旋转备用对电网可靠性的影响及优化配置研究

旋转备用(Spinning Reserve,SR)的不同分配方案会导致不同的电网可靠性水平。从改善大电网运行可靠性的角度出发,综合考虑机组类型和爬坡速率、元件可靠性参数、网络拓扑结构以及传输容量限制等因素,将SR的优化分配纳入到最优负荷削减模型中。利用该模型不等式约束中控制参数的拉格朗日乘子的物理意义,推导出系统电力不足期望对各机组备用容量的灵敏度表达式,提出了根据该灵敏度结果进行备用优化配置的启发式思路。同时以SR成本与用户停电损失之和最小为目标,通过同步联合优化确定SR的总量与配置方案。RBTS测试系统的仿真结果表明了所提方法的有效性和正确性。     

基于备用安全的含风电场的电力系统经济调度

随着风电在电网中渗透功率的持续增加,风电的不确定性给系统的备用决策和发电调度带来新的难题。为保障含风电场电力系统的安全运行,本文结合风电预测误差的概率密度函数,提出了一种系统运行安全性指标——备用安全可信度,并以备用安全可信度最大化和火电机组运行费用最小化作为优化目标函数,建立了含风电场的电力系统经济调度模型。针对寻优效率,本文采用了一种将优先顺序法和内点法相结合的优化方法对机组组合问题求解。算例分析证明了所提模型和解法的可行性和合理性。     

Cost allocation of spinning reserve based on risk contribution

Current cost allocation methods require generating companies (GENCOs) to afford spinning reserve (SR) costs according to their energy production rather than the impact on grid stabilization. The differences in generator reliability and forecast accuracy of renewables cause difficulty in quantifying the contribution of individual factors on the SR requirements (SRRs). First, this paper employs a reliability‐constrained unit commitment (RCUC) model to determine the SRR and SR costs according to the grid reliability. Then, a cost allocation method is proposed to allocate these SR costs based on risk contribution theories. The risk contribution theories, marginal contribution, and stand‐alone contribution are employed to measure the effect of individual risk factors on grid safety. The cost allocation method is demonstrated and discussed in the IEEE‐RTS. The proposed risk contribution method can quantify the impacts of risk factors on grid safety and allocate SR costs into them according to their contributions. Additionally, this risk‐based cost allocation method can encourage GENCOs to enhance the reliability level of generators and continuously improve the forecast accuracy of renewables to lower SR costs. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

大规模可再生能源接入下的电力系统充裕性优化(一)旋转级备用的优化

大规模可再生能源接入需要及时响应的各级备用容量支撑,合理配置立即可用的旋转级发电侧和需求侧备用容量对平衡系统可靠性与经济性至关重要。建立有偿使用备用服务的市场机制,其基本任务是购入合适的备用容量,在满足潜在风险场景下调度需求的同时,降低系统总成本。这就要求:考察每个可选备用措施(RM)在风险场景下的备用价值;从中选取性价比较高的RM或其组合。三篇连载文章完成了场景集下多等级备用协调优化的具体建模与求解,作为连载的第一篇,文中在分析现有备用优化求解方法的基础上,提出了基于RM代价性能比的旋转级备用优化方法。以穷尽式寻优方法为精度基准,通过所提方法与混合整数线性规划方法的对比,验证了所提方法的有效性。同时通过算例,从效率和精度两个方面给出了所提优化方法在不同规模系统下的表现。     

Application of Cost-CVaR model in determining optimal spinning reserve for wind power penetrated system

Spinning reserve (SR) is an important resource for system operators (SO) to cope with unpredictable imbalances between load and generation, which is caused by load forecast errors and unexpected deviations of wind power. The increased installed capacity of wind power adds the difficulty to predict total amount of injected power accurately and increase risk of load loss and wind curtailment. In view of large wind power penetrated in system, the paper proposes a Cost-CVaR model to determine optimal reserve requirements in electricity market. CVaR is applied to evaluate the risk caused by the uncertainties of load and wind power forecast. Risk management tool is proposed to make a reasonable tradeoff between risks and profits at various risk levels. The model is tested on a regional grid in China. Then the proposed method is compared with probabilistic and deterministic method. The results demonstrate the usefulness and efficiency of the proposed method.     

