Distributed Agent-Based Coordinated Control for Microgrid Management

Power systems have been undergoing radical changes in recent years, and their planning and operation will be surely undertaken according to the Smart Grid (SG) vision in the near future. The SG initiatives aim at introducing new technologies and services in power systems, to make the electrical networks more reliable, efficient, secure and environmentally-friendly. In particular, it is expected that communication technologies, computational intelligence and distributed energy sources will be widely used for the whole power system in an integrated fashion. In particular, nowadays, unprecedented challenges like as stringent regulations, environmental concerns, growing demand for high quality, reliable electricity and rising customer expectations are forcing utilities to rethink about electricity generation and delivery from the bottom up. Moreover, the availability of low cost computing and telecommunications technologies, new generation options, and scalable, modular automation systems push utilities to be dynamic, innovative and ambitious enough to take advantage of them. Driven by the dynamics of the new energy environment, leading utilities, technology vendors and government organizations have created a vision of the next generation of energy delivery systems: the Smart Grid. Operational changes of the grid, caused by restructuring of the electric utility industry and electricity storage technology advancements, have created an opportunity for storage systems to provide unique services to the evolving grid. Especially Battery Energy Storage Systems (BESSs), thanks to the large number and variety of services they can provide, are powerful tools for the solution of some challenges that future grids will face. This consideration makes BESSs critical components of the future grids. The BESS can be applied for different services into the different levels of power system chain to satisfy technical challenges and provide financial benefits. In the context of the application of BESSs in SGs, there are two main problems that need to be addressed in a way that exploits the BESS potential, that are linked to their operation and sizing. This thesis focuses on both these aspects, proposing new strategies that allow optimizing the BESS adoption. When dealing with BESSs, sizing and operation are strictly linked. The correct sizing of a BESS, in fact, needs to take into account its operation which in turn will be effected with the aim of optimizing the whole system where it is included. In the first part of this research study, advanced optimal operating strategies were proposed for BESSs by considering both the distribution system operator perspective and the end user. Thus, the proposed operating strategies were performed with the aim of (i) leveling the active power requested by the loads connected to a distribution system (distribution system operator service), (ii) reducing the electricity costs sustained by an end-use costumer that provides demand response (DR) (end user service) and (iii) scheduling a microgrid (µG) with DR resources such as Plug-in Electric Vehicles (PEVs) and Data Centers (DCs) (both the two section service). The proposed strategies also satisfied technical constraints of BESSs and other components of the µG. The second part of the thesis presented the optimal sizing of BESSs aimed at maximizing the benefits related to their use. In the thesis, the sizing, which is performed by considering the end user point of view with reference to both the industrial and residential customers, is effected by adopting both deterministic and probabilistic approaches. With reference to the deterministic approach, a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications was proposed. In case of probabilistic approach, the case of a BESS installed in an industrial facility was considered and the sizing was performed based on the decision theory. Technical improvements and economic benefits of optimal operation and optimal sizing of BESSs in SG are demonstrated by the obtained results which are reported in the numerical applications. More specifically, it was clearly determined that BESSs can offer technical supports into the distribution operator section of the grid in terms of load management and security challenges. Moreover optimal integration of BESSs into the grid was also appealing for end users thanks to valuable amounts of electricity bill cost reduction. Regarding the original contribution of the thesis, the following considerations can be done. With reference to the load leveling service, an innovative two-step procedure (day-ahead scheduling and very short time predictive control) was proposed which optimally controls a BESS connected to a distribution substation in order to perform load leveling. In case of DR, a proper control of the BESS was proposed in order to perform DR under different price schemes, such as Real Time Pricing (RTP) and Time of Use (TOU) without modifying the daily work cycle of the industrial loads. The control procedure allows achieving contemporaneously two important goals that are the reduction of the bill costs and the prolonging the battery's lifetime so further reducing the costs sustained by the customer. With reference to the scheduling of microgrids, the original contribution of the thesis is focused on the proposal of optimization strategies aimed at managing and coordinating, simultaneously, batteries on board of vehicles or equipping data centers' Uninterruptable Power Supply (UPS) and Distributed Generation (DG) units. Also comparisons among different single-objective based strategies are made in order to highlight the most convenient. With reference to the sizing based on deterministic approach, unlike the other relating literature, the innovative contribution is that the closed form procedure takes into account both the technical constraints of the battery and contractual agreements between the customer and the utility. Moreover, in the economical analysis performed for the sizing, which is applied with reference to both residential and small industrial customers and is based on actual TOU tariffs, a wide sensitivity analysis to consider different perspectives in terms of life span and future costs was performed. Some aspects that affect the profitability of the battery, such as technological limitations (e.g. the battery and converter efficiency), economic barriers (e.g. capital cost and the rate of change of the cost) and variation of the load profile along the years were deeply analyzed. In case of sizing based on probabilistic approach, the original contributions of the thesis are mainly referred to the proposal of a new method that uses a decision theory-based process to obtain the best sizing alternative considering the various uncertainties affecting the sizing procedure. The thesis is organized in three chapters which are dealing with integration of BESSs in SGs. The first chapter reports basic concepts and characteristics of BESSs, fundamental components and features of SGs and different services that BESSs can provide. The optimal operation strategies of BESS are considered in second chapter which includes their problem formulation, solving procedures and results. The third chapter deals with the optimal sizing problem of BESSs for which the problem formulation, solving procedures and results are reported. Finally, the conclusions are presented in the last part of thesis.

