Massive energy storage system for effective usage of renewable energy

The current energy trend indicates a strong thrust toward transforming renewable energy as a major power source.To achieve this mission,battery energy storage systems(BESSs)are indispensable.Although BESSs are expensive,cost reduction can be achieved by using BESSs for multiple purposes,such as load leveling,business continuity planning,frequency control,capacity market,arbitrage,and emergency power.In this paper,various applications of BESSs are classified.The possibility of achieving conflict-free combination of different applications is demonstrated.The total required energy storage capacity in Japan is estimated to be 150–200 GWh by 2030.The present status of NaS batteries for multipurpose use and new trends in battery-based businesses are introduced.

Improved Energy Management Strategy for Prosumer Buildings with Renewable Energy Sources and Battery Energy Storage Systems

The concept of utilizing microgrids(MGs)to convert buildings into prosumers is gaining massive popularity because of its economic and environmental benefits.These pro-sumer buildings consist of renewable energy sources and usually install battery energy storage systems(BESSs)to deal with the uncertain nature of renewable energy sources.However,because of the high capital investment of BESS and the limitation of available energy,there is a need for an effective energy management strategy for prosumer buildings that maximizes the profit of building owner and increases the operating life span of BESS.In this regard,this paper proposes an improved energy management strategy(IEMS)for the prosumer building to minimize the operating cost of MG and degradation factor of BESS.Moreover,to estimate the practical operating life span of BESS,this paper utilizes a non-linear battery degradation model.In addition,a flexible load shifting(FLS)scheme is also developed and integrated into the proposed strategy to further improve its performance.The proposed strategy is tested for the real-time annual data of a grid-tied solar photovoltaic(PV)and BESS-powered AC-DC hybrid MG installed at a commercial building.Moreover,the scenario reduction technique is used to handle the uncertainty associated with generation and load demand.To validate the performance of the proposed strategy,the results of IEMS are compared with the well-established energy management strategies.The simulation results verify that the proposed strategy substantially increases the profit of the building owner and operating life span of BESS.Moreover,FLS enhances the performance of IEMS by further improving the financial profit of MG owner and the life span of BESS,thus making the operation of prosumer building more economical and efficient.

Virtual Transmission Solution Based on Battery Energy Storage Systems to Boost Transmission Capacity

The increasing penetration of variable renewable energy(VRE)generation along with the decommissioning of conventional power plants in Chile,has raised several operational challenges in the Chilean National Power Grid(NPG),including transmission congestion and VRE curtailment.To mitigate these limitations,an innovative virtual transmission solution based on battery energy storage systems(BESSs),known as grid booster(GB),has been proposed to increase the capacity of the main 500 kV corridor of the NPG.This paper analyzes the dynamic performance of the GB using a wide-area electromagnetic transient(EMT)model of the NPG.The GB project,composed of two 500 MVA BESS units at each extreme of the 500 kV corridor,allows increasing the transmission capacity for 15 min during N-1 contingencies,overcoming transmission limitations under normal operation conditions while maintaining system stability during faults.The dynamic behavior of the GB is also analyzed to control power flow as well as voltage stability.The results show that the GB is an effective solution to allow greater penetration of VRE generation while maintaining system stability in the NPG.

An Analytical Method for Delineating Feasible Region for PV Integration Capacities in Net-zero Distribution Systems Considering Battery Energy Storage System Flexibility

To provide guidance for photovoltaic(PV)system integration in net-zero distribution systems(DSs),this paper proposes an analytical method for delineating the feasible region for PV integration capacities(PVICs),where the impact of battery energy storage system(BESS)flexibility is considered.First,we introduce distributionally robust chance constraints on network security and energy/carbon net-zero requirements,which form the upper and lower bounds of the feasible region.Then,the formulation and solution of the feasible region is proposed.The resulting analytical expression is a set of linear inequalities,illustrating that the feasible region is a polyhedron in a high-dimensional space.A procedure is designed to verify and adjust the feasible region,ensuring that it satisfies network loss constraints under alternating current(AC)power flow.Case studies on the 4-bus system,the IEEE 33-bus system,and the IEEE 123-bus system verify the effectiveness of the proposed method.It is demonstrated that the proposed method fully captures the spatio-temporal coupling relationship among PVs,loads,and BESSs,while also quantifying the impact of this relationship on the boundaries of the feasible region.

