计及动态一致性风险度量的水电短期优化调度

发电量的多期投标组合是一个动态的优化问题,决策过程中常常呈现多期风险,因而对风险的度量也应该是动态的。条件风险价值(conditional value at risk,CVaR)是一种静态一致性风险度量,不适用于对发电量的时间分解进行多期风险评估。该文提出一种动态一致性风险度量,考虑风险对未来投资收益波动的长期影响,将分位数作用于静态一致性风险度量来表征多期风险的动态特征,并采用分位数回归的方法,以各期CVaR的绝对偏差加权和最小为目标函数建立数学模型,该模型可同时应用于计及风险的发电量时间分解和空间分配计算。以水电厂短期优化调度为例,说明该风险度量指标的可行性和实用性。     

考虑开关动作次数的多时段配电网动态重构

通过配电网重构来降低网损是一种经济可靠的手段.一方面,鲜有文献研究如何在降低网损同时减少开关的动作次数;另一方面,目前大多数重构模型的求解算法难以保证全局最优解.提出一种基于二阶锥的多时段动态重构方法.以开关状态量为优化变量,以降低网损为优化目标,建立配电网多时段动态重构模型;将重构问题转化为混合整数二阶锥规划问题,采用二阶锥方法对所建模型进行求解,得到配电网最优动态拓扑.在此基础上,通过合并相似的开关状态,从而避免网架结构的频繁改变.通过IEEE33配电系统进行仿真,结果验证了所提方法的有效性与优越性.     

最小化运行费用的时变重构全局优化算法

该文提出了一种以运行费用最小为目标的时变重构全局优化算法。将时变重构问题分解为多个静态重构子问题，使用核心模式遗传最短路算法(CSGSA)分别求解每个子问题，得出候选放射状网络结构，并使用动态规划，根据各子问题的结果求解全局最优的时变重构策略。算法还对开关操作次数约束进行了处理，使之不影响动态规划的全局最优性。所提算法是配电网络实时调度，规划和离线分析的有效工具。     

Truck route planning in nonstationary stochastic networks with time windows at customer locations

Most existing methods for truck route planning assume known static data in an environment that is time varying and uncertain by nature, which limits their widespread applicability. The development of intelligent transportation systems such as the use of information technologies reduces the level of uncertainties and makes the use of more appropriate dynamic formulations and solutions feasible. In this paper, a truck route planning problem called stochastic traveling salesman problem with time windows (STSPTW) in which traveling times along roads and service times at customer locations are stochastic processes is investigated. A methodology is developed to estimate the truck arrival time at each customer location. Using estimated arrival times, an approximate solution method based on dynamic programming is proposed. The algorithm finds the best route with minimum expected cost while it guarantees certain levels of service are met. Simulation results are used to demonstrate the efficiency of the proposed algorithm.     

A dynamic model for coordination of generation and transmission expansion planning in power systems

This paper presents a new dynamic approach on the expansion planning problem in power systems. First, the coordination between generation system expansion and transmission system expansion has been formulated as a mixed integer nonlinear programming (MINLP) problem. Then, it has been shown that this MINLP model cannot be efficiently solved by the traditional MINLP solvers. Since the nonlinear term comes from the multiplication of a binary variable by a continuous one, a Benders decomposition approach has been employed to convert the MINLP formulation into a mixed integer linear programming (MILP) master problem, and a linear programming (LP) sub-problem. Besides, different times of construction have been considered for different transmission and generation facilities. In addition, a clustering based algorithm has been proposed to evaluate the reliability of the system at hierarchical level II (HLII). Since this dynamic planning method is an upgraded version of a recent developed static model, the result from both methods have been also compared. A simple 6-bus test system and IEEE 30-bus system have been selected to confirm the effectiveness of the introduced method.     

变电站扩容和电池储能系统容量配置的协调规划方法

充分考虑电池储能系统（BESS）的充放电效益对变电站扩容建设的推迟作用,建立了变电站扩容建设和BESS容量配置的协调规划模型。新模型基于一个含风电场的典型地区配电网络及其日负荷曲线,考虑了购电费用和BESS与变电站扩容的综合投资运行费用目标,同时还考虑了BESS的充放电特点和网络的安全约束。其中对于变电站扩容容量包含给定待选与连续可调两种情况。该模型是一个多时段非线性规划问题,在变电站扩容容量为给定待选的情况下还包含整数变量,需将其转换为含互补约束条件的连续优化问题,再采用原对偶解耦内点法将其解耦为单时段优化问题进行协调迭代求解。算例结果表明该方法可以有效减小电网的扩容投资,并实现储能系统容量的优化配置。     

Generation expansion planning in electricity markets: A novel framework based on dynamic stochastic MPEC

This paper presents a novel framework for generation expansion planning (GEP) of restructured power systems under uncertainty in a multi-period horizon, which includes generation investment from a price maker perspective. The investment problem is modeled as a bi-level optimization problem. The first level problem includes decisions related to investment in order to maximize total profit in the planning horizon. The second level problem consists of maximizing social welfare where the power market is cleared. Rival uncertainties on offering and investment are modeled using sets of scenarios. The bi-level optimization problem is then converted to a dynamic stochastic MPEC and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a typical six-bus power network, MAZANDARAN regional electric company (MREC) transmission network as an area of IRAN interconnected power system and IEEE RTS 24-bus network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the behavior of investments in electricity markets.     