The integration of battery energy storage systems (BESS) with renewable energy is a potential solution to address the disadvantages of renewable energy systems, which is irregular and intermittent power. In particular, residential BESS is advancing in numerous countries. The residential BESS connected to the photovoltaic system (PV) can store the PV power in the battery through charging, and supply the PV power, which was stored in the battery, to the load through discharging when there is no PV power. Therefore, the utilization of residential BESS with PV reduces the daily electric power consumption and the electricity bills that households have to charge. However, it is understood that there is no case of installing and using residential BESS in Korea yet. Most residential houses in Korea are apartment houses, and thus residential BESS can be used with balcony PV. This paper presents operation modes of residential BESS with balcony PV for apartment houses. The BESS capacity was estimated by considering the balcony PV capacity, which can be installed in households, and power consumption. The applicability of the residential BESS was analyzed through performance and economics evaluation under current and various conditions. The operation modes of BESS were divided into four types according to PV power supply priority and battery charging source, and a test took place in a demonstration house. The risk of fully discharging the battery has been discovered when PV power is first charged to the battery or when only PV power is charged with the battery. As a result, preferential charging of the battery with PV power and then with PV and grid power was found to be the most optimal operation mode. In addition, additional functions were proposed for residential BESS in apartment households. The results will contribute to effective application of residential BESS with balcony PV in the near future.

For hybrid energy systems utilizing renewable energy sources such as the power grid of Phu Quy island - Binh Thuan province, the integration of battery energy storage system (BESS) could be seen as a practical solution with remarkable advantages including economic and technical preeminence. BESS contributes to increasing renewable energy penetration, enhancing system stability and reducing the dependence on fossil fuel generation. However, the integration of BESS into an existing hybrid power system also necessitates to conduct a quantitative analysis of the performance of different solutions. This study investigates operational data of Phu Quy power grid for one year, evaluates solar energy potential and proposes a proper BESS integration solution based on a careful quantitative analysis. The simulation results show that selection of larger BESS capacity increases penetration rate of renewable energy. Nevertheless, of all proposed BESS integrated scenarios, renewable energy penetration rate as well as diesel consumption do not show a major difference. Therefore, choosing BESS also needs to consider the load capacity and time required to start and interconnect standby diesel generators.

