Using integer programming to refine Lagrangian-based unitcommitment solutions

The authors develop a technique for refining the unit commitment obtained from solving the Lagrangian. Their model is a computer program with nonlinear constraints. It can be solved to optimality using the branch-and-bound technique. Numerical results indicate a significant improvement in the quality of the solution obtained     

基于区块链架构的电力业务交易数据隐私保护

能源互联网的建设使得电力网络愈加开放,网络信任风险日益加剧,亟须一种兼具隐私保护和监管功能的区块链交易方案,以保证能源互联网交易的安全性及可控性.为解决传统区块链应用模式难以同时兼顾交易数据隐藏和监管这2个方面的不足,提出了一种可监管的区块链交易隐私保护模型.该模型采用概率公钥加密算法实现区块链交易用户真实身份的隐藏;利用承诺方案和零知识证明技术实现交易金额的隐私保护;借助基于身份的加密体制实现监管者对区块链交易的监督,大幅降低了存储、计算和密钥管理压力.系统应用分析表明,所提出的方案具有简单和实用的特点,能够满足业务应用的要求.     

双链式区块链架构设计及其点对点交易优化决策实现

在开放的售电侧市场中,具有电能生产和消费双重特性的产消者开展灵活对等的点对点交易.针对单链式区块链无法同时满足产消者交易的网络安全校核与去中心化问题,提出一种交易链和电能链耦合运行的双链式区块链及其点对点交易决策模型.其中交易链(公有链)实现产消者自主博弈的点对点交易,以市场方式最大化各产消者之间的经济利益;电能链(联盟链)以网络潮流为约束,实现市场交易方案的安全校核和调整.基于以太坊区块链开发平台,搭建IEEE 14节点配电系统点对点交易仿真场景.仿真结果表明,所设计的双链式区块链比单链式具有更高的交易处理效率和性能,能实现产消者点对点自主交易,保证了交易方案的安全自动执行.     

Economic Consequences of Alternative Solution Methods for Centralized Unit Commitment in Day-Ahead Electricity Markets

Many wholesale electricity markets call on the independent system operator (ISO) to determine day-ahead schedules for generators based on a centralized unit commitment. Up until recently, the Lagrangian relaxation (LR) algorithm was the only practical means of solving an ISO-scale unit commitment problem, and it was the solution technique used by most ISOs. Johnson et al. [1] demonstrate, however, that equity, incentive, and efficiency issues will arise from use of LR solutions, because different commitments that are similar in terms of total system costs can result in different surpluses to individual units. Recent advances in computing capabilities and optimization algorithms now make solution of the mixed-integer programming (MIP) formulation by means of branch and bound (B&B) tractable, often with optimality gaps smaller than those of LR algorithms, which has led some ISOs to adopt B&B algorithms and others proposing to do so. With the move towards B&B, one obvious question is whether the use of MIP will eliminate or reduce the issues with LR raised by Johnson et al. Using actual market data from an ISO, we demonstrate that both LR and MIP solutions will suffer the same equity issues, unless the ISO unit commitment problems can be solved to complete optimality within the allotted timeframe-which is beyond current computational capabilities. Our results further demonstrate that the size of the payoff deviations are not monotone in the size of the optimality gap, meaning smaller optimality gaps from B&B will not necessarily mitigate the issues Johnson et al. raise. We show that the use of "make-whole" payments, which ensure units recover any startup and no-load costs not recovered by inframarginal energy rents, can help to reduce surplus volatility and differences to some extent.     

Multi-area generation scheduling algorithm with regionally distributed optimal power flow using alternating direction method

This paper calls attention to the core issue as to the multi-area generation scheduling algorithm in interconnected electric power systems. This algorithm consists in deciding upon on/off states of generating units and their power outputs to meet the demands of customers under the consideration of operational technical constraints and transmission networks while keeping the generation cost to a minimum. In treating the mixed integer nonlinear programming (MINLP) problem, the generalized Benders decomposition (GBD) is applied to simply decouple a primal problem into a unit commitment (UC) master problem and inter-temporal optimal power flow (OPF) sub-problems. Most prominent in this work is that the alternating direction method (ADM) is introduced to accomplish the regional decomposition that allows efficient distributed solutions of OPF. Especially, the proposed distributed scheme whose effectiveness is clearly illustrated on a numerical example can find the most economic dispatch schedule incorporated with power transactions on a short-term basis where utilities are less inclined to pool knowledge about their systems or to telemeter measured system and cost data to the common system operator and nevertheless the gains from trade such as economy interchange are vital as well.     