自储能柔性互联配电网多时间尺度电压优化

为解决高渗透率分布式电源引起的电压越限问题,计及慢速调节设备特性和储能荷电状态的时序连续性,提出了自储能柔性互联配电网多时间尺度电压优化模型.日前优化求解慢速调节设备挡位并给出储能日内运行的功率限制区间,日内优化以此为基础求得各时段储能及柔直端口优化出力.基于电压越限检测实时调节各端口出力,以缩短过/欠电压持续时间.针对多时段耦合的混合整数非凸、非线性优化模型,提出了一种双层求解算法,上层利用动态规划法处理储能全时段优化与慢速调节设备的整数规划问题,下层利用多面体松弛技术改进二阶锥规划算法提高求解效率.最后,通过实际算例验证了所提模型和求解方法的有效性.     

基于半动态拓扑优化的电网运行方式辅助决策

网络拓扑优化作为一种新技术,通过在电网运行过程中改变网络结构来改善系统潮流分布,提升系统运行安全经济性。文中针对现有静态与动态网络拓扑优化方法分别存在的灵活性差与计算效率低的问题,提出了一种折中的半动态拓扑优化方法,进而基于该方法进行电力系统运行方式的辅助决策。首先,介绍了当前静态与动态两类网络拓扑优化方法的优缺点,进而提出了半动态网络拓扑优化方法;其次,基于静态、动态与半动态3类网络拓扑优化方法,构建了一般形式的电网运行方式辅助决策模型,进而运用线性化技术,将所提模型转化为混合整数线性规划问题;最后,对IEEE 14节点及IEEE 118节点系统进行计算分析,说明了所提半动态网络拓扑优化方法能够兼顾系统运行灵活性与模型解算效率。     

考虑电压稳定约束的无功规划研究综述

随着电力市场进程的加快,系统运行不断逼近极限,电压稳定已成为影响系统安全的焦点问题,而合理的无功规划对保持系统电压稳定具有重要意义。首先解释了考虑电压稳定约束的无功规划基本概念,接着对目前基于静态和动态电压稳定约束的无功规划模型和求解方法进行总结与评述,提出了该领域需要深入研究的五个关键问题,强调了考虑安全性和经济性的无功规划是当前该领域的发展趋势,最后指出了建立基于动态电压稳定裕度的无功规划模型是避免系统电压崩溃的关键。     

Application of linear programming redispatch technique to dynamicgeneration allocation

Consideration is given to dispatch problems that involve the allocation of system generation optimally among generating units while tracking a load curve and observing the power rate limits of the units, system spinning reserve requirements, and other security constraints. Two methods are used in the solution of the problem. The first method is a quadratic programming technique combined with a linear programming redispatch technique. The latter utilizes a linear programming formulation of the dynamic dispatch problem about the base case static economic dispatch solution. The second method is based on the Dantzig-Wolfe decomposition technique. Tests and computer results of four systems of different combinations of units and intervals are given to show the advantages of the techniques proposed     

电动汽车充电站多阶段选址规划

电动汽车充电站作为电动汽车运营所需的配套设施,其建设时间、位置与规模对电动汽车的推广有着重要意义。现有研究将电动汽车充电站的规划选址作为一个静态规划问题处理,忽视了电动汽车充电站的建设时间,因此提出了一种电动汽车充电站选址的多阶段规划模型,并应用伪动态规划的思想求解该模型。首先提出了一种计及电动汽车充电站投资成本、运行维护成本以及用户充电损耗费用的多阶段规划模型;其次在准确预测各阶段充电需求的基础上,通过遗传算法确定规划期末的规划方案;最后通过动态规划逆序解法获得各阶段的规划方案,算例分析验证该方案的优越性。     

动态输电网络规划的组合编码遗传算法

针对动态输电网络规划过程中需要考虑时间决策量的问题,提出了组合编码方式。组合编码方式将多阶段输电网络规划中的时间决策量隐含在编码中,从而使得多阶段的动态输电网络规划问题能够转换成静态规划问题进行求解。该编码方式满足表现型和基因型的1对1映射,及表现型空间与基因型空间距离上的一致性,从而保证了遗传算法的搜索效率。此外,针对动态输电网络规划的特点,对遗传算法的交叉算子、变异方式、适应度函数、惩罚系数等方面进行了改进,进一步改善了遗传算法求解多阶段输电网络规划问题的性能。以19节点系统为例对算法进行了验证,结果表明能够在较短的进化代数内得到问题的最优解。     

