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Due to a rising share of renewable energy sources on the production side and electrification of transport and heating on the consumption side, the efficient management of flexibility in distribution networks is crucial for ensuring optimal operation and utilization of resources. Nowadays, the sensitivity-based approach is mainly used in medium-voltage (MV) networks for regulating voltage profiles with reactive power of distributed energy resources (DER). The main disadvantage of the simplified sensitivity-based method is its inaccuracy in case of a high deviation of the network voltage from the nominal values. Furthermore, it was also noted that despite the fact that the method is well described in the literature, there is a lack of systematic approach to its implementation in real-life applications. Thus, the main objective of this paper is to address this disadvantage and to propose an algorithm designed to calculate required consumer flexibility in near real-time to ensure distribution grid operation within operational criteria. In the first part of the paper, network state, including line loading and node voltages, is assessed to determine distribution network node capacity. By analyzing the sensitivity of network busbars to changes in consumption and production, our algorithm effectively identifies the most efficient nodes and facilitates strategic decision-making for resource allocation. We demonstrate the effectiveness of our approach through simulations of real-world distribution network data, highlighting its ability to enhance network flexibility and improve resource utilization. Leveraging sensitivity coefficients, the algorithm enables flexible consumption and production management across various scenarios, supporting the transition to a more dynamic and efficient power system. [ABSTRACT FROM AUTHOR]

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

As offline control photovoltaic (PV) plants are not equipped with online communication and remote control systems, they cannot adjust their power in real-time. Therefore, in a distribution network saturated with offline control PVs, the distribution system operator (DSO) should schedule the distributed energy resources (DERs) considering the uncertainty of renewable energy to prevent curtailment due to overvoltage. This paper presents a day-ahead network operation strategy using a mobile energy storage system (MESS) and offline control PVs to minimize power curtailment. The MESS model efficiently considers the transportation time and power loss of the MESS, and models various operating modes, such as the charging, discharging, idle, and moving modes. The optimization problem is formulated based on mixed-integer linear programming (MILP) considering the spatial and temporal operation constraints of MESSs and is performed using chanced constrained optimal power flow (CC-OPF). The upper limits for offline control PVs are set based on the probabilistic approach, thus mitigating overvoltage due to forecasting errors. The proposed operation strategy was tested in the IEEE 33-node distribution system coupled with a 15-node transportation system. The test results show the effectiveness of the proposed method for minimizing curtailment in offline control PVs. [ABSTRACT FROM AUTHOR]

Microgrid technology offers a new practical approach to harnessing the benefits of distributed energy resources in grid-connected and island environments. There are several significant advantages associated with this technology, including cost-effectiveness, reliability, safety, and improved energy efficiency. However, the adoption of renewable energy generation and electric vehicles in modern microgrids has led to issues related to stability, energy management, and protection. This paper aims to discuss and analyze the latest techniques developed to address these issues, with an emphasis on microgrid stability and energy management schemes based on both traditional and distinct approaches. A comprehensive analysis of various schemes, potential issues, and challenges is conducted, along with an identification of research gaps and suggestions for future microgrid development. This paper provides an overview of the current state of the field and proposes potential areas of future research. [ABSTRACT FROM AUTHOR]

Users ought to decide how to operate and manage power systems in order to achieve various goals. As a result, many strategies have been developed to aid in this regard. Optimal power flow management is one such strategy that assists users in properly operating and managing the supply and demand of power in an optimal way under specified constraints. However, in-depth research on optimal power flow management is yet to be explored when it comes to the supply and demand of power for the bulk of standalone renewable energy systems such as solar photovoltaics, especially when it comes to specific applications such as powering military soldier-level portable electronic devices. This paper presents an optimal power flow management modelling and optimisation approach for solar-powered soldier-level portable electronic devices. The OPTI toolbox in MATLAB is used to solve the formulated nonlinear optimal power flow management problem using SCIP as the solver. A globally optimal solution was arrived at in a case study in which the objective function was to minimise the difference between the power supplied to the portable electronic device electronics and the respective portable electronic device power demands. This ensured that the demand for solar-powered soldier-level portable electronic devices is met at all times in spite of the prohibitive case scenarios' circumstances under the given constraints. This resolute approach underscores the importance placed on satisfying the demand needs of the specific devices while navigating and addressing the limitations posed by the existing conditions or constraints. Soldiers and the solar photovoltaic user fraternity at large will benefit from this work as they will be guided on how to optimally manage their power systems' supply and demand scenarios. The model developed herein is applicable to any demand profile and any number of portable electronic device and is adaptable to any geographical location receiving any amount of solar radiation. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive overview of the microgrid (MG) concept, including its definitions, challenges, advantages, components, structures, communication systems, and control methods, focusing on low-bandwidth (LB), wireless (WL), and wired control approaches. Generally, an MG is a small-scale power grid comprising local/common loads, energy storage devices, and distributed energy resources (DERs), operating in both islanded and grid-tied modes. MGs are instrumental to current and future electricity network development, such as a smart grid, as they can offer numerous benefits, such as enhanced network stability and reliability, increased efficiency, an increased integration of clean and renewable energies into the system, enhanced power quality, and so forth, to the increasingly growing and complicated power systems. By considering several objectives in both islanded and grid-tied modes, the development of efficient control systems for different kinds of MGs has been investigated in recent years. Among these control methods, LB communication (LBcom)-based control methods have attracted much attention due to their low expenses, recent developments, and high stability. This paper aims to shed some light on different aspects, a literature review, and research gaps of MGs, especially in the field of their control layers, concentrating on LBcom-based control methods. [ABSTRACT FROM AUTHOR]

Virtual synchronous generators (VSGs) are one of the most relevant solutions to integrate renewable energy in weak grids and microgrids. They indeed provide inverters characteristics of rotating machines (inertia for instance) that are useful for stabilizing the system, notably in the context of the high variability of the production. Thanks to the virtual characteristics of the VSG, the virtual parameters of the emulated synchronous machine can be optimally adapted online as a function of the electric environment of the inverter. We call that inverter's control a polymorphic VSG. The online adaptation of the critical control parameters of the VSG helps reduce the risk of deterioration of the inverter's constituents that might be induced by harsh events (frequent in weak grids) but, more importantly, improves the robustness of the system. In this paper, four implementations of a polymorphic VSG controller are compared on a simple microgrid study case to a complete VSG model. For the test, polymorphic VSGs have to minimize frequency and voltage oscillations while withstanding short circuits, which is typically a requirement for units in this context. One of the controls is based on recurrent optimization over a prediction time horizon, and two sub-optimal ones target practical implementation in industrial inverters with limited computational power. Results show a clear reduction in incidents in the microgrid thanks to the controllers. The error reduction with the complete polymorphic VSG is up to 100% for the voltage, 32% for the currents, and 79% for the duty ratio. Those values are decreased by 30 to 50% with the sub-optimal controllers but for a reduction in the computational burden of more than 97%. Recommendations are proposed for the development of an auto-adaptive polymorphic VSG from a high technology-readiness-level perspective, i.e., targeting a compromise between error reduction and computational burden. [ABSTRACT FROM AUTHOR]

