A coordinated dispatching strategy for wind power rapid ramp events in power systems with high wind power penetration

High wind power penetration poses a challenge for the dispatch of the power system when rapid ramp events occur. This paper proposes an optimal dispatching strategy against wind power rapid ramp events during peak load periods by coordinating generation units with different time intervals. Special attention is given to the definition of the wind power rapid ramp events considering operation conditions of the system. Then, the online prediction of wind power rapid ramp events and its influence on the spinning reserve procurement of the system is analyzed. Based on the principle of coordination among generation units with different time intervals, the optimal dispatch during peak load periods when wind power rapid ramp events occur is formulated as an optimization problem considering thermal generation units, the energy storage system, interruptible load and load shedding. To improve computational efficiency, the power output calculation of the generation units with different time intervals is decomposed. The results show that the proposed dispatching strategy is feasible for accommodating wind power rapid ramp events during peak load periods.     

Corrective economic dispatch in a microgrid

In this paper, a corrective economic dispatch problem formulation for distributed generators in a microgrid is presented, which considers the transition from grid‐connected operation to islanded operation. Various constraints related to the operation of a microgrid are modeled, such as spinning reserve requirement for the variation of load demand and the output of intermittent sources, the flow limits between the control areas, and ramping limits of distributed generators. The resulting problem is then solved by an interior point method. Numerical tests based on a three‐area ten‐unit microgrid system show the effects of these constraints on the generation cost. Copyright © 2012 John Wiley & Sons, Ltd.     

协同电网安全性与经济性的新能源优先实时调度方法及应用

电网实时调度介于日内小时级滚动调度和秒级自动发电控制(AGC)之间,是在线调度过程中承上启下的重要环节。对新能源高占比电网,实时调度是提高电网实时调节能力和应对新能源陡升/陡降等强波动性的重要手段。实时调度本质上是带多重约束的多目标优化问题,需要兼顾多种实际需求,在基本不需要人工干预的条件下,分别以5 min和15 min为调度周期,在线自动、高可靠地给出可行合理的优化策略。文中提出一种安全性和经济性协同的新能源优先实时调度方法,采用多阶段推进决策,实现了不同场景下不同调度目标的协调,兼顾了消除断面拥塞、最大化消纳新能源、传统机组间出力公平分配、AGC备用容量可行等不同的调度需求。基于所提出的方法,开发了实时调度系统并在多个省级电网投运,实际运行结果证明了该方法的有效性。     

A new approach to security-constrained generation scheduling of large-scale power systems with a piecewise linear ramping model

This paper presents a new and efficient approach to determine security-constrained generation scheduling (SCGS) in large-scale power systems, taking into account dispatch, network, and security constraints in pre and post-contingency states. A novel ramp rate limit is also modeled as a piecewise linear function in the SCGS problem to reflect more practical characteristics of the generating units. Benders decomposition is applied to this constrained solution process to obtain an optimal SCGS problem based on mixed-integer nonlinear programming (MINLP). The formulation can be embedded in two stages. First, a MIP is formulated in the master problem to solve a unit commitment (UC) problem. This stage determines appropriate on/off states of the units. The second stage, the subproblem, is formulated as a NLP to solve a security-constrained economic dispatch (SCED) problem. This stage is used to determine the feasibility of the master problem solution. It provides information to formulate the benders cuts that connect both problems. The proposed approach is tested in the IEEE 118-bus system to show its effectiveness. The simulation results are more realistic and feasible, whilst assuring an acceptable computation time.     

Combined environmental and economic dispatch of smart grids using distributed model predictive control

This paper presents an extended distributed model predictive control (DMPC) framework and its application to a smart grid case study. Specifically, a combined environmental and economic dispatch (EED) problem is formulated and solved, which is a non-trivial multi-objective optimization problem given the high number of agents, information exchanges and constraints associated to large-scale smart grids.In this line, the work proposed herein adopts a distributed Lagrange-based model predictive control with reduced computational demand making use of robust mixed-integer quadratic programming (MIQP) solvers. In addition, the model predictive control (MPC) nature of the framework accounts for renewable resource forecast while physical constraints are included in the formulation. The DMPC is herein extended to calculate market-based on-line energy pricing while minimizing the generation cost and emissions,and to include hard and soft constraints and ramp rate limits.The aforementioned control framework is applied to a smart grid composed of 11 consumer centers, 6 energy storages, 11 generation systems and 31 transmission lines. Simulation results show reductions of generation costs up to 40% when predictions are included in the formulation. Furthermore, the simulation of forecast errors results in up to 8% generation overcost. These results show that DMPC can be considered as an alternative versus other heuristic methods, which do not guarantee an optimal solution to the problem.     

