Energy Storage System In Microgrid Research Articles

A classification control strategy for energy storage system in microgrid

Storage devices are indispensable elements in a microgrid to compensate for the power imbalance between loads and the distributed generator (DG) output. Different storage strategies give diverse performances in adjustment speed and capacity. Based on the performance of different storage devices and the features of power imbalance curve in different periods, a classification control strategy is proposed in this paper. First, storage devices are given priorities according to the adjusting speed, and the power imbalance curve is divided into two periods according to the changing speed. During an emergency, all the storages are employed to compensate the rapidly increasing power imbalance; during the steady period, storage device with higher priority is employed to track the instantaneous component of power imbalance, while storage device with lower priority is used to replace the kWh output of higher priority storage. The proposed strategy is tested in a microgrid within the subdistribution network of IEEE RBTS Bus6 system using Monte Carlo methods. Simulation results indicate that the classification control strategy could endow the system with fast adjusting ability through coordination between storages. Reliability indices of the testing system are utilized to demonstrate that the classification control strategy could improve the stability of the microgrid and reliability of the distribution network. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

A method for optimal sizing energy storage systems for microgrids

This paper proposes a genetic algorithm-based method for sizing the energy storage system (ESS) in microgrids. The main goal of the proposed method is to find the energy and power capacities of the storage system that minimizes the operating cost of the microgrid. The energy management strategy (EMS) used in this paper is based on a fuzzy expert system which is responsible for setting the power output of the ESS. The design of the EMS is carried out by means of a genetic algorithm that is used to set the fuzzy rules and membership functions of the expert system. Given that the size of the storage system has a major influence on the energy management strategy, in this paper the EMS and ESS capacities are jointly optimized. In addition, the proposed method uses an aging model to predict the lifetime of the ESS. In this way it is possible to determine the cost associated with energy storage in a more precise manner. The unit commitment problem, which is crucial for the proper operation of the microgrid, has been also considered in the present work. The suggested sizing methodology has been validated in two case studies.

An Operating Control Strategy of Zinc Bromine Flow Battery Energy Storage Systems in Microgrid

With the continuous development of distributed solar, wind power and other renewable energy sources, renewable energy sources which has its own features, such as intermittent and randomness volatility, brings great challenges to the stable operation of power grid. Aiming at meeting the requirement of balancing the fluctuating renewable energy sources of micro grid, this paper proposes the operating control strategies of the zinc bromine flow battery storage. Firstly, the equivalent mathematical model based on the working principle of the zinc bromine flow battery is established; Secondly, a dual closed-loop strategy for the DC/DC converter is proposed, of which the inner loop is peak current control on zinc bromine flow battery side inductance while the outer loop is a switch control by constant active power and trickle current. By resorting the DC/AC grid side converter, the stability of DC bus voltage is maintained; Then, this paper proposes the optimization power control strategies of zinc bromine battery energy storage system as a constraint of state of charge and DC bus voltage; Finally, a 50kW zinc bromine flow battery energy storage system test platform is built, and the charging and discharging characteristics of zinc bromine energy storage system (ZESS) is researched in grid-connected mode, the test results have shown that the proposed power optimization control strategies for zinc bromine energy storage system could smooth renewable energy sources power fluctuation.

Optimal allocation of distributed generation and energy storage system in microgrids

This study presents a new approach for optimal allocation of distributed generation (DG) and energy storage system (ESS) in microgrids (MGs). The practical optimal allocation problems have non-smooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. A dynamic capacity adjustment algorithm is incorporated in the matrix real-coded genetic algorithm (MRCGA) framework to deal with the non-smooth cost functions. The proposed cost function takes into consideration operation cost minimisation as well as investment cost minimisation at the same time for the MG. Moreover, an energy storage equality constraint is applied to manage the state of charge of EES in MGs. The MRCGA is used to minimise the cost function of the system while constraining it to meet the customer demand and security of the system. For each studied case, sets of optimal capacities and economic operation strategies of ESS and DG sources are determined. The computational simulation results are presented to verify the effectiveness of the proposed method.

Optimal sizing of energy storage system for microgrids

Microgrids (MGs) are Low Voltage distribution networks comprising various distributed generators (DG), storage devices and controllable loads that can operate either interconnected or isolated from the main distribution grid as a controlled entity. Energy storage system (ESS) is a vital part of an MG. In this paper, a methodology is proposed for the optimal allocation and economic analysis of ESS in MGs on the basis of net present value (NPV). As the optimal operation of an MG strongly depends on the arrangement and allocation of its ESS, economic operation strategies and optimal allocation methods of the ESS devices are required for the MG. Self-adaptive Bee Swarm Optimization (SBSO) algorithm is applied to optimize the operation strategies and capacities of ESS in MGs in order to find maximal NPV, the generation schedule of ESS and distributed generation sources. This paper is to suggest, among those available ESS, the optimal sizes and types of them and their optimal arrangement, such that the total NPV achieved during the system operational lifetime period is maximized. After introducing the methodology, a case study is presented for illustration.

