inverter control approach, called enhanced virtual synchronous machine (eVSM), is proposed based on the VSM concept. Unlike existing VSM approaches, the eVSM does not emulate the rotating inertia based on an assumption of the unlimited energy storage, but it deploys the physically existing inertia of the dc-link element. The eVSM adopts an innovative way of enlarging the inertia utilization range, which obviates the need for having a large dc-link element or a dedicated battery storage system, while still providing the same inertia response of an equivalent synchronous machine. Theoretical developments and numerical results presented in this paper confirm that the proposed eVSM can present a stabilizing support to the grid similar to a synchronous machine despite the small size of its dc-link element. Moreover, its transient responses can be improved beyond those of conventional synchronous machines thanks to the possibility of more flexibly adjusting damping and governor functions. [ABSTRACT FROM AUTHOR]

This paper focuses on a review of the state of the art of future power grids, where new and modern technologies will be integrated into the power distribution grid, and will become the future key players for electricity generation, transmission, and distribution. The current power grids are undergoing an unprecedented transformation from the original design, changing the way how energy has been produced, delivered, and consumed over the past century. This new energy era includes the integration of renewable sources such as wind and solar, supported by the distributed or community energy storage, to power distribution grids through innovative high-frequency magnetic links and power-electronic converters. The use of emission free transportation, such as electric vehicles, and energy efficient technologies, such as superconducting generators and storage systems, are also rapidly emerging and will be integrated into the power grids in the foreseeable future. However, it is necessary to reconsider the current paradigms of system analysis and plan with a focus on how to achieve the most flexible, efficient, and reliable power grid for the future––the one that enables operation in a domain which is very different than the current one to deliver the services to consumers at an affordable cost. [ABSTRACT FROM AUTHOR]

Severe pollution induced by traditional fossil fuels arouses great attention on the usage of plug-in electric vehicles (PEVs) and renewable energy. However, large-scale penetration of PEVs combined with other kinds of appliances tends to cause excessive or even disastrous burden on the power grid, especially during peak hours. This paper focuses on the scheduling of PEVs charging process among different charging stations and each station can be supplied by both renewable energy generators and a distribution network. The distribution network also powers some uncontrollable loads. In order to minimize the on-grid energy cost with local renewable energy and non-ideal storage while avoiding the overload risk of the distribution network, an online algorithm consisting of scheduling the charging of PEVs and energy management of charging stations is developed based on Lyapunov optimization and Lagrange dual decomposition techniques. The algorithm can satisfy the random charging requests from PEVs with provable performance. Simulation results with real data demonstrate that the proposed algorithm can decrease the time-average cost of stations while avoiding overload in the distribution network in the presence of random uncontrollable loads. [ABSTRACT FROM PUBLISHER]

Large-scale renewable integration presents an effective way to decarbonize power grids, but carries increased risk of supply shortfalls owing to its volatility and uncertainty. Storage is a promising option to improve the generation adequacy of renewable. Thus, capacity credit assessment of renewable and storage is crucial in ensuring adequate generation capacity to meet loads. However, efficiently and accurately assessing capacity credit of these resources is challenging due to temporal dependencies in the operational time series (net loads and conventional generation units) and the need for extensive operation simulations. This paper develops a comprehensive multi-time-scale assessment framework integrating analytical and simulation methods to calculate the capacity credit of renewable and storage, thus capturing temporal features of these time series. Then, an interval-based strategy is proposed to simulate system operations, incorporating demand response in key scenarios. Furthermore, partitioning around medoids clustering and parallel computing techniques are employed to greatly accelerate the numerous operations for capacity credit assessment. The proposed method is validated using the RTS-79 system and a provincial real-world power grid in China. The results indicate that the developed framework can achieve efficient and refined capacity credit assessment and thus evaluate the impact of storage on the capacity credit. • Propose a novel method to quantify temporal features of operational time series for capacity credit (CC) assessment. • Develop a multi-time-scale CC assessment framework with an interval-based strategy to capture temporal features. • Utilize partitioning around medoids clustering and parallel computing to greatly enhance calculation efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a microgrid (MG) energy management strategy by considering renewable energy and battery storage systems. Renewable energy, including wind power generation and solar power generation, is integrated into the distribution network, for which is formulated the optimal dispatch model of mixed-power generation by considering the charging/discharging scheduling of battery storage systems. The MG system has an electrical link for power exchange between the MG and the utility during different hours of the day. Based on the time-of-use (TOU) and all technical constraints, an enhanced bee colony optimization (EBCO) is proposed to solve the daily economic dispatch of MG systems. In the EBCO procedure, the self-adaption repulsion factor is embedded in the bee swarm of the BCO in order to improve the behavior patterns of each bee swarm and increase its search efficiency and accuracy in high dimensions. Different modifications in moving patterns of EBCO are proposed to search the feasible space more effectively. EBCO is used for economic energy management of grid-connected and stand-alone scenarios, and the results are compared to those in previous algorithms. In either grid-connected or stand-alone scenarios, an optimal MG scheduling dispatch is achieved using micro-turbines, renewable energy and battery storage systems. Results show that the proposed method is feasible, robust and more effective than many previously-developed algorithms. [ABSTRACT FROM AUTHOR]

