Distributed and Risk-averse ADP Algorithm for Stochastic Economic Dispatch of Power System with Multiple Offshore Wind Farms

With more and more offshore wind power being increasingly connected to power grids,fluctuations in offshore wind speeds result in risks of high operation costs.To mitigate this problem,a risk-averse stochastic economic dispatch(ED)model of power system with multiple offshore wind farms(OWFs)is proposed in this paper.In this model,a novel GlueVaR method is used to measure the tail risk of the probability distribution of operation cost.The weighted sum of the expected operation cost and the GlueVaR is used to reflect the risk of operation cost,which can consider different risk requirements including risk aversion and risk neutrality flexibly by adjusting parameters.Then,a risk-averse approximate dynamic programming(ADP)algorithm is designed for solving the proposed model,in which multi-period ED problem is decoupled into a series of single-period ED problems.Besides,GlueVaR is introduced into the approximate value function training process for risk aversion.Finally,a distributed and risk-averse ADP algorithm is constructed based on the alternating direction method of multipliers,which can further decouple single-period ED between transmission system and multiple OWFs for ensuring information privacy.Case studies on the modified IEEE 39-bus system with an OWF and an actual provincial power system with four OWFs demonstrate correctness and efficiency of the proposed model and algorithm.

Market-oriented Optimal Dispatching Strategy for a Wind Farm with a Multiple Stage Hybrid Energy Storage System

With the increased promotion of integrated energy power systems(IEPS),renewable energy and energy storage systems(ESS)play a more important role.However,the fluctuation and intermittent nature of wind not only results in substantial reliability and stability defects,but it also weakens the competitiveness of wind generation in the electric power market.Meanwhile,the way to further enhance the system reliability effectively improving market profits of wind farms is one of the most important aspects of Wind-ESS joint operational design.In this paper,a market-oriented optimized dispatching strategy for a wind farm with a multiple stage hybrid ESS is proposed.The first stage ESS is designed to improve the profits of wind generation through day-ahead market operations,the real-time marketbased second stage ESS is focused on day-ahead forecasting error elimination and wind power fluctuation smoothing,while the backup stage ESS is associated with them to provide the ancillary service.An interval forecasting method is adopted to help to ensure reliable forecast results of day-ahead wind power,electricity prices and loads.With this hybrid ESS design,supply reliability and market profits are simultaneously achieved for wind farms.

Optimal Decomposition of Stochastic Dispatch Schedule for Renewable Energy Cluster

The correlated renewable energy farms are usually aggregated as a cluster in economic dispatch to relieve computational burden.This strategy can also achieve better performance since the precision of predicting the power generation of a cluster can be higher than those of individual farms.This paper proposes an optimal decomposition method to allocate dispatch schedules among renewable energy farms(REFs)in the cluster under existing stochastic optimization framework.The proposed model takes advantage of probabilistic characteristics of renewable generation to minimize the curtailment and ensure the feasibility of dispatch schedule of the clusters.Approximated tractable formulation and efficient solution method are the proposed to solve the proposed model.Numerical tests show that the proposed method achieves the optimal decomposition of dispatch schedule among REFs and facilitates the utilization of renewable generation.

A Storage and Transmission Joint Planning Method for Centralized Wind Power Transmission

Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuration of transmission capacity,which has the features of low utilization and poor economy,is hardly matching correctly due to the volatility and low energy density of wind.The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity,but facing the issue of energy storage cost recovery.Therefore,it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission.This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage,reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission.Then,analyze the multi-functional cost-sharing mode of energy storage,improve the efficiency of energy storage cost recovery.Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage,and realizes the transmission capacity optimization coordination and optimization with energy storage.The proposed method is verified by a wind base located in Northeast China.

新能源电力系统不确定优化调度方法研究现状及展望

风电场和光伏电站出力的不确定性给电力系统优化调度带来很大技术挑战。文中主要介绍了考虑新能源不确定性的电力系统优化调度方法的研究现状及后续研究方向展望。首先,重点论述了各种不确定优化调度(UOD)方法,包括随机优化方法、鲁棒优化方法、随机鲁棒优化结合方法和基于人工智能技术的方法。其中,随机优化方法包括场景法、机会约束规划法和近似动态规划法;鲁棒优化方法包括传统鲁棒优化法和分布鲁棒优化法;随机鲁棒优化结合方法包括采样鲁棒优化法和分布鲁棒机会约束规划法。然后,介绍了每一种方法的优化模型形式、模型的转化和求解原理及其优缺点。最后,对UOD的后续重点研究方向进行展望,包括兼顾多个目标的UOD问题及多目标不确定优化方法、输配系统UOD问题及分布式不确定优化方法、考虑稳定性约束的UOD问题及含常微分方程约束的不确定优化方法、考虑管道传输动态的综合能源系统UOD问题及含偏微分方程约束的不确定优化方法。

