Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Optimal configuration for photovoltaic storage system capacity in 5G base station microgrids

Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.

Energy Management and Capacity Optimization of Photovoltaic, Energy Storage System, Flexible Building Power System Considering Combined Benefit

Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions.Hence,to balance the interests of the environment and the building users,this paper proposes an optimal operation scheme for the photovoltaic,energy storage system,and flexible building power system(PEFB),considering the combined benefit of building.Based on the model of conventional photovoltaic(PV)and energy storage system(ESS),the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy,society,and environment as the optimization objective,taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints.The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’costs and the combined benefits of the building.The efficiency and effectiveness of the proposed methods are verified by simulated experiments.

Optimal Configuration for Design of Stand-Alone PV System

This paper presents a design for a stand-alone photovoltaic (PV) system to provide the required electricity for a single residential household in rural area in Jordan. The complete design steps for the suggested household loads are carried out. Site radiation data and the electrical load data of a typical household in the considered site are taken into account during the design steps. The reliability of the system is quantified by the loss of load probability. A computer program is developed to simulate the PV system behavior and to numerically find an optimal combination of PV array and battery bank for the design of stand-alone photovoltaic systems in terms of reliability and costs. The program calculates life cycle cost and annualized unit electrical cost. Simulations results showed that a value of loss of load probability LLP can be met by several combinations of PV array and battery storage. The method developed here uniquely determines the optimum configuration that meets the load demand with the minimum cost. The difference between the costs of these combinations is very large. The optimal unit electrical cost of 1 kWh for LLP = 0.049 is $0.293;while for LLP 0.0027 it is $0.402. The results of the study encouraged the use of the PV systems to electrify the remote sites in Jordan.

Multifunction Battery Energy Storage System for Distribution Networks

Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity price.In this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley filling.The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes.For determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a year.In addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s performances.The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone.The simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming language.The Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.

基于EnergyPlus和Jeplus+EA联合模拟的建筑围护结构及光储系统协同优化研究

建筑本体和可再生能源系统的协同作用对于降低建筑碳排放具有重要意义.以北京某办公建筑为例,基于NSGA-Ⅱ的优化算法,以运行阶段碳排放和生命周期成本为目标函数,以热舒适为约束条件,利用EnergyPlus和Jeplus+EA软件进行联合仿真,开展建筑围护结构和光储系统的协同优化研究.结果表明:配置光储系统可较大程度降低建筑电网购电量及运行阶段碳排放,虽然生命周期成本会略有增加,但其减碳效果,大于单纯依靠围护结构性能提升的传统做法;尽可能利用建筑空间配置光伏对减少碳排放及生命周期成本都是有利的;通过软件联合模拟可实现建筑围护结构和光储系统的协同优化,且较于各自独立优化,能取得更好的设计方案.

Optimal Sizing of Solar/Wind Hybrid Off-Grid Microgrids Using an Enhanced Genetic Algorithm

This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic Algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.

考虑负电价的建筑储能控制策略与优化配置设计方法

在双碳战略背景下,清洁能源已经成为城市能源供应的重要组成部分,与此同时建筑再电气化率也在不断提高,为了应对新形势下的能源供需平衡,我国电力市场不断完善,然而新市场规则带来的负电价现象,对建筑能源系统工程设计和运维带来了极大的挑战。本文以建筑光储系统为研究对象,考虑负电价情况,提出新市场机制下系统调度策略与容量配置方法,并通过Matlab进行模拟仿真,验证了该方法的有效性。

计及储能电池寿命衰减的居民小区光储优化配置

在居民小区配置光伏系统可减小电力系统的供电压力,配置储能装置能够减小光伏弃光率,同时还可以实现负荷的时空转移,减小负荷峰谷差。为使居民小区光储系统的配置更加合理,利用充放电次数和放电深度对储能电池寿命的影响,通过改进曲线拟合方法及线性分段处理方法,获得更加准确的曲线拟合函数和与原曲线更加贴合的分段线性函数,建立储能电池动态损耗模型;以光储系统年均净收益最大和负荷峰谷差最小为目标函数,对光储系统进行优化配置;最后使用不同权重求解方法得到光伏出力值及负荷需求值,采用多目标粒子群算法对在不同运行场景下的居民小区光储系统配置问题进行求解,并通过仿真对比分析不同运行场景下光储系统的运行策略。结果表明,居民小区储能系统在并网场景下的经济性和削峰填谷效果更佳,所采用模型合理有效,可为居民小区光储系统的规划建设提供参考。