Multi-Scale Fusion Model Based on Gated Recurrent Unit for Enhancing Prediction Accuracy of State-of-Charge in Battery Energy Storage Systems

Accurate prediction of the state-of-charge(SOC)of battery energy storage system(BESS)is critical for its safety and lifespan in electric vehicles.To overcome the imbalance of existing methods between multi-scale feature fusion and global feature extraction,this paper introduces a novel multi-scale fusion(MSF)model based on gated recurrent unit(GRU),which is specifically designed for complex multi-step SOC prediction in practical BESSs.Pearson correlation analysis is first employed to identify SOC-related parameters.These parameters are then input into a multi-layer GRU for point-wise feature extraction.Concurrently,the parameters undergo patching before entering a dual-stage multi-layer GRU,thus enabling the model to capture nuanced information across varying time intervals.Ultimately,by means of adaptive weight fusion and a fully connected network,multi-step SOC predictions are rendered.Following extensive validation over multiple days,it is illustrated that the proposed model achieves an absolute error of less than 1.5%in real-time SOC prediction.

Coordinated voltage regulation strategy of OLTC and BESS considering switching delay

When large-scale distributed renewable energy power generation systems are connected to the power grid,the risk of grid voltage fluctuations and exceeding the limit increases greatly.Fortunately,the on-load tap changer(OLTC)can adjust the transformer winding tap to maintain the secondary side voltage within the normal range.However,the inevitable delay in switching transformer taps makes it difficult to respond quickly to voltage fluctuations.Moreover,switching the transformer taps frequently will decrease the service life of OLTC.In order to solve this critical issue,a cooperative voltage regulation strategy applied between the battery energy storage systems(BESSs)and OLTSs.is proposed By adjusting the charge and discharge power of BESSs,the OLTC can frequently switch the transformer taps to achieve rapid voltage regulation.The effectiveness of the proposed coordinated regulation strategy is verified in the IEEE 33 node distribution systems.The simulation results show that the proposed coordinated regulation strategy can stabilize the voltage of the distribution network within a normal range and reduce the frequency of tap switching,as such elongating the service life of the equipment.

Deep reinforcement learning for online scheduling of photovoltaic systems with battery energy storage systems

A new online scheduling algorithm is proposed for photovoltaic(PV)systems with battery-assisted energy storage systems(BESS).The stochastic nature of renewable energy sources necessitates the employment of BESS to balance energy supplies and demands under uncertain weather conditions.The proposed online scheduling algorithm aims at minimizing the overall energy cost by performing actions such as load shifting and peak shaving through carefully scheduled BESS charging/discharging activities.The scheduling algorithm is developed by using deep deterministic policy gradient(DDPG),a deep reinforcement learning(DRL)algorithm that can deal with continuous state and action spaces.One of the main contributions of this work is a new DDPG reward function,which is designed based on the unique behaviors of energy systems.The new reward function can guide the scheduler to learn the appropriate behaviors of load shifting and peak shaving through a balanced process of exploration and exploitation.The new scheduling algorithm is tested through case studies using real world data,and the results indicate that it outperforms existing algorithms such as Deep Q-learning.The online algorithm can efficiently learn the behaviors of optimum non-casual off-line algorithms.

考虑储能单元健康状态与荷电状态一致性的BESS功率分配策略

针对由多个储能单元组成的大型电池储能系统(BESS)不规则充放电导致的储能单元健康状态(SOH)和荷电状态(SOC)不一致性问题,研究储能单元内SOH差异与SOC一致性的关系。结合充放电优先级排序和自适应变异粒子群优化(AMPSO)算法,提出考虑储能单元SOH和SOC一致性的BESS功率分配策略。基于包含BESS、风/光发电、电动汽车和常规负荷的共直流母线型集中式微电网并网示范平台的实测数据,对所提功率分配控制策略与传统功率分配控制策略进行了对比仿真分析。仿真结果表明,所提控制策略可有效提高储能单元SOC的一致性,延长储能单元使用寿命,降低储能单元运行损耗,增强BESS双向调节能力。

Contingency Reserve Evaluation for Fast Frequency Response of Multiple Battery Energy Storage Systems in a Large-scale Power Grid

Recently,the fast frequency response(FFR)service by large-scale battery energy storage systems(BESSs)has been successfully proved to arrest the frequency excursion during an unexpected power outage.However,adequate frequency response relies on proper evaluation of the contingency reserve of BESSs.The BESS FFR reserve is commonly managed under fixed contracts,ignoring various response characteristics of different BESSs and their coexisting interactions.This paper proposes a new methodology based on dynamic grid response and various BESS response characteristics to optimise the FFR reserves and prevent the frequency from breaching the under-frequency load shedding(UFLS)thresholds.The superiority of the proposed method is demonstrated to manage three large-scale BESSs operating simultaneously in an Australian power grid under high renewable penetration scenarios.Further,the proposed method can identify remaining battery power and energy reserve to be safely utilised for other grid services(e.g.,energy arbitrage).The results can provide valuable insights for integrating FFR into conventional ancillary services and techno-effective management of multiple BESSs.