The diminishing availability of fossil fuels will necessitate a shift toward renewable energy resources to supply vital electrical energy needs in the future. Two abundant renewable energy sources, solar and wind, are increasingly cost-competitive and also offer the potential of decentralized, and hence more robust, sourcing. However, the intermittent nature of solar and wind power can present difficulties in connection with integrating them into the main electric power grid. In this paper, we present an agent-based architecture for coordinating locally connected micro-grids, thereby supporting more cost-effective integration into the main power grid. These interconnected micro-grids, with renewable energy sources and energy storage devices, employ agents so that each micro-grid can choose to save or resell its stored energy in an open market in order to optimize its utility and costs. We show via simulation experiments how the micro-grid agent society operates and adapts under varying conditions of renewable energy availability and energy demand patterns. Such a system provides not only financial advantages but also local autonomy and a more robust energy distribution. In addition, these interconnected agents can also facilitate the reduction of carbon emission. In this connection, we compare five different micro-grid energy trading strategies. Thus, the experimental design and evaluation are motivated by a policy modeling perspective whereby the utility of an energy policy to a community (i.e., the strategy) is computed based on two attributes, the financial gain and the reduction in carbon emissions. Further, by means of 'what-if' analysis, different energy policies that can potentially be employed by a community are compared against one another. Also, the implications of these policies for a community are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient power management approach for the 24 h-ahead optimal maneuver of Mega–scale grid–connected microgrids containing a huge penetration of wind power, dispatchable distributed generation (diesel generator), energy storage system and local loads. The proposed energy management optimization objective aims to minimize the microgrid expenditure for fuel, operation and maintenance and main grid power import. It also aims to maximize the microgrid revenue by exporting energy to the upstream utility grid. The optimization model considers the uncertainties of the wind energy and power consumptions in the microgrids, and appropriate forecasting techniques are implemented to handle the uncertainties. The optimization model is formulated for a day-ahead optimization timeline with one-hour time steps, and it is solved using the ant colony optimization (ACO)-based metaheuristic approach. Actual data and parameters obtained from a practical microgrid platform in Atlanta, GA, USA are employed to formulate and validate the proposed energy management approach. Several simulations considering various operational scenarios are achieved to reveal the efficacy of the devised methodology. The obtained findings show the efficacy of the devised approach in various operational cases of the microgrids. To further confirm the efficacy of the devised approach, the achieved findings are compared to a pattern search (PS) optimization-based energy management approach and demonstrate outperformed performances with respect to solution optimality and computing time. [ABSTRACT FROM AUTHOR]