提升光储充电站运行效率的多目标优化配置策略

光储充电站的运行效率直接影响到其经济效益及电网侧的电能质量。针对在进行容量配置时对运行效率考虑不足会导致非必要的电能损耗,文中提出一种提升光储充电站运行效率的多目标优化配置策略。通过分析光储充电站变换器与内源线路功率损耗对于运行效率的影响,提出充电站的运行效率评估指标与计算方法,并讨论光储充电站运行效率对其容量配置的影响。建立以充电站经济效益、运行效率、电网侧峰谷供电功率补偿能力最佳为优化目标的多目标容量优化配置策略。针对优化目标特性,提出一种改进二代非支配排序遗传算法得到优化策略求解方法。选取中国西南地区某典型光储充电站运营场景,通过算例验证了优化策略的有效性与优越性。

海上油气平台不稳定电源与储能联合配置优化策略

针对海上油气平台集群接入不稳定电源与储能的联合配置问题,结合海上风电、光伏特点及已有的拓扑结构,提出了三阶段风机/光伏/储能阶段式联合配置策略,介绍嵌入潮流计算的阶段式粒子群算法。第一阶段通过LightGBM网络预测模型得到风机光伏的时序预测发电功率,再以投资建设经济性和潮流稳定性为目标优化每个节点的风机/光伏容量;第二阶段针对不稳定电源配置后的配电网,提出了基于电压和损耗灵敏度为指标的集群划分方法,将配电网集群划分为若干个子集群;第三阶段根据划分后的子集群,以储能容量、配电网损耗和节点电压波动为目标为每个子集群内配置储能。以渤海油田某10 kV实际油气平台配电网为例,设立燃气机出力功率自定义和经济性自定义两种方案来验证联合配置优化决策的合理性。结果表明,两种配置策略都可以有效地提升海上油气平台配电网的潮流稳定性,提高新能源的渗透率。本文研究验证了海上分散式风机/光伏发电工程的可行性,有利于实现未来海上油气平台的“零碳”建设。

基于净能力及二阶锥规划的分布式光储多场景协同优化策略

针对现有配电网中分布式光储调度模型存在资源协同不足、求解复杂等问题,提出了一种基于净能力及二阶锥规划的分布式光储多场景协同优化调度策略。通过引入储能接入配电网后的功率转移分布因子,提出一种基于系统净能力的储能最优选址计算方法;综合考虑储能的运行特性和分布式光伏的出力不确定性,建立以系统日综合成本和削峰填谷为目标的分布式光储多场景协同优化调度模型;利用二阶锥松弛和Big-M法对潮流约束、储能运行约束进行处理,将原规划模型转化为混合整数二阶锥规划问题。以IEEE 33节点系统和西北某实际系统为算例进行仿真分析,结果表明所提方法能在降低负荷峰谷差和日综合成本、平抑负荷波动的同时,显著提高对分布式光伏的消纳能力,验证了所提方法的有效性和可行性。

含高比例光伏配电网中计及需求侧响应的混合储能配置优化

大力发展光伏等可再生能源是我国实现“双碳”目标的重要途径,而光伏高比例接入配电网后随之带来一系列问题。以含高比例光伏配电网为研究对象,提出了计及用户侧需求响应的混合储能优化配置方法。针对负荷和光伏出力的双重不确定性,提出了基于预测误差概率分布的不确定性场景确定方法。考虑系统不确定性,统筹运行阶段用户侧需求响应调控措施以及潮流约束,提出了储能配置的3层优化模型。针对优化模型提出了相应的分解方法,以及基于列和约束生成算法的求解实施流程。通过在IEEE-33节点测试系统中的应用,使得系统可平移负荷峰值下降了10%,节点电压维持在合理范围,并在指导储能配置等方面具备显著的应用效果。通过分析光伏比例灵敏性可知,不含光伏情况下的储能总容量相比100%光伏比例场景增加了90%。

基于时序运行模拟的水火风光储互补系统电源优化配置

系统时序运行模拟是水火风光储互补系统电源规模优化配置的关键环节。对于水火风光储多能互补系统8760逐小时运行模拟,按照小时尺度构建的模型规模很大,直接求解困难。本文提出按时间尺度逐层分解、递进优化的高效求解算法,精确模拟系统全年逐小时调度运行过程。在此基础上,构建双层规划模型对由风电、光伏、水电、火电、抽水蓄能、梯级水电站混合式抽水蓄能和电化学储能等电源组成的并网多能互补系统的电源容量进行优化配置。将模型应用在青海省电网系统中,对风电、光伏、抽水蓄能电站和基于水电站的可逆机组容量进行优化,得到电源最佳配置方案。