Two interconnected AC microgrids are proposed based on three renewable energy sources (RESs): wind, solar, and biogas. The wind turbine drives a permanent magnet synchronous generator (PMSG). A solar photovoltaic system (SPVS) with an appropriate inverter was incorporated. The biogas genset (BG) consists of a biogas engine coupled with a synchronous generator. Two interconnected AC microgrids, M1 and M2, were considered for study in this work. The microgrid M2 is connected to a diesel engine (DE) characterized by a continuous power supply. The distribution power loss of the interconnected AC microgrids comprises in line loss. The M1 and M2 losses are modeled as an objective function (OF). The power quality enhancement of the interconnected microgrids will be achieved by minimizing this OF. This research also created a unique frequency control method called virtual inertia control (VIC), which stabilizes the microgrid frequency using an optimal controller. In this paper, the following five controllers are studied: a proportional integral controller (PI), a fractional order PI controller (FOPI), a fuzzy PI controller (FPI), a fuzzy fractional order PI controller (FFOPI), and a VIC based on FFOPI controller. The five controllers were tuned using particle swarm optimization (PSO) to minimize the (OF). The main contribution of this paper is the comprehensive study of the performance of interconnected AC microgrids under step load disturbances, step changes in wind/solar input power, and eventually grid following/forming contingencies as well as the virtual inertia control of renewable energy resources used in the structure of the microgrids. [ABSTRACT FROM AUTHOR]

Different types of distributed generation (DG) units based on renewable and non-renewable energy sources can create a local energy system in microgrids. The widespread penetration of distributed energy resources (DERs) has affected many power system issues, such as the control and operation of these networks. For the optimal operation of microgrids, optimal energy planning and management in the new space governing the distribution system requires extensive research and analysis. Getting acquainted with the latest research about the evaluation of the problems and challenges in the design of control systems plays an important role in providing a guidance map for researchers to find the recent challenges and propose new solutions. This paper tried to list the challenges of distributed generation sources for MG applications, opportunities, and solutions. These challenges are reported in hierarchical control strategies and power-sharing categories. Therefore, Model Predictive Control (MPC)-based approaches are reviewed for different recent control levels and power sharing strategies in a comprehensive and simple point of view. The performance comparison of MPC methods together and different allocated fitness functions and implementation algorithms are dedicated. Another hand, the potential of MPC methods to control inverters for increasing the reliability of the grid, which this feature could not be achieved by using conventional strategies, while has not been investigated by researchers widely, is introduced in a short review. Therefore, this paper shows an intersection guidance map for readers to facilitate future research works in these exciting and undiscovered fields. [ABSTRACT FROM AUTHOR]

The integration of renewable energy resources and uncertainties in power system models pose significant challenges to load frequency control (LFC). To tackle these challenges, controller tuning with robustness constraints provides an efficient solution. In this paper, we propose a novel approach for controller tuning in the LFC of microgrid systems with communication delay. Our approach converts the tuning task into an algorithm that solves two parametric equations subject to robustness constraints, resulting in high accuracy and computational efficiency. We use a perturbed scenario with uncertain microgrid model gains and communication delay to illustrate the tuning efficiency. Simulation examples, including comparisons with classical tuning methods, demonstrate the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a method for supplying stable electricity using renewable energy sources and energy storage systems (ESSs) in a small-scale microgrid (MG) such as an island. Traditional control methods, such as master–slave control and droop control, have focused on equalizing power sharing among a small number of generators and do not deal well with emergencies such as unplanned generator failures. This paper proposes a control method that can stably maintain the frequency of the MG in various situations by combining the advantages of master–slave control and droop control and complementing the disadvantages. Simulations were performed under various conditions to verify the proposed control method. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS. [ABSTRACT FROM AUTHOR]

Globally, renewable energy-based power generation is experiencing exponential growth due to concerns over the environmental impacts of traditional power generation methods. Microgrids (MGs) are commonly employed to integrate renewable sources due to their distributed nature, with batteries often used to compensate for power fluctuations caused by the intermittency of renewable energy sources. However, sudden fluctuations in the power supply can negatively impact battery performance, making it challenging to select an appropriate battery energy storage system (BESS) at the design stage of an MG. The cycle count of a battery in relation to battery stress is a useful measure for determining the general health of a battery and can aid in BESS selection. An accurate digital replica of an MG is required to determine the required cycle count and stress levels of a BESS. The Digital Twin (DT) concept can be used to replicate the dynamics of the MG in a virtual environment, allowing for the estimation of required cycle numbers and applied stress levels to a BESS. This paper presents a Microgrid Digital Twin (MGDT) model that can estimate the required cycle count and stress levels of a BESS without considering any unique battery type. Based on the results, designers can select an appropriate BESS for the MG, and the MGDT can also be used to roughly estimate the health of the currently operating BESS, allowing for cost-effective predictive maintenance scheduling for MGs. [ABSTRACT FROM AUTHOR]

Power generation from Renewable Energy Sources (RESs) is unpredictable due to climate or weather changes. Therefore, more control strategies are required to maintain the proper power supply in the entire microgrid. This paper presents a simulation scheme utilizing a solar system instanced by Photovoltaic (PV) panels coupled to the grid, loads, and an energy storage device. At first, modeling the PV panels cell and their operation were analyzed. The synthesis of the adaptive notch filter was designed to compensate for the input currents. The power converter's/inverter's efficiency and control facility allowed us to link the energy storage system with an electrical grid. Several simulations were accomplished consistently with nonlinear control techniques for the simple inverter, multi-variable filter, notch filter, and without a filter. Finally, the performances of the nonlinear controller with various filters were carried out to regulate the DC bus of the proposed grid. The advantage of these controllers is compensating the reactive power and harmonic currents to obtain a disturbance-free power network. The overall installations and simulations were established using the Matlab/Simulink software. [ABSTRACT FROM AUTHOR]