• The state-of-the-art research advances in power system restoration with large renewable penetration are reviewed from different system levels, i.e., transmission system, distribution system, and coordinated transmission and distribution system. • The methods of handling renewable power uncertainty during system restoration are summarized. • The laboratory validations and practical applications of the renewable power system restoration strategies are reviewed. • Promising research directions for renewable system restoration are provided, including uncertainty handling, artificial intelligence techniques, transient stability issues, cyber-physical interlinking, and multi-energy coupling. The catastrophic blackout events and ever-increasing penetration of renewable power generation highlight an advanced restoration strategy to effectively and reliably employ renewable power generation to contribute to renewable power system restoration. This paper reviews the research advances of power system restoration involving large renewable penetration, and the methods of handling renewable power uncertainty during restoration are also summarized. First, the transmission system restoration processes are divided into three sequential stages: a) black-start, b) network reconfiguration and c) load restoration, and the research advances of these three restoration stages involving large renewable generation are presented. Then, the distribution system restoration assisted by multiple flexible resources, such as renewable distributed generators, remotely-controlled switches, energy storage systems, and soft open points, are reviewed with emerging techniques, including micro-grids, multi-agent systems, repair crews, and mobile power sources. Furthermore, with the growing activeness and flexibility of the distribution system, the coordinated transmission and distribution system restoration and their information interactions are also discussed. Finally, for practical applications, the laboratory validations of restoration strategies using realistic power grid data, real-world restoration strategies, decision support systems, and field tests of black-start procedures are introduced to complete this literature review. Effectively deploying renewable power sources can significantly improve the power system restoration efficiency, and their inherent uncertainty should be carefully handled. Moreover, promising research trends are provided to improve the power system restoration with large renewable penetration. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) uses many small on-site energy harvesting deployments at individual buildings to generate electricity. DG has the potential to make generation more efficient by reducing transmission and distribution losses, carbon emissions, and demand peaks. However, since renewables are intermittent and uncontrollable, buildings must still rely, in part, on the electric grid for power. While DG deployments today use net metering to offset costs and balance local supply and demand, scaling net metering for intermittent renewables to a large fraction of buildings is challenging. In this paper, we explore an alternative approach that combines market-based electricity pricing models with on-site renewables and modest energy storage (in the form of batteries) to incentivize DG. We propose a system architecture and optimization algorithm, called GreenCharge, to efficiently manage the renewable energy and storage to reduce a building's electric bill. To determine when to charge and discharge the battery each day, the algorithm leverages prediction models for forecasting both future energy demand and future energy harvesting. We evaluate GreenCharge in simulation using a collection of real-world data sets, and compare with an oracle that has perfect knowledge of future energy demand/harvesting and a system that only leverages a battery to lower costs (without any renewables). We show that GreenCharge's savings for a typical home today are near 20%, which are greater than the savings from using only net metering. [ABSTRACT FROM PUBLISHER]

With the emerging installations of multitype renewable energy sources and energy storage elements, the dc electronic distribution systems in residential houses/buildings (dc nanogrid) are becoming an alternative future system solution, achieving a zero net-energy consumption and optimized power management. One of the critical components in such a dc system is the grid-interface bidirectional ac–dc power converter, namely the energy control center. Besides, the basic power conversion function, the system interface solution in grid-interface converter is important to successfully interconnect the ac and dc systems as well as fulfill the power quality and EMI regulation codes on both dc and ac sides. This paper presents a complete discussion of several aspects of system interface design for the grid-interface converter under both single-phase and three-phase system conditions. A passive plus active filter solution is proposed to accomplish the common-mode-related noises minimization as well as a dramatic reduction of the converter system volume. [ABSTRACT FROM AUTHOR]

With the emerging installations of multitype renewable energy sources and energy storage elements, the dc electronic distribution systems in residential buildings (dc nanogrid) are becoming an alternative future system solution, achieving a zero net-energy consumption and optimized power management. The concept of the energy control center (ECC), which interconnects the dc system to the traditional ac utility grid, is introduced, and the operation function of ECC converter suitable for dc nanogrid application is defined. This paper investigates a two-stage topology using a full bridge in series with a bidirectional synchronous rectifier dc–dc converter as a single-phase ECC for dc nanogrid, with a significant reduction of the dc-link capacitor value. The operation analysis and the design of passive components are provided. A bidirectional control system and the design process are also presented in terms of the system requirement and the small dc-link capacitor. [ABSTRACT FROM AUTHOR]