改进MOGOA及其在风储容量优化配置中的应用

针对传统方法在风储容量优化配置过程中求解精度低、效率低等问题,提出一种改进多目标蝗虫优化算法(improved multi-objective grasshopper optimization algorithm,IMOGOA),采用Fuch混沌映射、余弦自适应参数和莱维飞行三种策略进行改进,使算法的初始解分布更均匀、全局探索和局部开发更协调,同时增强了算法跳出局部最优的能力。对改进算法和多目标粒子群等多个算法进行性能测试对比,实验结果表明改进算法具有更好的寻优精度和稳定性。将该算法应用于风电场混合储能系统容量优化配置,对比其他算法,改进算法能够快速找出Pareto最优解集,在满足系统要求的同时,最大限度降低混合储能系统成本,可以验证算法改进策略的有效性和应用于实际优化问题的适用性。

含整体煤气化燃料电池-碳捕集电厂的风火储系统分布鲁棒调度方法

整体煤气化燃料电池(integrated gasification fuel cell,IGFC)是与碳捕集技术高度适配的清洁、高效、稳定的绿色煤电技术,有望克服传统碳捕集技术在低浓度CO_(2)环境下产生的高成本、高能耗问题。该文构建含IGFC碳捕集电厂的风火储发电系统。研究IGFC碳捕集电厂的运行机理,对IGFC内部各环节建立数学模型,提出工况匹配时燃烧利用率和阴极空气利用率需要满足的运行条件,并针对该型碳捕集电厂的电碳特性进行分析。为计及风电出力的不确定性,构建风火储系统的两阶段分布鲁棒经济调度模型,引入k阶适应性理论,提出基于正交支撑子集策略的求解方法来获得鲁棒对等式。最后,在改进IEEE-30节点系统中进行算例分析,结果表明,该型碳捕集电厂可利用阳极碳富集的优势,实现系统低碳经济调度的目标,并验证所提优化方法能为可行解提供可解释性。

考虑市场影响的风电厂与储能运营商联合调度策略研究

本文基于拥有风力发电厂与电力储能设备的电力运营商视角,考虑运营商参与电力交易会对市场电价产生影响的基础上,通过动态规划,以利润最大化为目标,研究其最优联合调度策略。研究表明:在考虑充放电效率以及运营成本时,存在三个最优参考点将储能设备中的可用库存空间分为四个区域,进而对应四个不同的决策活动:将风电和从市场上购买的电力全部存入储能系统;将部分风电存入储能系统并将剩余部分销售到市场;售出全部风电不向储能设备中存入电量;将所有的风电和储能系统中的部分电量销售至电力市场。运营商可根据当前时刻风力发电量和储能设备中的电量与最优参考点之间的大小关系,得到相应的最优电力调度策略及其交易量。此外,本文研究发现随着市场影响强度的增大,运营商的利润随之减小,因此运营商应在其市场影响强度与最优电力交易量之间做好权衡。本研究对运营商的电力调度具有重要的指导意义和实际应用价值。

基于衍生搜索政治优化算法解决含可再生能源的多区域经济调度问题

随着可再生能源并入多区域电力系统,其不确定性大大增加了电力系统多区域经济调度的复杂度。如何高效求解含有风力和太阳能的多区域经济调度(multi-areaeconomic dispatch containing wind and solar energy,MAEDWS)问题面临着严峻的挑战。针对现有优化算法在处理MAEDWS问题时存在收敛速度慢和求解精度低等不足,该文提出一种基于衍生搜索的政治优化(derivative search-based political optimizer,DSPO)算法。在政治优化算法的基础上,引入首脑引领策略和衍生搜索机制。前者引领候选解前往更有希望的区域,加快收敛速度;后者在区域获胜者周围衍生邻域解,丰富多样性。该文将DSPO算法和其他6种代表性算法应用于MAEDWS问题,并进行对比分析。收敛曲线和性能指标的结果表明DSPO算法在收敛效率、求解精确度、稳定性方面取得了整体最优。