基于局部随机搜索粒子群优化算法的电站短期发电优化调度

为提高粒子群优化(PSO)算法搜索精度、加快后期收敛速度,提出一种新的PSO算法,即局部随机搜索PSO算法。该算法用于求解电力系统的短期发电优化调度问题时,不仅要求满足电站实际运行中的系统负荷平衡约束,而且要考虑机组爬坡约束、出力限制区约束等非线性约束。给出了局部随机搜索PSO算法的步骤及短期发电优化调度问题求解方法。通过应用所提出的算法和其他文献提出的PSO算法、改进快速进化规划(IFEP)算法对15机系统的优化调度计算相比,证明所提出的算法最优解的发电费用最低,分别减少了3.8%和1%。     

基于改进两阶段鲁棒优化的区域综合能源系统经济调度

针对光伏出力及负荷的不确定性对系统日前经济调度和实时运行的影响,提出了一种以期望场景下最优,任意场景下可行的改进两阶段鲁棒优化方法,解决经典两阶段鲁棒优化存在的保守性问题。建立一种考虑可再生能源和负荷波动的区域综合能源系统改进两阶段鲁棒优化经济调度模型,通过列约束生成算法将目标函数分解为主问题和子问题进行反复迭代求解。模型第一阶段(主问题)以日前经济调度成本为目标函数,制定出包含系统设备出力、天然气供气计划的日前调度方案。在此基础上,第二阶段(子问题)以实时运行下调整成本为目标函数,通过调整设备出力应对系统中不确定波动。最后,以冬季某区域综合能源系统进行算例仿真,验证模型的有效性。#$NL关键词：区域综合能源系统;不确定性;改进鲁棒优化;经济调度     

A new method of evaluating robust power system security against uncertainties

The rapid expansion of renewable energy (RE) generation is leading to severe problems related to the reliability of network operation. Power system security is threatened by increased uncertainties of RE outputs and reduced controllable resources. Therefore, it is important to evaluate the robustness of the system controllability in order to preserve system security against uncertainties of RE outputs. We refer to the robustness of the system in this context as ‘robust power system security’. This paper proposes a new formulation for evaluating the robust security region in controllable parameter space where the conventional N‐1 security criterion suffices in the presence of uncertainties. We specify the confidence interval (CI) of uncertain parameters and obtain the worst case feasible region defined by a set of security constraints, which is a very new approach in the treatment of uncertainties. We use the minimum set of static constraints in the load dispatching problem with CI of RE prediction to evaluate the security region, which is referred to as the robust static security region (RSS) in this paper. The proposed method is useful to assess the degree of difficulty of system planning and operation from the viewpoint of the balance between controllable generator capacity and RE uncertainties. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

光伏光热联合发电基地并网优化调度模型

太阳能能源基地建设正在从单一光伏发电向光伏光热等多种太阳能能源利用形式方向发展。借助光热电站的大容量储热装置和具备快速爬坡速率的汽轮机组,光伏光热联合发电基地的并网运行的可调度性和可控性大大提升。从光伏光热联合发电基地的运行机理出发,建立了基于改进粒子群算法的光伏光热两阶段优化调度模型,第一阶段以削减等效负荷峰谷差、改善负荷曲线为优化目标,第二阶段以发电总成本最小为优化目标。该模型满足光伏光热电站的主要运行约束和传统机组组合安全约束,适用于光伏光热联合发电基地并网调度运行。对10机系统的仿真表明,在完全接纳太阳能发电的前提下,光伏光热发电基地在削减等效峰谷差、提高新能源消纳和降低发电总煤耗效益显著,同时对于光热电站的灵敏度分析表明,在规划建设光热电站时可根据单位峰谷差削减量以及建设成本来选择合适的装机容量和储热装置容量。     