Retraction notice to “A review of energy storage systems in microgrids with wind turbines” [Renew. Sustain. Energy Rev. 18 (2012) 316–326

Retraction notice to “A review of energy storage systems in microgrids with wind turbines” [Renew. Sustain. Energy Rev. 18 (2012) 316–326

Energy Management for Lifetime Extension of Energy Storage System in Micro-Grid Applications

Energy storage is needed in micro-grid to help solve the problem of intermittency introduced by renewable energy sources, enhance power quality and improve controllability of power flow. This paper presents an energy manager for energy storage system (ESS) in micro-grids. The objectives of the energy manager are focused on improving the energy efficiency and extending the life expectancy of ESS while ensuring constraints of energy storage modules are complied with. To this end a smart local prediction and local scheduling algorithm is proposed. A battery lifetime model that uses the proposed Peukert lifetime energy throughput based on the workload of the battery is developed. Verification shows that in the long run, the energy manger can improve overall energy efficiency of ESS from 74.1% to 85.5%, and improve estimated lifetime of 2 Battery Packs in ESS from 3.6 years and 2.4 years to 5 years and 5.7 years respectively.

An Efficiency-Optimized Isolated Bidirectional DC-DC Converter with Extended Power Range for Energy Storage Systems in Microgrids

This paper proposes a novel extended-single-phase shift (ESPS) control strategy of isolated bidirectional full-bridge DC-DC converters (IBDCs) which are a promising alternative as a power electronic interface in microgrids with an additional function of galvanic isolation. Based on the mathematical models of ESPS control under steady-state conditions, detailed theoretical and experimental analyses of IBDC under ESPS control are presented. Compared with conventional single-phase-shift (CSPS) control, ESPS control can greatly improve the efficiency of IBDCs in microgrids through decreasing current stress and backflow power considerably over a wide input and output voltage range under light and medium loads. In addition, ESPS control only needs to adjust one single phase-shift angel to control transmission power, thus it retains implementation simplicity in comparison with dual-phase-shift (DPS) control for microgrid applications. Furthermore, an efficiency-optimized modulation scheme based on ESPS and CSPS control is developed in the whole power range of IBDC for power distribution in microgrids. A 10 kW IBDC prototype is constructed and the experimental results validate the effectiveness of the proposed control strategy, showing that the proposed strategy can enhance the overall efficiency up to 30%.

Optimal Allocation and Economic Analysis of Energy Storage System in Microgrids

This paper presents a methodology for the optimal allocation and economic analysis of energy storage system (ESS) in microgrids (MGs) on the basis of net present value (NPV). As the performance of an MG strongly depends on the allocation and arrangement of its ESS, optimal allocation methods and economic operation strategies of the ESS devices are required for the MG. To optimize the operation strategies and capacities of ESS in MGs, the financial benefit and dynamic models of ESS are discussed. And then, a matrix real-coded genetic algorithm is applied to find maximal NPV, in which each GA chromosome consists of a 2-D real number matrix representing the generation schedule of ESS and distributed generation sources. This paper is to suggest, among those available ESS, the optimal sizes and types of them and their optimal arrangement, such that the total NPV achieved during the system operational lifetime period is maximized. Finally, some computational simulation results are presented to verify the effectiveness of the proposed method.

Editorial Special Issue on Power Electronics for Microgrids—Part II

The 46 papers in this second part of the special section on power electronics cover the following topics: AC microgrids; grid-interactive microgrids; DC microgrids; energy storage systems for microgrids; distributed generation (DG) units; maximum power point tracking (MPPT) algorithms for DG and microgrids; anti-islanding algorithms; synchronization for DG and microgrids; and topologies and front-ends for microgrids.

Guest Editorial Editorial Special Issue on Power Electronics for Microgrids—Part I

The 25 papers in this first part of the special section on power electronics for microgrids are organized according to the following six topics: novel technologies for microgrids; operation and protection of microgrids and distributed generation units; control of parallel-connected inverters; energy storage systems for microgrids; low voltage direct current microgrids and high voltage direct current systems; and grid interactive applications.