Abstract: The determination of both the connection topology and capacity sizing of the battery energy storage system (BESS) in a microgrid is crucial when considering energy bills and reliability indicators, as the usage type of the BESS affects investment and energy costs. In this study, the performances of individual and shared BESSs are compared across different price tariffs in a multi-microgrid structure designed using historical real data and existing prosumer solar homes. To illustrate the effects of the integrated BESS and grid outages on the cost of energy and net present cost (NPC), a BESS is first integrated into the selected solar home as a sample. The calculations are then made assuming an outage in the grid connected to the selected home with the integrated BESS. In the proposed system topology, which utilizes five selected solar homes with a shared BESS, the NPCs were found to be 51%, 28%, and 37% lower compared to individual systems for real-time pricing (RTP), flat price tariff (FPT), and time-of-use pricing (ToU), respectively. Furthermore, in modeling these grid interruptions, which are a real-life condition, system reliability indices such as system average interruption duration index and system average interruption frequency index were considered in the system sizing and cost optimization. When these indices were taken into account, similar reductions were observed compared to the individual system: 9% in RTP, 26% in FPT, and 61% in ToU, respectively.Cite this article as: S. Polat and E. Bıyık, “Evaluation of centralized and distributed energy storage systems in residential microgrid topologies,” Turk J Electr Power Energy Syst., 2025; 5(1), 30-40.

A modified NSGA approach for optimal sizing and allocation of distributed resources and battery energy storage system in distribution network

In microgrids, battery energy storage systems can be used in combination with renewable energy sources as a way to mitigate the adverse effects of the mismatch between renewable energy output and load demand on microgrid operation. To address the configuration of renewable energy generation units and battery energy storage systems in zero-carbon microgrids, the paper proposes a multi-objective optimal configuration method from the perspective of microgrid operation. Minimizing the life cycle cost of the system and minimizing the renewable curtailment are taken as objective functions. Based on actual wind and solar power output and load data, the multi-objective problem is solved by the normalized normal constraint method to obtain the configuration results. The validation study of typical days in three seasons is carried out respectively. Through the analysis of the validation results, it can be found that the proposed method can promote the cooperation between generation equipment and battery energy storage system, which makes the microgrid more economical. In addition, the stability of the model for load changes is proved by the sensitivity analysis.

This paper proposes a joint optimization model of grid-tied residential microgrid (MG) planning and operation with the support of demand side management (DSM). In this model, the residential MG is included with various distributed energy resources, such as photovoltaic units, wind turbines, microturbines, diesel engine generators (DEs), and battery energy storage systems (BESSs). The proposed model is formulated as a bi-objective optimization problem in view of economic and environmental contemplation. Therefore, the minimization of MG total annual cost and total annual emission are considered as the primary objectives. This paper mainly analyzes the benefits of DSM assistance in the process of residential MG joint planning and operation optimization. The proposed bi-objective optimization problem is converted into a single-objective optimization problem and the single-objective problem is solved using a mixed integer linear programming method. To investigate the impacts of DSM on the MG planning and operation problem, the proposed model is applied to a residential MG consisting of 1000 smart homes with different DSM participation levels. The simulation results show that the proposed model is an efficient tool for residential MG planning and operation optimization from the perspective of economic and environmental considerations.

The foremost challenge in a microgrid with Distributed Energy Resources (DER) is of managing the intermittent nature of renewable energy sources. Therefore, the extent of integration of the Battery Energy Storage System (BESS) has increased recently in a microgrid due to its versatility, high energy density, and efficiency. Generally, BESS is a grid-tied system and has fast power adjustment capability. Controversially, during the stand-alone mode, it cannot operate in the absence of a local Voltage Source (VS) which acts as a voltage and frequency reference in the network. To ensure the reliable operation of a microgrid during utility grid outage or non-availability of intermittent Renewable Energy Sources (RES), it is significant to operate the BESS with the local VS to dispatch the stored energy. This paper discusses the analytical methodology that can be adopted for identifying the most suitable rating of the VS which can act as a voltage and frequency reference for the BESS using Matlab/Simulink. Further, a simulation was carried out against various load characteristics and it is observed that an Uninterruptible Power Supply (UPS) with a kVA capacity of 35-45% of that of the BESS with an overload capacity of 150-200% can be chosen as a feasible choice to act as the VS.