基于扩展序列运算的含不确定性需求响应电力系统优化调度

未来高比例可再生能源的随机性给电力系统运行带来了前所未有的挑战,灵活性资源的不足限制了可再生能源的发展,柔性负荷可作为一种灵活性资源参与电力系统的调峰和备用。文中根据响应机制的不同,将柔性负荷分为激励型负荷和价格型负荷两种。基于扩展概率性序列运算理论,分别建立表征激励型负荷和价格型负荷响应不确定性的概率模型,表征风电出力不确定性的概率模型也随之建立。在此基础上,以应对风电波动性和随机性为背景,基于风险约束和风险成本理论,构建了同时考虑风电出力和需求响应不确定性的电力系统日前优化调度模型。针对构建的随机优化问题,文中通过序列运算对机会约束条件进行转化,将其转化为一个约束条件为线性的确定性优化问题进行求解。最后,通过仿真算例验证了模型的有效性,并分析了序列运算应用于不确定性问题的实用价值。     

计及源网荷交互影响的区域电网热稳安全供电区间计算方法

新能源和负荷的不确定性与输电通道的潮流转移存在交互影响,区域电网供电能力呈现出强不确定性的特点。提出一种计及源网荷交互影响的区域电网热稳安全供电区间计算模型及其求解方法。采用安全供电区间来描述区域电网供电能力的分布范围,考虑新能源和负荷的不确定性,建立区域电网热稳安全供电区间的线性化模型。在输电通道安全运行约束中考虑可中断负荷参与调控的影响,挖掘区域电网的供电能力。实际电网的算例结果表明,不同源荷分布下的供电能力分布在一个较宽的范围,可中断负荷的分布和容量均对供电能力影响较大,验证了所提模型的正确性。     

考虑动态功能的抽水蓄能电站综合规划模型

以系统运行的经济性和可靠性为目标,提出了一种抽水蓄能电站的综合规划模型。该模型不仅考虑了系统需求约束、备用约束以及电站静态运行约束,而且考虑了能源约束、环保约束以及各类型电站的爬坡和旋转备用容量等动态运行约束。通过对规划方案进行静态运行模拟和动态特性模拟,得到抽水蓄能电站的动静态效益指标;基于综合效益比较,从拟定的方案中找出系统对抽水蓄能电站的最佳需求空间和装机进度。应用该方法对某省级系统进行了算例计算分析,结果表明了所述模型的有效性。     

Dynamic economic dispatch: feasible and optimal solutions

Dynamic economic dispatch is an extension of the conventional economic dispatch problem that takes into consideration the limits on the ramp rate of the generating units. This paper examines the factors that affect the feasibility and optimality of solutions to this problem. It proposes two new solution methods. The first is guaranteed to find a feasible solution even when the load profile is nonmonotonic. The second is an efficient technique for funding the optimal solution. The results obtained with these methods are compared with those obtained using previously published methods     

考虑N-1安全约束的含可再生能源输电网结构鲁棒优化

为提高大规模可再生能源接入系统的运行经济与安全性,提出在考虑可再生能源接入的电力系统中通过输电网络结构优化,在保证安全运行约束的前提下,降低系统运行成本,提高可再生能源的消纳比例。研究将该优化问题分为经济调度问题和N-1校验问题,两个问题交替求解。经济调度问题对输电网结构和机组出力进行优化;N-1检验问题以系统失负荷为优化目标,并考虑重合一条线路作为应急手段。两个问题均可建立为两阶段鲁棒优化模型,利用Benders对偶法求解。进一步提出了模型求解的加速方法,适应于工程实际应用。对IEEE 39节点系统的仿真验证了所提方法的可行性和有效性。     