电力系统多时段无功电压控制的两阶段优化法

为减少无功电压控制设备的动作次数,提出了一种多时段无功电压控制的两阶段优化方法。第1阶段建立以有功损耗最小为目标的各时段静态无功优化模型,应用改进的遗传算法求解可以获得调度周期内每一时段的多组优化解,以此构成控制设备寻优的状态空间;第2阶段应用动态规划法寻求整个调度周期内控制设备状态转移的最短路径,从而可兼顾系统有功损耗、电压质量与设备动作次数的综合优化效果。此外,该方法易于实现并行处理。算例表明,该方法优化效果好,具有在线应用前景。     

Dynamic transmission planning under uncertainty

A new approximate method is presented to solve the dynamic optimization problem in long-range transmission capacity expansion planning. The method employs a static optimization technique along with an iterative procedure to simulate the dynamic solution.The proposed method can be simplified to provide a fast technique, also discussed in the paper. Comparison is made between the fast technique and the conventional horizon year planning approach.     

基于二阶锥规划的交直流混合配电网优化调度

针对交直流混合配电网优化调度中控制变量多样化的趋势,以网损费用和弃光费用之和最小作为目标函数,综合考虑分布式电源、储能装置、电压源换流器、电容器组和静止无功补偿装置等控制变量集合,建立交直流混合主动配电网有功-无功多时段协同优化新模型,解决电压越限问题,实现功率快速补偿。针对变量维数增加引起的模型最优解精确性问题,采用二阶锥规划对非凸非线性问题松弛凸化,利用Cplex算法求得模型最优解。最后,通过拓展的49节点系统算例测试结果验证所提模型的有效性。     

Fast computation of Q‐value‐based dynamic programming on road networks

One of the essential components of vehicle navigation systems is route planning. The single shortest path problem and multiple shortest path problem have been widely studied for route planning. This paper introduces a Q‐value‐based dynamic programming using the division concept for solving both single and multiple shortest path problems on road networks. The proposed algorithm divides the whole network into different divisions, and the updating of Q values in each division is one stage for searching the optimal routes on road networks. The proposed algorithm can greatly save the computational time without any preprocessing on the road networks. The proposed algorithm is also systematically studied in various sizes of road networks. The simulation results show the efficiency and effectiveness of the proposed algorithm on large‐scale road networks. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

一种实用的配电网无功运行两层优化方法研究

针对多时段动态无功优化,将控制设备动作次数转化成设备调节费用并将其计入目标函数,建立以全天网损费用与设备调节费用之和最小为目标函数的优化模型。将Fisher有序聚类算法引入到负荷曲线分段问题中,使分段后的负荷曲线尽可能贴近实际负荷水平。提出一种基于改进遗传算法和准动态规划法的两层优化算法,以获取全天控制设备的动作方案,实现多时段的协调优化。为兼顾算法的寻优速度和搜索精度,可依据电网规模灵活设置各阶段保留的最优路径数,适合于大规模系统的动态无功优化。算例表明了所提方法的实用和有效。     

计及控制设备动作次数约束的三阶段动态无功优化算法

为了避免控制设备频繁操作,动态无功优化模型需考虑无功补偿装置投切开关及变压器抽头的允许动作次数约束。但是,动态无功优化属于大规模、多时段、强耦合的混合整数非线性规划问题,对其直接求解是困难的。建立了以有功网损最小为目标函数的动态无功优化模型,并提出一种实用的三阶段动态无功优化算法,该算法的核心是一种具有多项式计算复杂度的前推-回推式动态规划算法。将计及控制设备动作次数约束的动态无功优化问题的求解分解为多个时间断面的连续无功优化计算、理想无功补偿装置无功补偿功率曲线和变压器变比曲线的阶梯化以及在确定各个时段的无功补偿容量和变压器变比情况下的连续无功优化计算3个阶段。对IEEE 30节点系统和某实际区域电网进行测试,结果验证了所提算法的合理性和实用性。     

Application of CVaR risk aversion approach in the expansion and operation planning and for setting the spot price in the Brazilian hydrothermal interconnected system

Traditionally, long-term power generation planning problems has been performed with the main objective of minimizing the expected value of generation and load curtailment costs. However, more recently there has been a need to apply some risk measure in order to avoid large amounts of load curtailment in critical inflow scenarios. This paper describes a direct approach for the implementation of a Conditional Value-at-Risk (CVaR) version for the long term hydrothermal coordination problem under a stochastic dual dynamic programming solving strategy. We also present an actual analysis that was made to validate and determine the key parameters of this model for a real application to the Brazilian system, where since September 2013 the proposed methodology has been officially used for operation planning and dispatch, to set the spot prices in the market and to perform expansion planning studies.