Microgrids (MGs) are a critical component in modern power systems, comprising interconnected loads and distributed energy resources (DERs) that can operate autonomously or in conjunction with the main grid. This review examines the role of MGs in advancing smart grid technologies, emphasizing the optimal integration of renewable energy sources (RES) and energy storage systems (ESS) to enhance their resilience and efficiency. It provides a detailed analysis of various MG architectures, including AC, DC, and hybrid topologies, alongside their operational modes. The paper highlights the pivotal role of control systems in optimizing energy management within MGs. Additionally, the challenges associated with MG integration, such as harmonic distortion, system stability, and regulatory constraints, are discussed. The review further explores the application of intelligent control strategies, including Fuzzy Logic Controllers (FLCs) and Genetic Algorithms (GAs), to optimize battery energy storage systems (BESS) and improve overall MG performance. The findings emphasize the need for innovative optimization techniques and intelligent control systems to overcome current limitations, thus enhancing the potential of MGs in future energy systems

Climate change and the pressing need for sustainable energy solutions have propelled smart grids to the forefront of technological innovation. The emergence of prosumers in smart grids, coupled with the integration of battery energy storage systems (BESS), has significantly enhanced the potential for harnessing renewable energy and optimizing energy consumption patterns. This thesis presents a novel evolutionary game-theoretic (EGT) framework for energy storage scheduling in smart grids, addressing the complex dynamics of local energy markets (LEMs) and the strategic interactions between prosumers equipped with photovoltaic (PV) systems and BESS.At the core of this research is a holistic energy management system (EMS) for prosumers with PV and BESS. This comprehensive framework serves as the foundation for optimizing energy consumption, storage, and trading within a smart grid community (SGC). It considers various factors such as stochastic energy generation, consumption patterns, and fluctuating market conditions to maximize the benefits for individual prosumers and the community as a whole. We propose a novel decentralized EGT approach for exploring a vast action space for battery scheduling over a 24-hour horizon. This innovative algorithm enhances energy management while preserving privacy and scalability. By leveraging EGT, the approach allows for adaptive decision-making in response to changing market conditions and prosumer behaviors, significantly improving upon market stability over traditional scheduling methods.A comprehensive comparative analysis evaluates our proposed EGT algorithm against established methods such as centralized optimization, game theory, and auction-based approaches. This comparison focuses on key performance metrics, including peak-to-average ratio, price volatility, economic efficiency, and computational performance. Results demonstrate the superiority of our EGT approach in terms of both effectiveness and efficiency.The research implements a modified fitness function within the EGT framework that balances technical and economic objectives through the analytic hierarchy process (AHP) approach. This novel fitness evaluation considers both the prosumer's electricity bill and battery degradation, measured by the depth of discharge (DoD). By incorporating these dual objectives, the framework enables prosumers to make informed decisions that balance immediate economic benefits with long-term battery health and sustainability.Building on this enhanced framework, we present a detailed techno-economic analysis that evaluates the financial viability of BESS investments within the SGC. Through considering metrics such as the net present value (NPV) and payback periods, we provide valuable insights into the economic implications of different battery utilization strategies. Our analysis reveals how varying the weights between economic and technical objectives impacts both immediate economic returns and long-term system sustainability. By incorporating these economic metrics alongside technical considerations in our EGT framework, we achieve a balanced approach that addresses both financial viability and system longevity.Extensive simulations demonstrate the effectiveness of our EGT algorithm in stabilizing market conditions under various Feed-in Tariff (FiT) scenarios and prosumer penetration rates. The results show how increased prosumer participation leads to more predictable investment outcomes and stable market conditions. This thesis provides an in-depth analysis of a demand-side management scheme that can be employed by prosumers worldwide in the near future, contributing to the global effort in combating climate change through advanced energy management solutions