海上风氢系统与沿海电网能量协同优化调度

为实现海上风电的高效消纳和绿色氢能的制备,提出一种海上风氢系统与沿海电网能量协同优化调度方法。首先,通过评估海上风电场间的风能耦合效应,建立考虑风能异域强化利用的风电场群发电转移模型。其次,量化分析风电场的疲劳载荷与疲劳成本之间的关系,构建考虑检修便利性的风电场群均衡载荷模型。基于此,提出风电场群综合效能调控模型,以协调发电与疲劳寿命之间的关系。然后,考虑海上风流因素对船舶航行时间的影响,建立电氢并举的能量外送模型。最后,以系统运行成本最小为目标,提出考虑主动孤岛、制氢效率特性以及系统旋转备用的海上风氢系统与沿海电网能量协同优化调度模型。算例验证了所提方法的有效性和优越性,为海上风电制氢能量调度提供了一种新的思路。

风光火储联合供应火电厂厂用电系统优化调度

随着风电和光伏发电量逐年增长,其消纳问题日益凸显。同时,大容量火电机组厂用电负荷也相对较高,造成额外的运行成本。对此,基于多能互补思想,建立了一种风光火储联合供应火电厂厂用电优化调度模型。首先,提出了风光火储联合供应火电厂厂用电的组成结构,将风电、光伏发电优先供应厂用电负荷;其次构建了风光火储联合供应火电厂厂用电优化调度模型,考虑了火电机组不同负荷率下的运行成本和风光储成本,采用层次分析法建立了基于总成本、弃风弃光成本和环境成本的多目标函数,设置相应约束条件;最后,设置不同的场景对比分析联合供应厂用电系统的优化结果,试验结果表明:所提出的联合供应厂用电系统模型可以减少机组运行成本和环境成本,并促进风光消纳。

基于储能和无功优化的直驱机组海上风电场低电压穿越策略

针对直驱永磁机组海上风电场中的低电压穿越问题,提出了一种基于储能和无功优化的控制方案。采用锂电池作为分散式储能设备,吸收故障时刻直流母线上的多余功率,抑制电网故障时机组直流侧电压上升。同时根据各台机组的不同运行状况分配不同的无功指令,选取网侧变流器输出的有功功率、直流母线电压、机端电压作为评价指标,依据评价指标结果对风电场中各台风电机组低电压穿越能力进行评估,优化控制各台机组的无功出力,从而有效提高整个风电场的无功输出能力。以某海上风电场为例进行仿真分析,仿真结果表明了该方案能显著提高风电场低电压穿越能力。

沿海区域综合能源生产单元随机优化调度

为实现沿海区域的海上风电场、海上采气平台和陆上热电联供燃气电厂等多种能源生产子单元的协同化运行,考虑可再生能源出力和氢负荷的随机波动,提出沿海区域综合能源生产单元(coastal integrated energy production units,CIEPU)随机优化调度模型。采用参数化代价函数近似(parametric cost function approximation,PCFA)的动态规划算法求解随机优化调度模型。通过一种基于梯度下降的求解方法--Adadelta法,获得策略函数的一阶信息,并计算梯度平方的指数衰减平均值,以更新策略函数的迭代步长;对随机优化调度模型进行策略参数逼近,从而得到近似最优的策略参数,并逐一时段求解出CIEPU的最优调度计划。最后,以某个CIEPU为例,分析计算结果表明,所提出方法获得的优化调度方案可以提高CIEPU运行的经济性并降低碳排放量,验证了所提方法的准确性和高效性。

基于Copula-Shuffle方法的风光互补制氢合成绿色甲醇系统两阶段随机优化

为实现“双碳”目标,推进氢能多领域应用,设计一种风光互补制氢合成绿色甲醇系统,提出面向电化工(P2X)系统的Copula-Shuffle风光出力不确定性与相关性调度场景生成方法。基于所提系统内各设备运行特性,以净收益最大为适应度函数建立两阶段随机优化模型并进行仿真分析。结果表明,所提系统经过设计调度优化后,利用电解槽启停待调度及氢储能灵活调控,主动平抑风光不稳定输出,满足绿色甲醇合成设备的柔性变负荷调节与连续生产约束,实现各设备间的深度协同运行。所提系统可充分消纳新能源电力,具有初步盈利能力,研究成果可为绿色甲醇产业提供一定的指导。