Renewable Energy Sources have been growing rapidly over the last few years. The spreading of renewables has become stronger due to the increased air pollution, which is largely believed to be irreversible for the environment. On the other hand, the penetration of renewable energy technologies causes major problems to the stability of the grid. Along with the fluctuations of the renewable energy technologies production, storage is important for power and voltage smoothing. Energy storage is also important for energy management, frequency regulation, peak shaving, load leveling, seasonal storage and standby generation during a fault. Thus, storage technologies have gained an increased attention and have become more than a necessity nowadays. This paper presents an up to date comprehensive overview of energy storage technologies. It incorporates characteristics and functionalities of each storage technology, as well as their advantages and disadvantages compared with other storage technologies. Comparison tables with several characteristics of each storage method are included, while different applications of energy storage technologies are described as well. Finally, several hybrid energy storage applications are analyzed and different combinations of energy storage technologies are reviewed. [ABSTRACT FROM AUTHOR]

This paper seeks to quantify the benefits of a flexible energy system in the context of enabling higher levels of variable renewable energy on the grid. We explore a nuclear hybrid energy system (NHES) consisting of a 300 MW small modular reactor, wind generation, battery storage, and a reverse osmosis desalination plant. A dispatch rule is constructed within the Risk Analysis Virtual Environment (RAVEN) to model the system. Stochastic optimization and parametric analysis are utilized to explore how increased volatility in the net demand resulting from higher levels of wind penetration affect the optimal solution, and the stability of the system’s levelized cost of electricity (LCOE). In this study, net demand is the demand minus wind generation. This work contributes multi-objective analysis implemented through a supply-demand mismatch penalty to illustrate the financial stability and operational reliability benefits of the flexible energy system. In this context, we find that the additional up front cost of flexible loads and energy storage result in greater stability in LCOE as volatility in the demand increases. Additionally, the flexibility results in increased reliability in terms of meeting the demand. Although the analysis is conducted on a NHES, we emphasize the flexibility of the method applied here, in that the RAVEN platform and the multi-objective strategy are widely applicable to the analysis of energy systems faced with uncertainties in supply and demand. [ABSTRACT FROM AUTHOR]

• Proposing a new robust co-planning of AC/DC hybrid transmission network and energy storage. • Embedding BFM within the proposed co-planning model. • Using data-adaptive robust optimization to cope with uncertainties. • Validating the effectiveness of the proposed method in practical power system. This paper proposes a robust co-planning model of hybrid AC/DC transmission network and energy storage with the penetration of renewable energy to promote the accommodation of renewable energy and to avoid investment redundancy. The energy storage configured in the power grid can improve the power flow distribution and alleviate transmission congestion, postponing the investment of new devices. A deterministic co-planning model is firstly developed considering voltage fluctuation, reactive power flow and the flexibility of voltage source converter based high voltage direct current (VSC-HVDC). To address the solving complexity caused by the non-convexity of the model, second-order cone programming (SOCP) is applied to transform the proposed model into a convex problem. To cope with the uncertainty of renewable energy, the robust co-planning formulation is established, where the data-adaptive uncertainty set with the extreme scenario method is introduced to describe renewable generation uncertainty. The column-and-constraint generation (C&CG) algorithm is adopted to decompose the robust co-planning problem into a master problem and several slave problems, which reduces the calculation scale and accelerates the solving process. Two case studies on a modified Garver's 6-bus system and a practical Jiangxi province power system in China are carried out to verify the effectiveness and superiority of the proposed robust co-planning model. [ABSTRACT FROM AUTHOR]

The joint optimization of power systems, mobile energy storage systems (MESSs), and renewable energy involves complex constraints and numerous decision variables, and it is difficult to achieve optimization quickly through the use of commercial solvers, such as Gurobi and Cplex. To address this challenge, we present an effective joint optimization approach for MESSs and power grids that consider various renewable energy sources, including wind power (WP), photovoltaic (PV) power, and hydropower. The integration of MESSs could alleviate congestion, minimize renewable energy waste, fulfill unexpected energy demands, and lower the operational costs for power networks. To model the entire system, a mixed-integer programming (MIP) model was proposed that considered both the MESSs and the power grid, with the goal of minimizing costs. Furthermore, this research proposed a highly efficient deep reinforcement learning (DRL)-based method to optimize route selection and charging/discharging operations. The efficacy of the proposed method was demonstrated through many numerical simulations. [ABSTRACT FROM AUTHOR]