Microgrid technology has recently gained global attention over increasing demands for the inclusion of renewable energy resources in power grids, requiring constant research and development in aspects such as control, protection, reliability, and management. With an ever-increasing scope for maximizing renewable energy output, there is also a need to reduce the curtailment of power on both the generation and demand sides by increasing forecasting accuracies and using resources more effectively. This paper proposes a dual-stage dispatch employing a novel "split-horizon" strategy, in a bid to enhance energy management in a standalone microgrid. The split-horizon is essentially the considered time horizon split into equal operational periods of the dual-stage dispatch. The proposed strategy utilizes a custom-designed novel variant of the inertia-weight-based particle swarm optimization (PSO), termed customized PSO, to perform the optimal schedule and dispatch operation by benefitting from the simplicity of PSO and customization as per the considered objectives. A modified IEEE 34-node test system is derived into a standalone microgrid with added distributed energy resources to test the proposed strategy, while another standalone microgrid, a modified IEEE 69-node test feeder, is also considered for scalability. Furthermore, the validation of the strategy is performed appropriately with a case study while also validating the proposed optimization algorithm. It is observed that the proposed energy management strategy provides approximatelya 7% reduction in costs. [ABSTRACT FROM AUTHOR]

This paper describes an energy management strategy for a DC microgrid that utilizes a hybrid renewable energy system (HRES) composed of a photovoltaic (PV) module, a wind turbine based on a permanent magnetic synchronous generator (PMSG), and a battery energy storage system (BESS). The strategy is designed to provide a flexible and reliable system architecture that ensures continuous power supply to loads under all conditions. The control scheme is based on the generation of reference source currents and the management of power flux. To optimize the supply–demand balance and ensure optimal power sharing, the strategy employs artificial intelligence algorithms that use previous data, constantly updated forecasts (such as weather forecasts and local production data), and other factors to control all system components in an optimal manner. A double-input single-output DC–DC converter is used to extract the maximum power point tracking (MPPT) from each source. This allows the converter to still transfer power from one source to another even if one of the sources is unable to generate power. In this HRES configuration, all the sources are connected in parallel through the common DC–DC converter. The strategy also includes a long short-term memory (LSTM) network-based forecasting approach to predict the available energy production and the battery state of charge (SOC). The system is tested using Matlab/Simulink and validated experimentally in a laboratory setting. [ABSTRACT FROM AUTHOR]

Superconducting magnetic energy storage (SMES) systems are characterized by their high-power density; they are integrated into high-energy density storage systems, such as batteries, to produce hybrid energy storage systems (HESSs), resulting in the increased performance of renewable energy sources (RESs). Incorporating RESs and HESS into a DC bus to obtain a DC microgrid concept is considered a more attractive option for solving system reliability and stability issues. In this paper, we focus on employing SMES systems based on their characteristics of a fast response and high efficiency, which contribute to increased battery lifespan, and reducing the mismatch between the energy supplied by the renewable energy source and the load demand by compensating for the effects of partial shading on the PV system on the DC bus side and the imbalance in loads on the other side of the AC bus. The incremental conductance algorithm (INC) is used for maximum power point tracking (MPPT) in the PV system. Fuzzy logic control (FLC) is proposed for the generation of control signals for the DC–DC chopper used to charge/discharge the SMES coil. Simulations using MATLAB/Simulink were then carried out to assess the proposed models of the (standalone and grid) connection systems. [ABSTRACT FROM AUTHOR]

Microgrids (MG) are small-scale electric grids with local voltage control and power management systems to facilitate the high penetration and grid integration of renewable energy resources (RES). The distributed generation units (DGs), including RESs, are connected to (micro) grids through power electronics-based inverters. Therefore, new paradigms are required for voltage and frequency regulation by inverter-interfaced DGs (IIDGs). Notably, employing effective voltage and frequency regulation methods for establishing power-sharing among parallel inverters in MGs is the most critical issue. This paper provides a comprehensive study, comparison, and classification of control methods including communication-based, decentralized, and construction and compensation control techniques. The development of inverter-dominated MGs has caused limitations in employing classical control techniques due to their defective performance in handling non-linear models of IIDGs. To this end, this article reviews and illustrates advanced controllers that can deal with the challenges that are created due to the uncertain and arbitrary impedance characteristics of IIDGs in dynamics/transients. [ABSTRACT FROM AUTHOR]

The rising demand for electricity, economic benefits, and environmental pressures related to the use of fossil fuels are driving electricity generation mostly from renewable energy sources. One of the main challenges in renewable energy generation is uncertainty involved in forecasting because of the intermittent nature of renewable sources. The demand also varies according to the time of day, the season, the location, the climate, and the availability of resources. Microgrids offer a potential solution for the integration of small-scale renewable energy sources and loads along with energy storage systems and other non-renewable sources. However, intermittent generation and varying demand need to be matched to provide stable power to consumers. Therefore, it is crucial to design an energy management system to effectively manage the energy sources and supply loads for reliable and efficient operation. This paper reviews different techniques proposed in the literature to achieve the objectives of a microgrid energy management system. The benefits of existing energy management systems and their challenges are also discussed. The challenges associated with uncertainties and methods to overcome them are critically reviewed. [ABSTRACT FROM AUTHOR]

Renewable-energy-based microgrids (MGs) are being advocated around the world in response to increasing energy demand, high levels of greenhouse gas (GHG) emissions, energy losses, and the depletion of conventional energy resources. However, the high investment cost of the MGs besides the low selling price of the energy to the main grid are two main challenges to realize the MGs in developing countries such as Iran. For this reason, the government should define some incentive policies to attract investor attention to MGs. This paper aims to develop a framework for the optimal planning of a renewable energy-based MG considering the incentive policies. To investigate the effect of the incentive policies on the planning formulation, three different policies are introduced in a pilot system in Iran. The minimum penetration rates of the RESs in the MG to receive the government incentive are defined as 20% and 40% in two different scenarios. The results show that the proposed incentive policies reduce the MG's total net present cost (NPC) and the amount of carbon dioxide (CO2) emissions. The maximum NPC and CO2 reduction in comparison with the base case (with incentive policies) are 22.87% and 56.13%, respectively. The simulations are conducted using the hybrid optimization model for electric renewables (HOMER) software. [ABSTRACT FROM AUTHOR]

Using renewable energy sources instead of fossil fuels is one of the best solutions to overcome greenhouse gas (GHG) emissions. However, in designing clean power generation microgrids, the economic aspects of using renewable energy technologies should be considered. Furthermore, due to the unpredictable nature of renewable energy sources, the reliability of renewable energy microgrids should also be evaluated. Optimized hybrid microgrids based on wind and solar energy can provide cost-effective power generation systems with high reliability. These microgrids can meet the power demands of the consuming units, especially in remote areas. Various techniques have been used to optimize the size of power generation systems based on renewable energy to improve efficiency, maintain reliability, improve the power grid's resilience, and reduce system costs. Each of these techniques has shown its advantages and disadvantages in optimizing the size of hybrid renewable energy systems. To increase the share of renewable energies in electricity supply in the future and develop these new technologies further, this paper reviews the latest and most efficient techniques used to optimize green microgrids from an economical and reliable perspective to achieve a clean, economical, and highly reliable microgrid. [ABSTRACT FROM AUTHOR]