Emerging distributed energy resources (DERs)—such as solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicles (EVs)—are expected to increase substantially in India in the coming years following policy-driven targets of the Government of India to modernize its electricity system, reduce greenhouse gas emissions (GHGs), and improve air quality. These emerging technologies can pose challenges to distribution utilities, forcing overhauls in planning and operational practices. They can also create challenges in power system infrastructure planning and cause more frequent system operational violations (e.g., network voltage bounds and loading thresholds) if not properly integrated. The impacts on the localized power distribution grid from these emerging technologies manifest in increased infrastructure investments and erratic shifts in demand patterns. These impacts are not yet well understood, and analytic solutions are not readily available. To address these challenges, the National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL), developed an advanced power distribution system impact analysis framework of BRPL’s distribution system. This framework helps analyze the readiness of the power distribution network to accommodate emerging technologies and the potential opportunities they might introduce. The framework has been predominantly set up to evaluate distributed PV, BESS, and EVs. In this collaboration between NREL and BRPL, we developed and evaluated the framework on two distribution feeders in the BRPL territory for various scenarios of BESS and EVs. BESS are evaluated for their effectiveness on the grid to mitigate present and future feeder overloading scenarios, and they are subsequently analyzed for their costs compared to the costs of traditional upgradation measures. Scenarios include assessing the effects of EV density on grid infrastructure upgrades and interlinking EV management with BESS integration.

This project explores the integration of battery energy storage systems (BESS) in residential settings to optimize energy management with a novel focus on standalone BESS configurations independent of solar photovoltaic (PV) systems. The objective is to analyze electricity price patterns, evaluate different BESS configurations, and develop strategies for efficient charging and discharging. This enables homeowners to store excess electricity during low-demand periods and discharge it during peak demand, reducing grid reliance and saving on electricity costs. The analysis reveals that a standalone BESS can reduce electricity costs by leveraging low-demand periods with electricity prices averaging 0.4 DKK/kWh, compared to peak prices exceeding 0.8 DKK/kWh. For June 2023, optimal charging (6:00–14:00, 18:00–22:00) and discharging (14:00–18:00, 23:00–6:00) periods were identified, leading to potential cost savings of up to 30 %. The findings highlight the potential of BESS to transform energy management and suggestions such as a net metering program are proposed to mitigate these challenges.

As the demand for electricity increases day by day, the integration of battery energy storage systems (BESS) has become highly influential when considering power systems. Battery energy storage systems have the advantage of improving the economy of power with environmental benefits. For the successful integration of battery energy storage systems, the optimal placement and economic dispatching of energy is required to avoid problems. A BESS will provide power whenever the DGs are unable to provide power to the system. In the case of solar power, the sun cannot provide light to solar panels all day and wind turbines encounter variations in wind supply. This research proposes optimal placement within a BESS and a reduction in the cost of energy usage from conventional sources by considering BESSs with active power capability via an IEEE-33 bus system using an algorithm called mixed-integer second-order cone programming (MI-SOCP), modeled in MATLAB using MOSEK solver to reduce the cost of energy as an objective function. The MI aspect of the algorithm is used to find out the optimal placement of the BESS and the SOCP part is used to reformulate the economic dispatch problem in an AC-distributed BESS.

Harnessing demand-side management benefit towards achieving a 100% renewable energy microgrid

Battery energy storage system (BESS) is the key element to integrate a distributed generation (DG) unit into a microgrid. This paper presents a microgrid consisting of singlephase photovoltaic (PV) arrays which function as the primary DG units and a BESS to supplement the intermittent PV power generation and demand variations in the microgrid. An energy management system is proposed to coordinate the operations of the microgrid during grid-connected and islanded modes of operation. The BESS is incorporated into the microgrid to deal with power imbalance and peak load demand during grid-connected operation and to compensate for any power shortage during islanded operation. The controller design for the voltage source inverter employs a model predictive control (MPC) algorithm which enables faster dynamic response. MATLAB/Simulink is used to simulate the proposed microgrid under different test scenarios. The simulation results show that the operations of the BESS in the microgrid can be coordinated effectively using the proposed control system to ensure stable operation of the overall microgrid.