一种用于机组组合问题的改进双重粒子群算法

为了更经济快速地解决机组组合问题,提出一种改进双重粒子群优化(particle swarm optimization,PSO)算法,包含离散部分和连续部分。离散PSO分时段优化机组的启停状态,在种群更新时加入了临界算子,改进了可行解的判别条件,各机组出力最低值的和要在一定程度上低于负荷需求值,并考虑机组启停时间的向前继承和向后约束。连续PSO用于启停状态确定过程中和确定后的负荷分配,考虑功率平衡约束、热备用约束和机组的出力上下限约束。求解经济负荷分配时,利用罚函数的方法满足机组的爬坡速率约束,最后得到煤耗最小值。采用2个24时段的算例进行仿真,实验结果表明新算法减少了搜索量,提高了收敛速度,并为机组组合问题提出了新思路。     

含抽蓄电站与新能源发电的柔性直流系统日前优化调度方法

多端柔性高压直流输电技术可实现大规模可再生能源发电的多点汇集送出,通过接入和调控抽水蓄能(以下简称"抽蓄")电站可进一步平抑可再生能源出力波动、匹配负荷侧需求.针对含新能源发电和抽蓄电站的多端柔性直流系统,采用生成场景集方法建立了考虑新能源发电出力不确定性的日前随机优化调度模型.该模型详细考虑了定速与可变速抽蓄机组运行约束和抽蓄电站库容约束,同时包含了计及柔性直流电网有功损耗的潮流约束.通过对柔性直流电网潮流约束二阶锥松弛,将所建立模型转换为以期望运行费用最小为目标的混合整数二阶锥规划问题,可求解获得日前优化调度方案.以中国张北柔性直流示范工程为例进行仿真分析,验证了所提方法的有效性.     

Development of optimization model for power system operation,outline of model design and verification of output

Osaka Gas Co., Ltd., jointly with NTT DATA Mathematical Systems Inc., has developed unit‐commitment model for optimizing dispatch of power generation units. Main purpose of this development is to simulate the future world of electric power system in accordance with national energy policy aiming to introduce large amount of renewable energy as well as vitalized cross‐border power exchange via PX market to enhance economically‐efficient power system operation. The model incorporates not only constraints of supply‐demand balance but also constraints of operating reserves, regulation reserves, maximum CO2‐emissions, etc.     

应用粒子群优化算法求解市场环境下的电力系统动态经济调度问题

在竞争性的电力市场环境下,为了获得最大化的社会利润,提出了基于竞价机制的动态经济调度模型,该模型综合考虑了发电机组的爬坡约束、输电线路的容量约束和污染气体排放量的约束。针对该模型,提出了一种新的求解方法:粒子群优化算法(PSO)。算例的结果表明,PSO算法能够有效地得到一个高性能的优化调度结果     

基于一致性理论的独立微电网分布式动态经济调度

独立微电网是提高可再生能源利用率的有效途径,动态经济调度是微电网系统运行的重要环节。文中给出了独立微电网动态经济调度模型,提出了一套基于一致性理论的分布式实现方法,各参与者依靠本地计算以及邻居间的少量信息交互实现系统优化。计算分为两个阶段:在第一阶段,各单元通过平均一致性算法获得全网信息,并以最大化利用可再生能源为目标预设可控负荷的用电计划;在第二阶段,各单元通过更新发电机或储能系统时段间的出力上下限,将原问题解耦为一系列单时段经济调度问题,再采用一致性牵引算法根据等微增率准则逐个计算每个时段的最优出力。通过仿真算例验证了所提模型与算法的有效性。     

考虑热网约束和碳交易的多区域综合能源系统优化调度

为了提高可再生能源消纳率及减少发电过程中碳排放对环境的污染,提出了一种考虑热网约束和碳交易的多区域综合能源系统优化调度模型。首先,通过热网管道和节点的基本方程描述热网系统,建立区域综合能源系统与热网耦合模型;其次,分析国内外两种碳交易机制的特点,建立以系统运行成本、碳交易成本和可再生能源消纳惩罚成本之和最小为目标函数的低碳经济调度模型;最后,以冬季某热网连接的多区域综合能源系统为例,采用混合整数线性规划对模型进行求解,分析2种碳交易机制对系统经济运行和碳排放的影响。结果表明,通过热网连接多个区域综合能源系统,能充分利用区域间负荷的互补特性,减少系统碳排放,提高可再生能源的消纳率。