The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency. [ABSTRACT FROM AUTHOR]

The rapid development of Internet-of-Things in smart grid has enabled millions of grid-connected distributed controllable resources (DCR; e.g., electric vehicles, controllable loads) to provide service to the grid, such as frequency regulation and demand response. The integration of these DCRs may become a large virtual power plant network with various characteristics. This poses great challenges from both control and management perspectives, e.g., computation/communication burden, optimization complexity, scalability limitation, prosumer privacy, etc. In this article, we propose an effective autonomous incentive-based DCR control and management framework to integrate a large amount of DCRs to provide grid services, which simultaneously provides accurate active power adjustment to the grid, optimizes DCR allocations, and maximizes the profits for all prosumers and system operators. A model-free deep deterministic policy gradient-based method is designed to find the optimal incentives in a continuous action space to encourage prosumers to adjust their power consumptions. The method is implemented in a consortium open-source blockchain platform, Hyperledger Fabric, which facilitates controls and transaction management. To demonstrate the effectiveness of the framework, extensive experimental studies are conducted using real-world data. [ABSTRACT FROM AUTHOR]

As the world strives toward meeting the Paris agreement target of zero carbon emission by 2050, more renewable energy generators are now being integrated into the grid, this in turn is responsible for frequency instability challenges experienced in the new grid. The challenges associated with the modern power grid are identified in this research. In addition, a review on virtual inertial control strategies, inertia estimation techniques in power system, modeling characteristics of energy storage systems used in providing inertia support to the grid, and modeling techniques in power system operational and expansion planning is given. Findings of this study reveal that adequate system inertia in the modern grid is essential to mitigate frequency instability, thus, considering the inertia requirement of the grid in operational and expansion planning model will be key in ensuring the grid's stability. Finally, a direction for future research has been identified from the study, while an inertial constant of between 4 and 10 s is recommended to ensure frequency stability in modern power grid. [ABSTRACT FROM AUTHOR]

Integration of renewable energy resources in microgrids has been increasing in recent decades. Due to the randomness in renewable resources such as solar and wind, the power generated can deviate from forecasted values. This variation may cause increased operating costs for committing costly reserve units or penalty costs for shedding load. In addition, it is often desired to charge/discharge and coordinate the energy storage units in an efficient and economical way. To address these problems, a novel battery operation cost model is proposed which considers a battery as an equivalent fuel-run generator to enable it to be incorporated into a unit commitment problem. A probabilistic constrained approach is used to incorporate the uncertainties of the renewable sources and load demands into the unit commitment (UC) and economic dispatch problems. [ABSTRACT FROM AUTHOR]

Insular electricity grids are considered to have a more fragile structure than the mainland ones due to several factors such as the lower inertia because of lower number of generation facilities connected to the system, absence or insufficient interconnection with the main grid, etc. The recent trend of integrating large portions of environmentally sustainable power generation units that have a significantly volatile nature in the generation mix (such as wind and solar energy conversion systems) within this fragile structure, poses profound challenges that need deeper and specific analysis. This study aims to provide an overview of insular power system structures and operational requirements, especially under increasing penetration of renewable energy sources. Firstly, a general evaluation of insular power systems is presented. Then, potential challenges are thoroughly discussed together with opportunities to tackle them. Future technological developments, as well as innovative applications are also given special attention. Hence, this paper contributes to the scarce literature regarding insular power systems by providing a critical overview of issues regarding their operation and possible solutions. [ABSTRACT FROM AUTHOR]