This paper introduces a modified consensus-based real-time optimization framework for utility-connected and islanded microgrids scheduling in normal conditions and under cyberattacks. The exchange of power with the utility is modeled, and the operation of the microgrid energy resources is optimized to minimize the total energy cost. This framework tracks both generation and load variations to decide optimal power generations and the exchange of power with the utility. A linear cost function is defined for the utility where the rates are updated at every time interval. In addition, a realistic approach is taken to limit the power generation from renewable energy sources, including photovoltaics (PVs), wind turbines (WTs), and dispatchable distributed generators (DDGs). The maximum output power of DDGs is limited to their ramp rates. Besides this, a specific cloud-fog architecture is suggested to make the real-time operation and monitoring of the proposed method feasible for utility-connected and islanded microgrids. The cloud-fog-based framework is flexible in applying demand response (DR) programs for more efficiency of the power operation. The algorithm's performance is examined on the 14 bus IEEE network and is compared with optimal results. Three operating scenarios are considered to model the load as light and heavy, and after denial of service (DoS) attack to indicate the algorithm's feasibility, robustness, and proficiency. In addition, the uncertainty of the system is analyzed using the unscented transformation (UT) method. The simulation results demonstrate a robust, rapid converging rate and the capability to track the load variations due to the probable responsive loads (considering DR programs) or natural alters of load demand. [ABSTRACT FROM AUTHOR]

Even though many studies have been deployed to determine the optimal planning and operation of microgrids, limited research was discussed to determine the optimal microgrids' geographical boundaries. This paper proposes a zonal-based optimal microgrid identification model aiming at identifying the optimal microgrids topology in the current distribution systems through zoning the network into several clusters. In addition, the proposed model was developed as a mixed-integer linear programming (MILP) problem that identifies the optimal capacity and location of installing distributed energy resources (DERs), including but not limited to renewable energy resources and Battery Energy Storage Systems (BESS), within the determined microgrid's boundaries. Moreover, it investigates the impact of incorporating the BESS in boosting the DERs' penetration on the optimal centralized microgrid. Numerical simulations on the IEEE-33 bus test system demonstrate the features and effectiveness of the proposed model on identifying the optimal microgrid geographical boundaries on current distribution grids as well as its capability on defining the optimal sizes and locations of installing DERs within the microgrid's zonal area. [ABSTRACT FROM AUTHOR]

The international community has set ambitious targets to replace the use of fossil fuels for electricity generation with renewable energy sources. The use of large-scale (e.g., solar farms) and small-scale solutions (e.g., onsite green technologies) represents one way to achieve these goals. This paper presents a mathematical optimization framework to coordinate the energy decisions between the distribution network and the networked microgrids embedded within it. Utility-scale renewable and conventional generators are considered in the distribution network, while the microgrids include onsite renewable generation and energy storage. The distribution network operator utilizes demand-side management policies to improve the network's efficiency, and the microgrids operate under these programs by reducing their energy usage, scheduling the electricity usage under dynamic tariffs, and supplying energy to the grid. The uncertainty of renewable energy sources is addressed by robust optimization. The decisions of the distribution network and the microgrids are made independently, whereas the proposed collaboration scheme allows for the alignment of the systems' objectives. A case study is analyzed to show the capability of the model to assess multiple configurations, eliminating the necessity of load shedding, and increasing the power supplied by the microgrids (22.3 MW) and the renewable energy share by up to 5.03%. [ABSTRACT FROM AUTHOR]

Microgrids, or distributed systems of local energy generation, transmission, and demand, are now technologically and operationally capable of providing power to communities, especially in rural and peri-urban regions of developing nations. The reliability of the system, the cost of power generation, and the operating environmental impact are the major issues when designing and evaluating the performance of an off-grid hybrid renewable energy microgrid (HREM). This paper presents an integrated method for optimal sizing and operation of an HREM for rural agricultural communities in the Southern Philippines composed of run-of-the-river hydropower, photovoltaics (PV), diesel generator, and a battery energy storage system (BESS) using multi-objective particle swarm optimization (MOPSO) and a proposed multi-case power management strategy. The three conflicting objective functions that were simultaneously minimized were: loss of power supply probability (LPSP), levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions, subject to several constraints. The optimization generated 200 non-dominated or Pareto optimal alternative solutions, 4 of which were selected as solutions of interest. Based on the results, the optimal sizes of the main components for the reliable operation of the system are 100 panels with a rating of 0.25 kW for PV, 100 kWh for BESS, and 13 kW for the diesel generator, with corresponding LCOE, LPSP, and GHG emission values of 0.1795 USD/kWh, 0.05%, and 7874 kg, respectively, for 1 year. The effectiveness of the proposed HREM design was also analyzed, and the study yielded plenty of useful findings that could aid the electrification of the area. [ABSTRACT FROM AUTHOR]

The expansion of renewable energies is progressing strongly. The influence on the power supply networks by the variability of the infeed must be met with new concepts. In this paper, we investigate the possibilities of integrating microgrids as a cooperating unit in the power supply network to support further expansion of renewable energy sources (RES) power plants. In this paper, a differentiation of microgrids from similar network structures is established, and a classification of proposed groups is made. Then, after the description of the simulation of the components in a microgrid, with practical advice, an example model is shown, which aids the dimensioning of the components within a microgrid to achieve a specified goal. [ABSTRACT FROM AUTHOR]

The telecommunication industry relies heavily on a reliable and continuous power supply. Traditional power sources like diesel generators have long been the backbone of telecom infrastructure. However, the growing demand for sustainable and eco-friendly solutions has spurred interest in renewable energy sources. Proton exchange membrane (PEM) fuel cell-based systems, integrated with solar and wind energy, offer a promising alternative. This review explores the potential of these hybrid systems in stationary telecom applications, providing a comprehensive overview of their architecture, energy management, and storage solutions. As the demand for telecommunication services grows, so does the need for a reliable power supply. Diesel generators are linked with high operational costs, noise pollution, and significant greenhouse gas emissions, prompting a search for more sustainable alternatives. This review analyzes the current state of PEM fuel cell systems in telecom applications, examines the architecture of microgrids incorporating renewable energy sources, and discusses optimization methods, challenges, and future directions for energy storage systems. Critical findings and recommendations are presented, highlighting objectives and constraints for future developments. Leveraging these technologies can help the telecom industry reduce fossil fuel reliance, lower operational costs, minimize environmental impact, and increase system reliability. [ABSTRACT FROM AUTHOR]