考虑场间功率时移的海上风电场群联合储能优化调度方法

相邻海上风电场间因尾流效应产生功率时移能力,可为海上风电场群参与电网有功优化调度提供有效支撑。提出一种考虑场间功率时移的海上风电场群联合储能优化调度方法。首先,基于海上风电场群功率预测与电网有功调度计划量化风电场群功率跟踪需求;计及风速传播时间建立场间功率时移模型,利用风电场间功率时移能力参与电网调度;针对出力偏差协调储能进一步跟踪调度计划。然后,以系统运行成本最小为目标,构建考虑场间功率时移的海上风电场群储能优化调度模型。最后,以某实际海上风电场群储能系统为例进行仿真验证,结果表明所提方法能够利用相邻海上风电场间功率时移能力,有效降低储能调用成本,实现海上风电场群对电网有功调度计划的跟踪。

基于多目标原子轨道搜索算法的风电场集群最优经济调度

随着环保意识的增强以及风电渗透率的不断攀升,使得电力部门对含风电系统的经济调度提出了更高的要求。为了在降低污染物排放及促进风电消纳的同时将发电成本控制在最低,建立了考虑环境与经济指标的风-火多随机变量经济调度模型。该模型中的目标函数考虑了火力发电成本、风力发电成本、弃风惩罚成本及污染气体排放。采用多目标原子轨道搜索算法进行模型求解,该算法在传统原子轨道搜索算法的基础上添加了存档机制、网络机制以及领导者选择机制,具有较强的多目标优化执行能力。结合修改后的IEEE30节点算例进行仿真分析,结果验证了所提模型的可行性以及多目标原子轨道搜索算法求解此类问题的有效性。

基于多阶段双重博弈的多园区随机场景低碳分布式调度优化

多园区综合能源系统在碳交易机制下存在多主体交互问题,保障信息隐私的基础上协调园区多场景下利益分配冲突,是实现综合能源系统低碳发展的关键。该文通过分析碳交易和绿证交易原理,构建运营商与多园区的绿证-碳排放联动双层交易框架。利用Stackelberg博弈理论建立中间运营商与多园区间领导跟随关系,制定上级购售电价引导园区制定机组出力计划。在此基础上,结合Nash博弈理论,实现多园区智能体间议价合作博弈,以保证多园区间收益与公平分配。随后,基于随机场景法与条件风险价值理论,提出一种多阶段双重博弈的多园区随机场景低碳分布式调度优化方法,并将改进交替方向乘子法与差分进化法相结合,解耦不同园区系统,实现分布式求解,保护各参与主体隐私同时提升收敛速度。最后,通过搭建多园区综合能源系统进行仿真,验证所提调度方法在新能源多场景下可优化园区利益矛盾,有效提升多园区整体效益,降低碳排放。

水风光综合基地多风险量化及长期多目标协调优化调度方法

水风光一体化运行可以发挥多种能源优势,提高综合效益。风光能源大规模并入水电基地,因不确定性增加致使系统能源消纳和电力供应问题更加突出,将面临更高弃水和缺电风险。针对该问题,提出了一种评估各时段蓄水状态的风险量化方法。基于该方法构建了考虑弃水量、发电量、弃水风险和缺电风险的多目标调度模型,基于双层优化,采用动态规划、离散微分动态规划和逐步优化相结合的算法进行高效求解,将分层序列法与线性加权和法嵌入算法中,以协调多目标矛盾。最后,以中国某水风光综合基地为工程背景模拟调度,并将所提模型与传统模型进行对比验证。研究结果表明,所提模型能较好地刻画运行风险,通过调整水电运行方式能合理消纳新能源,并获得更高稳定收益;模型能以较高效率完成求解,并满足实际调度时效性要求;在实际场景与预测场景出现偏差时,能显著降低弃水损失,通过改变水电运行方式以适应新能源日益增长带来的运行风险。

Optimized dispatch of wind farms with power control capability for power system restoration

As the power control technology of wind farms develops,the output power of wind farms can be constant,which makes it possible for wind farms to participate in power system restoration.However,due to the uncertainty of wind energy,the actual output power can’t reach a constant dispatch power in all time intervals,resulting in uncertain power sags which may induce the frequency of the system being restored to go outside the security limits.Therefore,it is necessary to optimize the dispatch of wind farms participating in power system restoration.Considering that the probability distribution function(PDF)oftransient power sags is hard to obtain,a robust optimization model is proposed in this paper,which can maximize the output power of wind farms participating in power system restoration.Simulation results demonstrate that the security constraints of the restored system can be kept within security limits when wind farm dispatch is optimized by the proposed method.

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.