This paper proposes an alterable structure power router (PR) topology which shares the ability of general Alternating Current (AC) and Direct Current (DC) port. This alterable structure PR aims to better implement the interconnections among micro-grids, renewable energy, and traditional grids. The PR's converter structure is alterable according to the system power. Based on the operation analysis of the PR, the mathematic model of the power router is established and the relationship between switch states and port voltage is analyzed. According to the PR mathematical model, the control method is designed to realize current control in both AC and DC mode. With the proposed power router topology, the PR's port can be used in both AC and DC situations, which saves the cost of traditional PRs and increases economic efficiency. The simulation and experimental results prove the good steady-state and dynamic performance of the proposed power router topology. [ABSTRACT FROM AUTHOR]

Energy crisis and environmental pollution have become global problems, and the increasing use of energy has caused climate change. Electric vehicle (EV) is regarded as the future of the automotive industry, because of the lesser impact on the environment than traditional vehicles. In recent years, electric vehicles have developed rapidly. However, the development of charging points and service cannot adapt to the development trend of EV. In urban areas, the distribution characteristics of street lighting and charging points are similar. Therefore, the street lighting pole with EV charging is proposed. However, due to the capacity limit of public grid, the single hybrid pole is only suitable for slow charging. This paper proposes hybrid poles group based on renewable energy, street lighting, and EV charging, which can realize fast charging and slow charging based on DC micro-grid with help of energy storage device. For studying the suitable number in a group of smart hybrid pole, the efficiency model of smart hybrid poles group is proposed. The efficiency model indicates that the group approach has better performance than the single pole, which provides a theoretical basis for practical construction. [ABSTRACT FROM AUTHOR]

The growing share of renewable energies needs more flexible services to balance their intermittency and variance. The existing coal fired units and electrical energy storage (EES) systems may play an important role in delivering flexible services. The value of their flexibility services, along with the value of renewable energies, has to be analyzed from the perspective of the power system, in which the capacity costs and operation costs of renewable energy power units, EES systems, and thermal power generation units have to be taken into consideration. An optimal model is built to analyze the renewable energy integration and the flexibility services delivered by the EES systems and thermal power units in a power system. Taking the existing thermal power units and EES systems in North China Power Grid as an instance, the overall cost of the grid is examined for the penetration of renewable energies and flexible service provision. The results show that the growing shares of renewable energies are affected by their capacity credits and flexibility sources in the grid, and that the potential of thermal power units to provide flexible services will be reduced due to the replacement of renewable energies for thermal power generation. The results also indicate that the thermal units may be dispatched to have priority to delivering flexible services for the renewable energy integration, and that the curtailment of renewable energies may be regarded as one type of flexible service. According to these results, policy and strategy recommendations are put forward to weigh the role of existing coal-fired units and EES systems in providing flexible services, and to improve their compensation mechanism and their coordination. [ABSTRACT FROM AUTHOR]

[Display omitted] • Energy management strategy for a renewable-based electro-thermal microgrid. • Minimize power peaks and fluctuations in the grid using power forecasting. • Using two systems of energy storage (heat and battery) and demand side management. • Analysis by means of simulation has been carried out using one-year measured data. • Experimental validation has been done in a real size microgrid. This paper proposes an energy management strategy for a residential microgrid comprising photovoltaic (PV) panels, a small wind turbine and solar thermal collectors. The microgrid can control the power exchanged with the grid thanks to a battery and a controllable electric water heater, which provide two degrees of freedom to the control strategy. As input data, the proposed control strategy uses the battery state of charge (SOC), the temperature of the hot water tank, the power of each microgrid element as well as the demand and renewable generation forecasts. By using forecasted data and by controlling the electric water heater, the strategy is able to achieve a better grid power profile while using a smaller battery than previous works, hence reducing the overall cost of the system. The strategy is tested by means of simulation with real data for one year and it is also experimentally validated in the microgrid built at the Renewable Energy Laboratory at the UPNA. [ABSTRACT FROM AUTHOR]