Reactive power management in microgrids with high penetration of distributed renewable energy sources (DRESs) is challenging. The intermittent generation of DRES makes the power management cumbersome. Generally, Flexible AC Transmission System (FACTS) devices such as Distribution Static Compensator (DSTATCOM) are employed for reactive power compensation in microgrids. However, for effective results in microgrids, coordinated operation between DSTATCOM and Distributed Energy Resources (DERs) is required. In this paper, IEC 61850 communication is proposed for realizing coordinated operation between microgrid controller (MGCC), DSTATCOM and DERs. In microgrids, there may be large number of DERs dispersed over a large area. Hence, the underlying communication network technology for IEC 61850 communication must be highly scalable with wide range. Recently developed communication technology Long Term Evolution (LTE) is a promising solution since it offers high data rates, reliability, scalability and longer range. In this paper, the developed IEC 61850 based reactive power management system is tested with the LTE technology and the performance evaluation tests have been performed. Firstly, IEC 61850 messages have been mapped on LTE stack to enable their transmission. Then, simulations over a network emulator have been performed to evaluate the performance of IEC 61850 communication message exchanges over LTE network in terms of End to End (ETE) delays. [ABSTRACT FROM AUTHOR]

Energy storage (ES) is playing an increasingly important role in reducing the spatial and temporal power imbalance of supply and demand caused by the uncertainty and periodicity of renewable energy in the microgrid. The utilization efficiency of distributed ES belonging to different entities can be improved through sharing, and considerable flexibility resources can be provided to the microgrid through the coordination of ES sharing and demand response, but its reliability is affected by multiple uncertainties from different sources. In this study, a two-stage ES sharing mechanism is proposed, in which the idle ES capacity is aggregated on the previous day to provide reliable resources for real-time optimization. Then, a two-layer semi-coupled optimization strategy based on a deep deterministic policy gradient is proposed to solve the asynchronous decision problems of day-ahead sharing and intra-day optimization. To deal with the impact of multiple uncertainties, Monte Carlo sampling is applied to ensure that the shared ES capacity is sufficient in any circumstances. Simulation verifies that the local consumption rate of renewable energy is effectively increased by 12.9%, and both microgrid operator and prosumers can improve their revenue through the joint optimization of ES sharing and demand response. [ABSTRACT FROM AUTHOR]

The energy carrier infrastructure, including both electricity and natural gas sources, has evolved and begun functioning independently over recent years. Nevertheless, recent studies are pivoting toward the exploration of a unified architecture for energy systems that combines Multiple-Energy Carriers into a single network, hence moving away from treating these carriers separately. As an outcome, a new methodology has emerged, integrating electrical, chemical, and heating carriers and centered around the concept of Energy Hubs (EHs). EHs are complex systems that handle the input and output of different energy types, including their conversion and storage. Furthermore, EHs include Combined Heat and Power (CHP) units, which offer greater efficiency and are more environmentally benign than traditional thermal units. Additionally, CHP units provide greater flexibility in the use of natural gas and electricity, thereby offering significant advantages over traditional methods of energy supply. This article introduces a new approach for exploring the steady-state model of EHs and addresses all related optimization issues. These issues encompass the optimal dispatch across multiple carriers, the optimal hub interconnection, and the ideal hub configuration within an energy system. Consequently, this article targets the reduction in the overall system energy costs, while maintaining compliance with all the necessary system constraints. The method is applied in an existing Smart Microgrid (SM) of a typical Greek 17-bus low-voltage distribution network into which EHs are introduced along with Renewable Energy Sources (RESs) and Electric Vehicles (EVs). The SM experiments focus on the optimization of the operational cost using different operational scenarios with distributed generation (DG) and CHP units as well as EVs. A sensitivity analysis is also performed under variations in electricity costs to identify the optimal scenario for handling increased demand. [ABSTRACT FROM AUTHOR]

The massive expansion of Distributed Energy Resources and schedulable loads have forced a variation of generation, transmission, and final usage of electricity towards the paradigm of Smart Communities microgrids and of Renewable Energy Communities. In the paper, the use of multiple DC microgrids for residential applications, i.e., the nanogrids, in order to compose and create a renewable energy community, is hypothesized. The DC Bus Signaling distributed control strategy for the power management of each individual nanogrid is applied to satisfy the power flow requests sent from an aggregator. It is important to underline that this is an adaptive control strategy, i.e., it is used when the nanogrid provides a service to the aggregator and when not. In addition, the value of the DC bus voltage of each nanogrid is communicated to the aggregator. In this way, the aggregator is aware of the regulation capacity that each nanogrid can provide and which flexible resources are used to provide this capacity. The effectiveness of the proposed control strategy is demonstrated via numerical experiments. The energy community considered in the paper consists of five nanogrids, interfaced to a common ML-LV substation. The nanogrids, equipped with a photovoltaic plant and a set of lithium-ion batteries, participate in the balancing service depending on its local generation and storage capacity. [ABSTRACT FROM AUTHOR]

One of the most critical challenges for modern power systems is to reliably supply electricity to its consumers during and in the aftermath of natural disasters. As our dependence on electrical power has increased over the years, long-term power outages can lead to devastating impacts on affected communities. Furthermore, power outages can halt the operation of water treatment plants, leading to shortages in clean water, which is essential during post-disaster recovery. One way to address this is to temporarily reconfigure power and water networks into localized networks, i.e., electric microgrids and water micro-nets, that utilize local resources to supply local demand independently of the main power grid and/or water network. Utilizing distributed energy resources such as wind and solar and treating wastewater locally for potable reuse can provide the operational flexibility for such systems to operate sustainably. However, due to uncertainties in both renewable energy generation and electric/water consumption, ensuring sustainable operation is a challenging task. In this paper, an optimal operational strategy is proposed for an islanded microgrid/micro-net, considering the stochastic nature of renewable energy resources, electric demand, and water demand. An energy storage system is modeled to address the uncertainty in power generation and demand, in conjunction with local water storage and wastewater treatment to accommodate variable water demands. A two-stage stochastic programming model is formulated and solved to determine an optimal operation strategy for the combined system. [ABSTRACT FROM AUTHOR]