部分接入电池储能系统的模块化多电平换流器控制方法

部分接入电池储能系统的模块化多电平换流器(MMC with partly integrated BESS,MMCPBESS)可以在接入储能的同时节约建造成本,但其控制更加复杂。针对下桥臂接入储能电池的MMC-PBESS拓扑,建立数学模型及等效电路。在此基础上给出电容电压均衡策略,提出了上/下桥臂分控的控制策略,并分析了其运行边界。在MATLAB/Simulink平台搭建仿真模型,仿真了不同交直流功率比例的运行工况,所提控制策略可以在维持电容电压平衡的同时实现对电池充电的功能。该策略无需额外的环流计算,上下桥臂控制解耦,简单灵活。

基于SVPWM控制的STATCOM-BESS特性分析与仿真

针对传统静止无功补偿器(static synchronous compensator-STATCOM)只能补充无功功率的不足,对直流侧并联蓄电池储能系统(battery energy storage system-BESS)的改进装置进行了研究,从而实现有功无功功率的双重控制。首先对STATCOM-BESS工作原理和数学模型进行简要介绍,之后对四象限模式的运行特性进行重点分析,并研究了基于电压空间矢量(SVPWM)有功功率无功功率独立控制的电流解耦控制技术。最后在MATLAB/Simulink中搭建STATCOM-BESS模型进行仿真分析,仿真结果显示装置在快速实现无功功率补偿的同时也可以实现有功功率的控制,并具有良好的动稳态特性,因此验证了理论分析的正确性和控制方法的有效性。

含储能有源配网的经济调度与协同优化

为了提升电池储能系统的有源配网运行效益,提出面向电池储能有源配网,包含经济调度与协同优化方法的分层递阶系统架构。首先,概述模型中不同层级间的逻辑运算关系;其次,针对不同层的优化目标,建立含光-储-充有源配网的经济调度与优化的2阶段模型。第1阶段以系统成本最小化为优化目标,第2阶段以系统网损最小为目标进行建模与仿真。最后,基于不同运行场景下的仿真结果,分析光、储、充的变化规律,并给出储能系统在不同节点的优化配置方案。

Optimal Bidding Strategy for PV and BESSs in Joint Energy and Frequency Regulation Markets Considering Carbon Reduction Benefits

Photovoltaic(PV)and battery energy storage systems(BESSs)are key components in the energy market and crucial contributors to carbon emission reduction targets.These systems can not only provide energy but can also generate considerable revenue by providing frequency regulation services and participating in carbon trading.This study proposes a bidding strategy for PV and BESSs operating in joint energy and frequency regulation markets,with a specific focus on carbon reduction benefits.A two-stage bidding framework that optimizes the profit of PV and BESSs is presented.In the first stage,the day-ahead energy market takes into account potential real-time forecast deviations.In the second stage,the real-time balancing market uses a rolling optimization method to account for multiple uncertainties.Notably,a real-time frequency regulation control method is proposed for the participation of PV and BESSs in automatic generation control(AGC).This is particularly relevant given the uncertainty of grid frequency fluctuations in the optimization model of the real-time balancing market.This control method dynamically assigns the frequency regulation amount undertaken by the PV and BESSs according to the control interval in which the area control error(ACE)occurs.The case study results demonstrate that the proposed bidding strategy not only enables the PV and BESSs to effectively participate in the grid frequency regulation response but also yields considerable carbon emission reduction benefits and effectively improves the system operation economy.

计及电池储能和抽水蓄能灵活性的电力系统优化调度方法

充分利用灵活性资源的调节能力可有效平抑新能源出力的波动,保证系统经济安全运行。提出一种计及电池储能和抽水蓄能灵活性的电力系统优化调度方法。在建立向上/向下灵活性需求模型的基础上,以调度能量成本、备用成本和灵活调节服务调用成本的总成本最小为目标,建立基于日前安全约束机组组合和实时经济再调度的混合整数线性规划模型,采用CPLEX进行求解。以IEEE-RTS-24节点系统为算例,考虑4种不同典型方案场景,对比验证了所提方法能有效提升系统运行灵活性,降低运行成本。

计及多点电池储能系统的电网二次调频协同控制

在“碳达峰•碳中和”国家能源战略变革背景下,大规模可再生能源的加速并网加剧了电力系统对于快速调频资源需求的迫切性,如何充分发挥以电池储能系统(battery energy storage systems,BESS)为代表的新型快速资源在电网调频中的作用是解决该问题的关键。首先,为满足电网各类型调频资源在自动发电控制(automatic generation control,AGC)系统中的接入监视与分类决策需求,提出“域-群-机”三级控制模型架构;然后,从BESS的荷电状态(state of charge,SOC)主动管理出发,提出基于改进的动态调频容量(dynamic available AGC,DAA)的多元集群协同控制策略,以及引入SOC影响因子的多点BESS功率分配策略;最后,结合实际电网的持续扰动工况及模拟跳机扰动工况进行仿真分析,验证了文中所提控制策略的有效性。文中所提策略不但可以显著改善各单点BESS的SOC一致性,而且能够提升电网调频品质。