In developing countries such as in Africa, rural areas are not always connected to the national or regional electric grid. As there is a huge potential for solar energy production, photovoltaics are established to supply electricity for operating critical infrastructures with battery systems and diesel generators installed for redundancy. These systems have the potential for further utilization. As a first step, overproduction of solar energy is offered to households due to simple control rules observing battery levels. This paper proposes an optimization method for energy allocation by process graphs or P-graphs. The method provides preliminary estimations on optimal periodical energy balances between energy producers, storage, and consumers of different priorities. These preliminary estimations serve as reconciliation parameters for advanced real-time control of energy distribution. Each step of transforming the practical problem of multiperiod energy distribution to the language of process network synthesis and then optionally to mathematical programming is detailed. To represent the problem adequately, the original formulation of process network synthesis is extended to take into account potential targets and intermediate entities that cannot be accumulated. The work aims to provide better utilization of renewable energy sources and storage. The microgrid profit and return of investment can also be improved by the proposed methodology. Image 1 [ABSTRACT FROM AUTHOR]

Because of the increase of the data traffic demand, wireless access networks, through which users access telecommunication services, have expanded, in terms of size and of capability and, consequently, in terms of power consumption. Therefore, costs to buy the necessary power for the supply of base stations of those networks is becoming very high, impacting the communication cost. In this study, strategies to reduce the amount of money spent for the purchase of the energy consumed by the base stations are proposed for a network powered by solar panels, energy batteries and the power grid. First, the variability of the energy prices is exploited. It provides a cost reduction of up to 30%, when energy is bought in advance. If a part of the base stations is deactivated when the energy price is higher than a given threshold, a compromise between the energy cost and the user coverage drop is needed. In the simulated scenario, the necessary energy cost can be reduced by more than 40%, preserving the user coverage by greater than 94%. Second, the network is introduced to the energy market: it buys and sells energy from/to the traditional power grid. Finally, costs are reduced by the reduction of power consumption of the network, achieved by using microcell base stations. In the considered scenario, up to a 31% cost reduction is obtained, without the deterioration of the quality of service, but a huge Capex expenditure is required. [ABSTRACT FROM AUTHOR]

The deep penetration of wind and solar power is a critical component of the future power grid. However, the intermittency and stochasticity of these renewable resources bring significant challenges to the reliable and economic operation of power systems. Motivated by these challenges, we present a multistage adaptive robust optimization model for the unit commitment (UC) problem, which models the sequential nature of the dispatch process and utilizes a new type of dynamic uncertainty sets to capture the temporal and spatial correlations of wind and solar power. The model also considers the operation of energy storage devices. We propose a simplified and effective affine policy for dispatch decisions, and develop an efficient algorithmic framework using a combination of constraint generation and duality-based reformulation with various improvements. Extensive computational experiments show that the proposed method can efficiently solve multistage robust UC problems on the Polish 2736-bus system under high dimensional uncertainty of 60 wind farms and 30 solar farms. The computational results also suggest that the proposed model leads to significant benefits in both costs and reliability over robust models with traditional uncertainty sets as well as deterministic models with reserve rules. [ABSTRACT FROM AUTHOR]

The combined cooling, heating, and power (CCHP) microgrid system is good for energy gradient utility. At the same time, it can promote the renewable energy (RE) consumption and abate environmental pollution. In a CCHP microgrid system, the electrical energy storage (EES), which can storage and release electrical energy, plays an indispensable role. A robust optimization model of the CCHP microgrid participating in power market transaction is constructed to calculate the CCHP microgrid operation cost in 4 cases. The results show that the EES can significantly reduce the cost of the CCHP microgrid by 13.21%, compared with 8.36% in Group 1 without renewable energy. The EES can reduce the reserved capacity of micro gas turbine units to deal with the precariousness of RE generation and then reduce the CCHP microgrid operation cost by reducing the purchase of energy from the power grid and arbitrage. Finally, the calculation method of comprehensive value of the EES is constructed. The comprehensive value of the EES is higher in Group 2 with renewable energy compared with Group 1 without renewable energy. Through net present value (NPV) calculation and sensitivity analysis, it is found that the RE penetration level and EES cost have the greatest impact on the economic performance of EES. This shows that with the continuous rising of the RE penetration level and the gradual decrease of EES cost, great potential still waits to be tapped in the comprehensive value of EES in the future. [ABSTRACT FROM AUTHOR]