Direct current (DC) microgrids (MG) constitute a research field that has gained great attention over the past few years, challenging the well-established dominance of their alternating current (AC) counterparts in Low Voltage (LV) (up to 1.5 kV) as well as Medium Voltage (MV) applications (up to 50 kV). The main reasons behind this change are: (i) the ascending amalgamation of Renewable Energy Sources (RES) and Battery Energy Storage Systems (BESS), which predominantly supply DC power to the energy mix that meets electrical power demand and (ii) the ascending use of electronic loads and other DC-powered devices by the end-users. In this sense, DC distribution provides a more efficient interface between the majority of Distributed Energy Resources (DER) and part of the total load of a MG. The early adopters of DC MGs include mostly buildings with high RES production, ships, data centers, electric vehicle (EV) charging stations and traction systems. However, the lack of expertise and the insufficient standards' framework inhibit their wider spread. This review paper presents the state of the art of LV and MV DC MGs in terms of advantages/disadvantages over their AC counterparts, their interface with the AC main grid, topologies, control, applications, ancillary services and standardization issues. Overall, the aim of this review is to highlight the possibilities provided by DC MG architectures as well as the necessity for a solid/inclusive regulatory framework, which is their main weakness. [ABSTRACT FROM AUTHOR]

Multi-Use Platform (MUP) is a new topic addressed, extensively, under the EU funded projects that aim to exploit oceans in a sustainable way in order to reduce the costs of marine energy and to extract seafood. MUP's electrical grid experiences many challenges, being offshore. One of these challenges is that only Alternating Current (AC) systems are considered which are inefficient, expensive and require bulky components. Considering the advantages of Direct Current (DC) systems, this paper aims to study the feasibility of using the DC system to improve the electrical infrastructure of the MUP's grid. Floating energy unit comprising tidal, wind and solar energy resources is considered as a base unit for the MUP's grid. The paper proposes a new distributed controller for grid voltage regulation and minimizing circulating current among parallel-connected floating energy units in an offshore Low Voltage Direct Current (LVDC) microgrid. A mathematical model is derived for n-parallel floating energy units with the proposed controller. Additionally, stability analysis for the overall model of a single floating energy unit is also presented. The analysis and simulation of the proposed DC system demonstrate that the system is stable and fault-rejected at different operating conditions. [ABSTRACT FROM AUTHOR]

The European Union aims to reduce Greenhouse Gas (GHG) emissions by 55% before 2030 compared to 1990 as a reference year. One of the main contributions to GHG emissions comes from the household sector. This paper shows that the household sector, when organised into a form of prosumer microgrids, including renewable sources for electric, heating and cooling energy supply, can be efficiently decarbonised. This paper investigates one hypothetical prosumer microgrid with the model RES2GEO (Renewable Energy Sources to Geothermal). The aim is to integrate a carbon-free photovoltaic electricity source and a shallow geothermal reservoir as a heat source and heat sink during the heating and cooling season. A total of four cases have been evaluated for the Zagreb City location. The results represent a balance of both thermal and electric energy flows within the microgrid, as well as thermal recuperation of the reservoir. The levelised cost of energy for all cases, based on a 20-year modelling horizon, varies between 41 and 63 EUR/MWh. On the other hand, all cases show a decrease in CO2 emissions by more than 75%, with the best case featuring a reduction of more than 85% compared to the base case, where electricity and gas for heating are supplied from the Distribution System Operator at retail prices. With the use of close integration of electricity, heating and cooling demand and supply of energy, cost-effective decarbonisation can be achieved for the household sector. [ABSTRACT FROM AUTHOR]

Microgrids can assist in managing power supply and demand, increase grid resilience to adverse weather, increase the deployment of zero-emission energy sources, utilise waste heat, and reduce energy wasted through transmission lines. To ensure that the full benefits of microgrid use are realised, hybrid renewable energy-based microgrids must operate at peak efficiency. To offer an optimal solution for managing microgrids with hybrid renewable energy sources (HRESs) while taking microgrid reserve margins into account, the particle swarm optimisation (PSO) method is suggested. The suggested approach demonstrated good performance in terms of charging and discharging BESS and maintaining the necessary reserve margins to supply critical loads if the grid and renewable energy sources are unavailable. On a clear day, the amount of electricity sold to the grid increased by 58%, while on a partially overcast day, it increased by 153%. Microgrids provide a good return on investment for their operators when they are run at peak efficiency. This is because the BESS is largely charged during off-peak hours or with excess renewable energy, and power is only purchased during less expensive off-peak hours. [ABSTRACT FROM AUTHOR]

Modern power systems must provide efficient, reliable, and environmentally responsible energy. Recently, the inclusion of Microgrids (MGs) has allowed us to overcome some difficulties and face important challenges in this direction, especially related to the use of alternative energy sources. Increased and probabilistic demand, as well as limited energy supply, pose the need to evaluate the reliability of any distribution system (DS) when MGs are introduced. Here we reviewed and classified the state-of-the-art of reliability assessment (RA) in MGs. Initially, we contextualize RA in distribution systems. Next, each of the MGs subsystems components are introduced and the questions (1) why is it important to evaluate the reliability in Microgrids? (2) how do Microgrids influence the reliability of distribution systems? and (3) how does each of its subsystems influence the reliability of the Microgrids? are addressed. A total of 1395 research studies were published between 2002 and 2020. Using the PRISMA model, 147 met the inclusion criteria (71% correspond to research papers and 29% to reviews; 62% were published in journals, 34% were conference papers and 4% were books). The first study dates from 1971. Despite immense advances in MGs, we identified that (1) real test systems constitute an emerging trend; (2) although new MG configurations sound promising, the development and application of new RA techniques are a necessary step towards the identification of potential pitfalls of such architectures; (3) new RA methods or variations of the existing ones, whether analytical or simulation-based, are constantly being proposed, but their comparison for a particular DS, including MGs, are yet to be performed; and (4) more research studies are needed to assess how new control strategies and information and communications technology impact MGs reliability. Future lines of research could build upon these gaps to enhance reliability, especially when alternative energy resources are available. [ABSTRACT FROM AUTHOR]

As the penetration rate of renewable energy resources (RES) in the power system increases, uncertainty and variability in system operation increase. The application of energy storage systems (ESS) in the power system has been increased to compensate for the characteristics of renewable energy resources. Since ESS is a controllable and highly responsive power resource, primary frequency response and inertia response are possible in case of system contingency, so it can be utilized for frequency regulation (FR) purposes. In frequency regulation, reduction of the Rate of Change of Frequency (RoCoF) and increase the frequency nadir by improving the response characteristics are important factors to secure frequency stability. Therefore, it is important to control ESS with proper parameters according to changing system situation. In this paper, we propose a method to calculate and apply a frequency droop, which is basically required according to the power system condition based on swing equation and effective inertia assessment. In addition, a method to estimate RoCoF droop according to the correlation with frequency by estimating the systematic inertia in the current situation is proposed. The case study for verification of the proposed method was performed through dynamic simulation using actual Korean power system data. The results show that the proposed method is more effective than the governor-free of the conventional thermal generator and conventional droop control-based FR-ESS. [ABSTRACT FROM AUTHOR]