Energy Management and Operational Control Methods for Grid Battery Energy Storage Systems

Energy storage is one of the key means for improving the flexibility,economy and security of power system.It is also important in promoting new energy consumption and the energy Internet.Therefore,energy storage is expected to support distributed power and the micro-grid,promote open sharing and flexible trading of energy production and consumption,and realize multi-functional coordination.In recent years,with the rapid development of the battery energy storage industry,its technology has shown the characteristics and trends for large-scale integration and distributed applications with multi-objective collaboration.As a grid-level application,energy management systems(EMS)of a battery energy storage system(BESS)were deployed in real time at utility control centers as an important component of power grid management.Based on the analysis of the development status of a BESS,this paper introduced application scenarios,such as reduction of power output fluctuations,agreement to the output plan at the renewable energy generation side,power grid frequency adjustment,power flow optimization at the power transmission side,and a distributed and niohile energy storage system at the power distribution side.The studies and application status of a BESS in recent years were reviewed.The energy management,operation control methods,and application scenes of large-scale BESSs were also examined in the study.

Aggregator Service for PV and Battery Energy Storage Systems of Residential Building

Distributed energy resources(DERs),including photovoltaic(PV)systems,small wind turbines,and energy storage systems(ESSs)are being increasingly installed in many residential units and the industry sector at large.DER installations in apartment buildings,however,pose a more complex issue particularly in the context of property ownership and the distribution of DR benefits.In this paper,a novel aggregator service is proposed to provide centralized management services for residents and DER asset owners in apartment buildings.The proposed service consists of a business model for billing and benefits distribution,and a model predictive control(MPC)control algorithm for managing and optimizing DER operations.Both physical and communication structures are proposed to ensure the implementation of such aggregator services for buildings.Three billing tariffs,i.e.,flat rate,time-of-use(TOU),and real time pricing(RTP)are compared by way of case studies.The results indicate that the proposed aggregator service is compatible with the business model.It is shown to offer good performance in load shifting,bill savings,and energy trading of DERs.Overall,the aggregator service is expected to provide benefits in reducing the pay back periods of the investment.

A Fuzzy Hierarchical Strategy for Improving Frequency Regulation of Battery Energy Storage System

Battery energy storage systems(BESSs)can provide instantaneous support for frequency regulation(FR)because of their fast response characteristics.However,purely pursuing a better FR effect calls for continually rapid cycles of BESSs,which shortens their lifetime and deteriorates the operational economy.To coordinate the lifespan savings and the FR effect,this paper presents a control strategy for the FR of BESSs based on fuzzy logic and hierarchical controllers.The fuzzy logic controller improves the effect of FR by adjusting the charging/discharging power of the BESS with a higher response speed and precision based on the area control error(ACE)signal and the change rate of ACE in a non-linear way.Hierarchical controllers effectively reduce the life loss by optimizing the depth of discharge,which ensures that the state of charge(SOC)of BESS is always in the optimal operating range,and the total FR cost is the lowest at this time.The proposed method can achieve the optimal balance between ACE reduction and operational economy of BESS.The effectiveness of the proposed strategy is verified in a two-area power system.

Stochastic coordinated operation of wind and battery energy storage system considering battery degradation

Grid-scale battery energy storage systems(BESSs)are promising to solve multiple problems for future power systems.Due to the limited lifespan and high cost of BESS,there is a cost-benefit trade-off between battery effort and operational performance.Thus,we develop a battery degradation model to accurately represent the battery degradation and related cost during battery operation and cycling.A linearization method is proposed to transform the developed battery degradation model into the mixed integer linear programming(MILP)optimization problems.The battery degradation model is incorporated with a hybrid deterministic/stochastic look-ahead rolling optimization model of windBESS bidding and operation in the real-time electricity market.Simulation results show that the developed battery degradation model is able to effectively help to extend the battery cycle life and make more profits for wind-BESS.Moreover,the proposed rolling look-ahead operational optimization strategy can utilize the updated wind power forecast,thereby also increase the wind-BESS profit.

Economic Dispatch of Islanded Microgrid Considering a Cooperative Strategy Between Diesel Generator and Battery Energy Storage System

For the impact of intermittent resources' high penetration on the economic dispatch of islanded microgrid, a new economic dispatch method is presented to minimize the overall generating cost for islanded microgrid, considering a cooperative strategy between diesel generator(hereinafter referred to as DE) and battery energy storage system(BESS). The optimum economic operation range of DE and the optimal set-point between DE and BESS are presented in the cooperative dispatch strategy, in which BESS is used fully to enable DE in a lower cost and higher efficient way. The results are analyzed under various operation conditions and also prove the validity of the proposed method.