考虑源荷协调的风电并网系统旋转备用容量优化

风电的接入给电力系统带来更大不确定性,要求电网公司购买更多的旋转备用以维持电力系统的功率平衡和稳定,兼顾系统运行可靠性与经济性的旋转备用优化配置具有重要意义。考虑风电、需求侧互动资源,提出一种基于多场景的概率性旋转备用优化方法。该方法综合考虑风电预测误差、负荷波动及发电机非计划停运不确定性因素对旋转备用的需求,将弃风、可中断负荷分别作为部分负、正旋转备用融入发电日前调度计划,以购电总费用最低为目标函数建立日前机组组合优化模型,获得各时段旋转备用优化配置量。通过对IEEE 30节点、IEEE 118节点系统进行算例分析,验证了所提方法的正确性和有效性。     

Optimal Scheduling of Spinning Reserve with Transmission Constraints

An effective method is proposed to schedule spinning reserve optimally. The method considers the transmission constraint in the whole scheduling process. To get the feasible solution faster, transmission line limits are first relaxed using the Lagrangian Relaxation technique. In the economic dispatch, after unit generation and spinning reserve are allocated among the committed units to satisfy the system andunit constraints, the schedule is then modified by a linear programming algorithm to avoid line overloads. The schedule is then updated by a probabilistic reserve assessment to meet a given risk index. The optimal value of the risk index is selected via a cost/benefit analysis based on the tradeoff between the total Unit Commitment (UC) schedule cost and the expected cost of energy not served. Finally, a unit decommitment technique is incorporated to solve the problem of reserve over-commitment in the Lagrangian Relaxation–based UC. The results of reserve scheduling with the transmission constraint are shown by the simulation runs performed on the IEEE reliability test system.     

考虑光-荷不确定性和旋转备用约束的主动配电网经济优化调度策略

分布式光伏、储能装置等大量分布式电源接入主动配电网(active distribution networks,ADN)后,光伏出力、负荷和旋转备用容量的多重不确定性对主动配电网经济调度的可靠性提出新的挑战。考虑了光伏出力及负荷不确定性,对旋转备用容量进行概率约束,以调度过程中运行成本最小为目标函数提出了一种主动配电网经济优化调度模型。通过所提出的潮流约束线性化方法和离散步长变换方法,将机会约束规划(chance constrained programming,CCP)模型转化为易于求解的确定性混合整数线性规划(mixed-integer linear programming,MILP)模型,并通过CPLEX求解器进行求解。基于IEEE-33节点配电网系统对所提方法进行验证。算例结果表明,所提策略的系统计算时间显著减少,优化效果更好,且可以通过适当设置旋转备用容量概率约束的置信水平实现主动配电网可靠性与经济性间平衡。     

Customer choice of reliability in spinning reserve procurement and cost allocation using well-being analysis

A novel pool-based market-clearing algorithm for spinning reserve (SR) procurement and the cost allocation associated with provision of spinning reserve among customers (DisCos) is developed in this paper. Rational buyer market model is used to clear energy and spinning reserve markets in the proposed algorithm. This market model gives DisCos the opportunity to declare their own energy requirement together with their desired reliability levels to the ISO and also they can participate in the SR market as a interruptible load. The DisCos’ desired reliability levels are selected from a hybrid deterministic/probabilistic framework designated as the system well-being model. Using the demand of each DisCo and its associated desired reliability level, the overall desired system reliability level is determined. The market operator then purchases spinning reserve commodity from the associated market such that the overall desired system reliability level is satisfied. A methodology is developed in this paper to fairly allocate the cost associated with providing spinning reserve among DisCos based on their demands and desired reliability levels. An algorithm is also presented in this paper for implementing the proposed approach. The effectiveness of the proposed technique is examined using the IEEE-RTS.     

多场景概率机组组合在含风电系统中的备用协调优化

备用配置是系统抵御风险、提高运行可靠性的重要手段,也是系统运行安全与经济协调决策的问题。提出了基于状态转移的概率机组组合方法,该方法将风电的运行场景离散化,通过对风电预测误差进行概率表达,并在时间尺度上考虑状态的转移矩阵组成多场景的方法,以场景发生的概率协调系统在场景下的调度决策,并以实时校正备用作为正常和误差场景之间机组的调整限制。通过安全与经济的协调,能够自动为风电出力的波动配置适宜的备用,且模型中考虑了网络安全约束对机组组合和备用决策的影响。最后对含风电系统进行了实例仿真分析,结果表明模型的有效性和可行性,对风电的调度和规划具有指导意义。     