Grid-forming inverters are the essential components in the effort to integrate renewable energy resources into stand-alone power systems and microgrids. Performance of these inverters directly depends on their control parameters embodied in the controller. Even the most conscientiously designed controller will exhibit suboptimal performance upon implementation due to the presence of parasitic elements in the existing hardware. Hence, the controller has to be tuned and optimized. In the present article, the process of implementation, laboratory verification, and tuning of a matching-controlled grid-forming inverter is presented. In order to assess the efficiency of the grid-forming controller, its operation has been tested and analyzed in blackstart, steady state, and transient operation. For this purpose, a systematic sensitivity analysis has been conducted and the control parameters have been tuned in laboratory tests. The laboratory results verify proper operation of a 7 kW grid-forming inverter in all three test scenarios. After applying the proposed method on the tested grid-forming inverter in steady state operation, total harmonic distortion (THD) of the output voltage is less than 0.5% for its practical loading range (maximum THD is less than 1% in no-load condition). The system is able to blackstart and supply the loads. Finally, the studied grid-forming inverter is stable in the presence of severe step load changes and disturbances, i.e., voltage overshoot is managed well and compensated for with a low settling time using this approach. [ABSTRACT FROM AUTHOR]

This paper presents the analysis of an energy management system (EMS) implemented to fulfill the requirements of a microgrid (MG) power supply owned by a small industrial company and connected to the rural power system. The main goal of this system is to ensure connection with the existing rural power system in terms of energy exchange, as well as to perform islanding mode operation of the microgrid based on the energy demand of the company. Power generated in the implemented microgrid is based on a hybrid system supported by renewable energy sources and an energy storage system. The aim of the developed energy management system implemented in this MG power system is to enable the microgrid to operate according to scheduled diagrams related to different load events. The presented investigation, analysis, and assessment of the implemented energy management system are based on the on-site measurements and observations of the long-term operation of the microgrid concerning the hybrid renewable energy-based generation system and the company energy demand, which is useful from perspective of the predicted deficiency of electrical energy in Poland, both for customers and transmission system operators. Furthermore, the observed drawbacks and failures of the implemented EMS and the MG are pointed out and discussed to overcome and minimize these disadvantages, and to improve the operational reliability of the whole system. [ABSTRACT FROM AUTHOR]

Seaports are well known as the medium that has evolved into the central link between sea and land for complex marine activities. The growth in maritime logistics particularly necessitates a large volume of energy supply in order to maintain the operation of sea trade, resulting in an imbalance between generation and demand sides. Future projections for three major concerns show an increase in load demand, cost of operation, and environmental issues. In order to overcome these problems, integrating microgrids as an innovative technology in the seaport power system appears to be a vital strategy. It is believed that microgrids enhance seaport operation by providing sustainable, environmentally friendly, and cost-effective energy. Although microgrids are well established and widely used in a variety of operations on land, their incorporation into the seaport is still limited. The involvement of a variety of heavy loads such as all-electric ships, cranes, cold ironing, and buildings infrastructure renders it a complicated arrangement task in several aspects, which necessitates further research and leaves space for improvement. In this paper, an overview of the seaport microgrids in terms of their concepts and operation management is presented. It provides the perspectives for integrating the microgrid concept into a seaport from both shore side and seaside as a smart initiative for the green port's vision. Future research directions are discussed towards the development of a more efficient marine power system. [ABSTRACT FROM AUTHOR]

Microgrids are empowered by the advances in renewable energy generation, which enable the microgrids to generate the required energy for supplying their loads and trade the surplus energy to other microgrids or the macrogrid. Microgrids need to optimize the scheduling of their demands and energy levels while trading their surplus with others to minimize the overall cost. This can be affected by various factors such as variations in demand, energy generation, and competition among microgrids due to their dynamic nature. Thus, reaching optimal scheduling is challenging due to the uncertainty caused by the generation/consumption of renewable energy and the complexity of interconnected microgrids and their interplay. Previous works mainly rely on modeling-based approaches and the availability of precise information on microgrid dynamics. This paper addresses the energy trading problem among microgrids by minimizing the cost while uncertainty exists in microgrid generation and demand. To this end, a Bayesian coalitional reinforcement learning-based model is introduced to minimize the energy trading cost among microgrids by forming stable coalitions. The results show that the proposed model can minimize the cost up to 23% with respect to the coalitional game theory model. [ABSTRACT FROM AUTHOR]

Modern (micro) grids host inverter-based generation units for utilizing renewable and sustainable energy resources. Due to the lack of physical inertia and, thus, the low inertia level of inverter-interfaced energy resources, the frequency dynamic is adversely affected, which critically impacts the stability of autonomous microgrids. The idea of virtual inertia control (VIC), assisted by battery energy storage systems (BESSs), has been presented to improve the frequency dynamic in islanded microgrids. This study presents the PD-FOPID cascaded controller for the BESS, a unique method for enhancing the performance of VIC in islanded microgrids. Using the firefly algorithm (FA), the settings of this controller are optimally tuned. This approach is robust to disruptions due to uncertainties in islanded microgrids. In several scenarios, the performance of the suggested approach is compared with those of other control techniques, such as VIC based on an MPC controller, VIC based on a robust H-infinite controller, adaptive VIC, and VIC based on an optimized PI controller. The simulation results in MATLAB show that the suggested methodology in the area of VIC is better than previous methods. [ABSTRACT FROM AUTHOR]

This article suggests a hybrid DC microgrid (HDCMG) with different levels of DC bus voltages to use for various types of loads. The available sources in the HDCMG are wind generating systems (WGSs), photovoltaic (PV) systems, battery banks, and the AC grid for emergencies. The various levels of the DC bus voltages are 760 V, 380 V, and 48 V for different application uses such as electric vehicles and home applications. In addition, the controller plays an important role in the proposed system to achieve the desired DC bus voltage levels and extract the maximum power point (MPP) from the WGS and PV systems. In order to check the power continuity for the critical loads and improve the overall system performance, a suggested energy management strategy (SEMS) is developed. The SEMS is based on the optimum generated power and the state-of-charge (SOC) of the battery banks. Further, the SEMS is developed as a way to prevent battery storage from overcharging and deep discharging. The mathematical relations of the proposed HDCMG and MPP tracking are described. The bidirectional 3-Φ inverter connects the 760 V bus voltage to the AC grid for regulating this DC bus by absorbing the excess power or supplying the required power during the shortage in the generation and the low SOC of the battery storage. Buck converters with controlled duty cycles rather than constant duty cycles are used to obtain 380 V and 48 V from 760 V to achieve better dynamic responses. The overall HDCMG is evaluated using the MATLAB/Simulink package under different working cases to verify the capability of the control system and the PEMS. The obtained results are discussed and show the good performance and the capability of the overall system under the different scenarios, including (i) a comparison between variable duty and constant duty; (ii) high/low generated power and the SOC of the battery in the acceptable region; (iii) high/low generated power and the SOC of the battery in the critical region; and (iv) high/low generated power and the SOC of the battery in the overcharging region. [ABSTRACT FROM AUTHOR]