计及电能质量影响的主动配电网光储容量优化

“双碳”目标的提出,配电网新能源接入已成必然,光储并网配置将成为影响配电网电能质量的关键因素之一。该文建立一种计及电能质量影响的主动配电网光储双层优化配置模型,下层调度模型采用基于二阶锥规划的最优潮流模型,以系统网损最低为目标对各主动管理措施和分布式电源出力进行调度;上层配置模型以发电系统年投资运行成本、各光伏并网点电能质量评估值、系统总弃光率和储能收益为目标进行优化,采用向量序优化理论进行求解,保证计算结果的快速性和准确性。采用IEEE-33节点系统进行算例分析,结果表明计及电能质量影响开展主动配电网光储容量优化,可以保证电网运行经济性的同时尽可能提升电网的电能质量,对于新型主动配电网规划建设可提供重要的理论支撑。

新能源大基地风光储容量协调优化配置

大型新能源基地需要协调配置风光火储容量以满足外送要求,其中火电容量及外送通道的容量通常预先确定,从而风电、光伏、储能的容量配置成为影响新能源外送效果的重要因素。为此,针对大型新能源基地,研究了风光储容量优化配置问题,提出了基于新能源外送可靠性的容量配置方法。基于需求侧的负荷曲线,提出了一种聚类方法来优化直流通道的计划传输功率;基于直流计划功率,提出了衡量新能源外送可靠性的送电置信概率指标;基于送电置信概率等约束,构建了风光储容量优化配置的基本规划模型。为了进一步保证在不同的场景下新能源能可靠外送,在基本规划模型的基础上加入场景分布不确定性,提出了风光储容量配置的分布鲁棒规划模型。考虑到分布鲁棒约束包含整数变量,提出了一种迭代算法用于该分布鲁棒规划模型的求解。实际算例验证了所提方法的有效性。

计及混合储能寿命损耗的光伏功率平抑策略

针对光伏大规模并网产生的功率波动问题,提出了一种计及混合储能寿命损耗的光伏并网功率平抑策略。该策略根据光伏功率与并网功率波动允许范围的关系确定混合储能动作状态及功率指令,实现了光伏并网功率波动的平抑;然后建立了关于混合储能系统功率协调控制的多目标优化模型,并利用带精英策略的快速非支配排序遗传算法求解该模型;最后对平抑及功率协调控制进行了仿真验证。与传统平抑策略相比,所提策略在实现光伏并网功率波动平抑的基础上,有效降低了混合储能系统的寿命损耗与运行损耗。

计及共享储能与光伏的园区多用户综合收益优化

针对含共享储能与户用光伏的园区场景,文中提出一种用户侧综合收益双层优化方法,充分挖掘共享储能灵活性及用户用电需求差异性,在实现用户整体经济效益最优的同时提升光伏消纳能力。模型上层为月前优化阶段,以用户月度用电成本最低为目标,考虑系统能量平衡、储能充放电约束以及储能荷电状态约束,优化工业用户最大用电功率,降低需量电费;模型下层为日前优化阶段,综合考虑用户综合收益及光伏消纳能力,以上层优化结果为约束条件,兼顾功率、储能等约束,提出共享储能充放电功率及用户与电网交互功率等日前优化策略,在用户月度整体经济性最优的前提下,实现用户侧每日经济效益的优化。最后,以南方某实际园区作为算例验证了文中所提方法的有效性。

光储系统并网功率波动平抑及储能优化配置

【目的】电池储能是保证光伏发电系统可靠性、提高光伏发电利用率的有效手段之一,但在光储电站中存在功率波动平抑难、储能容量配置不合理等问题,为解决这些问题,开展了相关研究。【方法】针对能量型电池储能,分析了调度模式和自主模式特性,提出了一种基于储能运行在调度模式的光储系统限功率平抑策略,以实现功率平抑和减少储能充放电频繁切换。建立了以最小光储系统弃电损失为优化目标,以功率波动越限概率等作为约束条件的优化模型,并利用算法对储能配置进行求解和优化。以西藏朗明桑珠孜50 MW光储电站为例,验证了所提平抑策略的有效性。【结果】所提平抑策略在不增加储能充放电切换次数的前提下,将光储系统并网功率波动越限概率由25.64%降至6.41%,且并网功率波动越限概率为5%时,该50 MW并网光伏电站储能系统最优配置为14.5 MW/94 MW·h。【结论】所提抑策略及储能优化配置方法可为并网光储电站优化设计和运行提供技术参考。