考虑微网源荷不确定性的旋转备用容量优化

电力市场环境下,为应对微网源荷波动和可控机组随机故障,提升其供电可靠性,提出了一种考虑微网源荷不确定性的旋转备用容量优化方法。计及日前预测误差,采用序列理论对源荷随机概率性序列以及可控机组随机故障序列进行离散化处理,生成微网综合不确定性离散分布模型;在此基础上,以微网运行成本、备用成本和停电损失的总成本最小为目标函数,建立旋转备用容量优化模型,并结合蒙特卡罗与粒子群算法对该模型进行求解,获得各时段的旋转备用优化配置容量。以某地微网系统为例,仿真验证了所提方法的有效性和合理性。     

电力市场下综合考虑系统可靠性和旋转备用效益的机组组合

通过对电力市场条件下机组组合问题的研究，提出了综合考虑发电系统可靠性和旋转备用效益的机组组合的模型和方法。该方法以旋转备用的比较效益最大为目标函数，通过概率评估方法，利用系统投运风险度确定机组投运台数，利用系统响应风险度确定旋转备用的合理分布，并提出了一种求解以上问题的启发式求解算法，给出了算例及结果。     

考虑需求响应与风电不确定性的两阶段鲁棒旋转备用容量优化模型

以风电为代表的新能源大规模并网威胁到了传统电力系统的稳定运行,对备用容量的配置也有了新的要求。在新电改和能源需求侧改革的背景下,用户侧的需求响应（demand response,DR）资源在备用容量配置的问题上凭借其灵活性和可操作性越来越得到重视。为此,文章分别从基于价格和激励的需求响应参与备用容量优化角度,提出了以调度成本和备用成本最小为目标函数的两阶段鲁棒优化模型。利用列和约束生成（columa and constraint generation, C&CG）算法将其分解为考虑风电不确定性的日前备用容量优化配置主问题和实时备用电量分配子问题,运用AD算法计算子问题并寻找“最坏点”代入到主问题中进行迭代求解,提高了求解效率。算例结果验证了模型的有效性和正确性,并表明需求响应作为一种灵活的调控资源可以有效促进风电消纳,同时可以降低系统调度成本和备用成本。     

基于系统频率响应特征的电网广义旋转备用优化配置

现有的旋转备用配置方法多将旋转备用的来源限定于常规发电机组,较少虑及储能装置与柔性负荷等新兴电力设施对旋转备用优化配置的积极影响。为此,文中提出了电网广义旋转备用的概念;借助序列化建模思路与可描述随机变量取值相依结构的Copula函数,建立电网等效负荷(电网原始负荷与对应时刻点新能源发电出力的差值)波动量与预测偏差模型;综合考虑系统频率响应特征,以电网广义旋转备用购置成本、停电损失成本与弃新能源发电成本最低为目标,提出一种基于系统频率响应的新能源高渗透电网广义旋转备用优化配置方法。以新疆某新能源高渗透区域电网实际运行数据为依据,仿真验证了所提方法的可行性。     

Cost assessment of efficiency losses in hydroelectric plants

Some important real-time tasks of the independent system operator (ISO) are the monitoring and control of power system events (load deviations and contingencies). These events are usually managed by the ISO using operating reserve ancillary services. These services represent an additional capacity (MW) available in generators and some interruptible loads. Generators must change their operating points in order that this capacity can remain available. These changes might lead to efficiency losses in energy production. In systems with a high percentage of hydroelectric production, hydroelectric plants need to know the impact of ancillary services on their profits. This work therefore analyzes the cost of efficiency losses due to operating reserve availability in hydroelectric generators. A method to calculate this cost component is proposed using a unit commitment dispatch for a single hydroelectric plant. This dispatch is performed without considering the operating reserve availability and is compared with the traditional dispatch, which takes into account the availability of operating reserve. The proposal is used to calculate the cost of efficiency losses on a Brazilian hydroelectric generator. We found that the cost of efficiency losses can be considerable when compared to the incomes of a hydroelectric plant in the short-term market.     