This study investigated a grid-connected smart microgrid (MG) system integrating solar photovoltaic (PV) panels and a battery energy storage system (BESS) as distributed energy resources (DERs) to locally serve residential loads. The load-shifting demand-side management (DSM) technique was employed to effectively manage the load appliances. The proposed load-shifting algorithm relies on minimum price incentives to allow customers to allocate their load appliances economically during minimum price periods. The algorithm considers the waiting times and minimum tariff periods for appliances, calculates precise operating durations for each appliance, and prioritizes powering the appliances from the MG first, followed by the main grid. The system comprises two non-shiftable and three shiftable loads. When the MG power is insufficient to activate all shiftable loads, the system transfers the remaining unsupplied shiftable appliances to periods with low-priced energy. The Energy Internet concept is adopted to manage energy and monitor usage when a customer is unable to check the accuracy of their energy meter by supervising the system's features on-site. The proposed comprehensive system enables load management, continuous monitoring, customer awareness, and energy cost saving. Six cases were studied, both numerically and experimentally, with varying MG power generation and load pre-scheduling periods, with and without DSM application. In all adopted cases, the implemented system save energy costs by at least 50%. [ABSTRACT FROM AUTHOR]

To sustain the complexity of growing demand, the conventional grid (CG) is incorporated with communication technology like advanced metering with sensors, demand response (DR), energy storage systems (ESS), and inclusion of electric vehicles (EV). In order to maintain local area energy balance and reliability, microgrids (MG) are proposed. Microgrids are low or medium voltage distribution systems with a resilient operation, that control the exchange of power between the main grid, locally distributed generators (DGs), and consumers using intelligent energy management techniques. This paper gives a brief introduction to microgrids, their operations, and further, a review of different energy management approaches. In a microgrid control strategy, an energy management system (EMS) is the key component to maintain the balance between energy resources (CG, DG, ESS, and EVs) and loads available while contributing the profit to utility. This article classifies the methodologies used for EMS based on the structure, control, and technique used. The untapped areas which have scope for investigation are also mentioned. [ABSTRACT FROM AUTHOR]

The fast depletion of fossil fuels and the growing awareness of the need for environmental protection have led us to the energy crisis. Positive development has been achieved since the last decade by the collective effort of scientists. In this regard, renewable energy sources (RES) are being deployed in the power system to meet the energy demand. The microgrid concept (AC, DC) is introduced, in which distributed energy resources (DERs), the energy storage system (ESS) and loads are interconnected. DC microgrids are appreciated due to their high efficiency and reliability performance. Despite its significant growth, the DC microgrid is still relatively novel in terms of grid architecture and control systems. In this context, an energy management system (EMS) is essential for the optimal use of DERs in secure, reliable, and intelligent ways. Therefore, this paper strives to shed light on DC microgrid architecture, control structure, and EMS. With an extensive literature survey on EMSs' role, different methods and strategies related to microgrid energy management are covered in this article. More attention is centered on the EMS for DC microgrids in terms of size and cost optimization. A very concise analysis of multiple optimization methods and techniques has been presented exclusively for residential applications. [ABSTRACT FROM AUTHOR]

Energy storage systems are an effective solution to manage the intermittency of renewable energies, balance supply, and demand. Numerous studies recommend adopting a shared energy storage system (ESS) as opposed to multiple single ESSs because of their high prices and inefficiency. Thus, this study examines a shared storage system in a grid-connected microgrid. By modifying the power outputs of the energy resources, this work intends to implement an economic dispatch of a shared ESS in order to satisfy the power balance and lower the overall cost of electricity. In this context, an optimization problem was formulated and developed using a mixed-integer linear programming (MILP) model. Furthermore, a pilot project (the Solar Decathlon Africa Village) in the Green & Smart Building Park (GSBP), Benguerir, Morocco, was employed to evaluate and verify the proposed approach. Some comparable scenarios were therefore run in a MATLAB environment. The collected findings demonstrate the efficacy of the developed algorithm in terms of optimizing energy cost reductions and enhancing the integration of renewable resources into the Moroccan energy mix. [ABSTRACT FROM AUTHOR]

This article presents a cost-effective and reliable solution for meeting the energy demands of remote areas through the integration of multiple renewable energy sources. The proposed system aims to reduce dependence on fossil fuels and promote sustainable development by utilizing accessible energy resources in a self-contained microgrid. Using the Hybrid Optimization Model for Electric Renewable (HOMER) software, the study examined the optimal combination of energy sources and storage technologies for an integrated hybrid renewable energy system (IHRES) in the Patiala location of Punjab. The total life cycle cost (TLCC) is the main objective of this manuscript. The HOMER result is taken as a reference, and the results are compared with the optimization hybrid algorithm (PSORSA). From this, it is clear that the proposed algorithm has less TLCC as compared to others. Two combinations of energy sources and storage technologies were considered, namely solar photovoltaic (PV)/battery and solar PV/fuel cell (FC). The results showed that the solar PV/FC combination is more cost-effective, reliable, and efficient than the solar PV/battery combination. Additionally, the IHRES strategy was found to be more economically viable than the single energy source system, with lower total life cycle costs and greater reliability and efficiency. Overall, the proposed IHRES model offers a promising solution for meeting energy demands in remote areas while reducing dependence on fossil fuels and promoting sustainable development. [ABSTRACT FROM AUTHOR]

The capacity configuration of the energy storage system plays a crucial role in enhancing the reliability of the power supply, power quality, and renewable energy utilization in microgrids. Based on variational mode decomposition (VMD), a capacity optimization configuration model for a hybrid energy storage system (HESS) consisting of batteries and supercapacitors is established to achieve the optimal configuration of energy storage capacity in wind–solar complementary islanded microgrids. Firstly, based on the energy mapping relationship between the frequency domain and time domain, the decomposition mode number K of VMD is determined based on the principle of minimum total mode aliasing energy. Then, considering the smoothing fluctuation characteristics of different energy storage components, the dividing point N of high frequency and low frequency in the unbalanced power between the source and load in the microgrid is selected to allocate charging and discharging power instructions for the battery and supercapacitor. Finally, taking the annual comprehensive cost of the HESS as the objective function, a hybrid energy storage capacity optimization configuration model is established, and the dividing point N is used as the optimization variable to solve the model in order to obtain the optimal configuration results. The case study results show that the proposed method is more economical and feasible than the existing energy storage configuration methods. [ABSTRACT FROM AUTHOR]