基于条件风险价值的含风电电力系统旋转备用效益研究

由于风电出力的波动性和间歇性,大规模风电并网使得旋转备用效益和风险的矛盾更加突出。考虑系统上、下旋转备用的容量成本和能量成本,以及因购买上旋转备用而减少的失负荷损失和因购买下旋转备用而减少的弃风损失,以期望旋转备用效益最大和系统损失的条件风险价值(CVaR)最小为两个目标,建立基于条件风险价值的含风电电力系统旋转备用效益-风险模型。采用蒙特卡罗法模拟实际负荷功率和风电出力的预测偏差,并改进多目标粒子群优化算法,用于求解得到期望旋转备用效益-风险有效前沿和日前旋转备用计划,以及不同可靠性水平、置信水平对期望旋转备用效益和风险的影响。最后,通过算例验证了该模型和算法的可行性。     

考虑可中断负荷的风电接入系统旋转备用双层优化方法

风电接入规模的不断扩大加大了电力系统的波动,使得电网需要配置更多的旋转备用(spinning reserve,SR)抑制电力系统波动与电网等效负荷预测偏差,传统以固定比例配置常规机组旋转备用容量的方法经济性差且未考虑系统内其他资源。考虑辅助服务市场进一步开放以及可中断负荷特性,将可中断负荷与常规机组一同参与辅助服务市场,文章提出了一种考虑可中断负荷的旋转备用双层优化方法。该方法以时间为尺度,上层优化日前协议签订的容量成本,下层优化日内实时调用成本,构建优化总期望成本的双层优化目标函数,基于序列化建模思想将系统等效负荷预测偏差离散化得出相应决策期望值,通过商用软件CPLEX求解目标函数获得各时段可中断负荷与常规机组最优备用容量。最后以新疆某地区实际运行数据进行算例分析,验证所提方法的可行性。     

电力市场中的备用需求和备用调度

确定性方法和概率性方法是 2种不同的确定备用需求容量的方法 ,2种方法相比 ,概率性方法能够更好地反映系统的可靠性 ,确定的备用容量更为合理。在分析概率性方法的基本原理的基础上 ,结合电力市场对几种确定备用需求的概率性方法 ,进一步提出了一种以用户要求作为可靠性风险指标的确定备用容量的方法。对于最优化备用需求所带来的新的策略竞价问题 ,较好的一个方法是对系统中非计划停机采取惩罚 。     

基于加权半方差的含风电电力系统旋转备用效益研究

在考虑系统旋转备用的容量成本和能量成本、因购买旋转备用而减少的停电损失,以及旋转备用效益的离散程度的基础上,引入风险偏好系数,并采用证券投资组合中的加权半方差度量风险。以期望旋转备用效益最大和风险最小为优化目标,建立基于加权半方差的含风电电力系统旋转备用效益-风险模型。采用蒙特卡洛模拟法模拟实际负荷功率偏差和风电出力预测偏差,并通过多目标纵横交叉算法求得期望旋转备用效益-风险有效前沿和日前旋转备用计划,以及风险偏好系数、可靠性水平、预测偏差、失负荷损失价格、旋转备用价格对期望旋转备用效益和风险的影响。算例验证了所提模型的合理性。     

Multi-period wind integrated optimal dispatch using series PSO-DE with time-varying Gaussian membership function based fuzzy selection

Wind power has emerged as the most promising option for providing sustainable eco-friendly power supply to the modern world. Due to its unpredictable nature, integration of wind power into the conventional power grid is a very challenging task having dynamic characteristics. Due to the inherent uncertainty associated with wind availability, additional spinning reserve needs to be scheduled in order to maintain security and supply reliability. Multi-period multi-objective optimal dispatch (MPMOOD) is presented for wind integrated power system with reserve constraints. The complex relationship between wind power availability, spinning reserve allocation and their impact on economic/environmental cost are analysed using an elaborate model.A new multi-objective Series PSO-DE (SPSO-DE) hybrid algorithm is proposed where the two paradigms, differential evolution (DE) and particle swarm optimization (PSO) share domain information and maintain a synergistic cooperation to overcome their individual weaknesses. For multi-objective (MO) problems, the selection operation in SPSO-DE is replaced by a 5-class time-varying fuzzy selection mechanism (TVFSM) to avoid saturation and to increase Pareto diversity. To promote convergence towards the central part of the Pareto front and to quickly isolate the boundary solutions, Guassian membership function is employed. Elitism is applied to preserve good solutions and momentum operation is used to stop premature convergence. The proposed method expedites the search for the best solution, i.e. the solution which satisfies all the objectives of the MO problems. To test the performance and computational efficiency, the proposed method is applied on two standard test power systems.