多区域电力联营体运行下的输电成本分配

在发电计划由电力联营体（Pool）集中调度的互联电力系统中，各区域负担的发电量及计划交换功率（SIP）水平是统一决定的。为了让联营体成员得到公平的成本回报及利益分配，有必要对不同的输电交易进行适当的输电运行成本分配。文中提出了将联营体内集中调度的计划交换功率水平分解成多个“一对一”的双边交易。双边交易的交易量及其相关的环流输电成本将用于成本回报和利益分配的计算。同时还提出了一种通过迭代多区域全交流最优潮流来解决成本分配问题的算法。最后通过一个算例来阐明该算法及其实现，并讨论系统参数如系统负荷及输电线容量变化所带来的影响。     

A decomposition approach to nonlinear multi-area generationscheduling with tie-line constraints using expert systems

The authors propose a rigorous method to treat multiarea generation scheduling with tie line limits. An expert system was used for obtaining the initial solution. As the generation scheduling problem involves unit commitment and economic dispatch, the method adopts an iterative procedure to deal with these two phases. The hourly load demand and the area power generation will cause the tie flows to change. To maintain the operation security in every area, the spinning reserve should comply with the area power generation rather than its load demand. After economic dispatch, it is necessary to adjust the unit commitment in each area for preserving the spinning reserve requirements. Heuristics were used to modify the generation unit combinations. The objective is to find an economic generation schedule for a multiarea system. The interchange transactions among areas represent the transportation problem, embedded within the nonlinear optimization process. The equivalent system concept is adopted, and the transmission losses are included in this study. A four-area system with each area consisting of 26 units was used to test the efficiency of the proposed algorithm     

电力市场中的委托交易及其数学模型

该文提出了电力市场委托交易的概念,并提出了在传输阻塞和机组故障2种情况下基于收益最大化的委托交易的2个数学模型。在这2个模型中,要求委托交易的收益应大于在电力市场中策略竞标的收益,同时考虑了委托交易公司效益、输电线路功率限制、整个电网的功率平衡和委托交易等因素的约束条件,给出了委托交易公司和委托交易等因素的约束条件,给出了委托交易公司和受委托交易公司的成本函数。在研究电力市场中策略性竞标的收益时提出了基于收益最大化的策略性竞标的数学模型,对于这些最大化目标问题,采用了动态编程算法。在这些算法基础上提出了最大化目标问题的解决方案,通过一个算例的仿真计算,证明了所提出的委托交易的2个数学模型的正确性和有效性。     

引入LEC寿命管理的汽包锅炉机组负荷分配优化

以煤耗最小为目标函数的优化方法,虽然燃料费用最为节省,但是由于参数波动大且频繁,对机组造成了更大的伤害。文中将寿命延长控制（LEC）概念引入机组负荷分配优化工作中,将汽包寿命损耗考虑到机组负荷分配的优化中,在电网负荷变动越来越剧烈的形势下,这种模型是一种更加符合电厂实际的调峰方案。在寻优过程中,引入随机微粒群算法,该算法适用于快速寻优,能在速度和精度上满足计算要求。计算结果表明,LEC寿命管理方法的结果比平均分配负荷方法每日节省1393元,而寿命损耗却不增加。     

Unit commitment using hybrid models: a comparative study for dynamic programming, expert system, fuzzy system and genetic algorithms

Hybrid models for solving unit commitment problem have been proposed in this paper. To incorporate the changes due to the addition of new constraints automatically, an expert system (ES) has been proposed. The ES combines both schedules of units to be committed based on any classical or traditional algorithms and the knowledge of experienced power system operators. A solution database, i.e. information contained in the previous schedule is used to facilitate the current solution process. The proposed ES receives the input, i.e. the unit commitment solutions from a fuzzy-neural network. The unit commitment solutions from the artificial neural network cannot offer good performance if the load patterns are dissimilar to those of the trained data. Hence, the load demands, i.e. the input to the fuzzy-neural network is considered as fuzzy variables. To take into account the uncertainty in load demands, a fuzzy decision making approach has also been developed to solve the unit commitment problem and to train the artificial neural network. Due to the mathematical complexity of traditional techniques for solving unit commitment problem and also to facilitate comparison genetic algorithm, a non-traditional optimization technique has also been proposed. To demonstrate the effectiveness of the models proposed, extensive studies have been performed for different power systems consisting of 10, 26 and 34 generating units. The generation cost obtained and the computational time required by the proposed model has been compared with the existing traditional techniques such as dynamic programming (DP), ES, fuzzy system (FS) and genetic algorithms (GA).     

基于DPoA共识机制的分布式电力交易信用激励

分布式能源发电容量较小,不适合参与传统的电力交易,且其出力的不确定性易造成交易违约。通过区块链技术中的联盟链构建了适合分布式源、荷进行点对点交易的社区型电力交易平台,提出一种委托权威证明(DPoA)共识机制对区块链节点进行信用评价与激励。构造了履约信用函数和验证奖励函数对链上节点的交易履约与交易验证情况进行量化评价,并依据节点信用评价结果建立了信用奖惩激励机制。通过分析10个分布式源、荷节点参与的电力交易过程表明:基于区块链技术构建的社区型电力交易平台,可发挥电力市场促进分布式清洁能源消纳的作用;基于DPoA的信用激励机制可激励分布式电力交易节点提高履约度,维护自身信用。     

A tabu search based hybrid optimization approach for a fuzzy modelled unit commitment problem

This article presents a solution model for the unit commitment problem (UCP) using fuzzy logic to address uncertainties in the problem. Hybrid tabu search (TS), particle swarm optimization (PSO) and sequential quadratic programming (SQP) technique (hybrid TS–PSO–SQP) is used to schedule the generating units based on the fuzzy logic decisions. The fitness function for the hybrid TS–PSO–SQP is formulated by combining the objective function of UCP and a penalty calculated from the fuzzy logic decisions. Fuzzy decisions are made based on the statistics of the load demand error and spinning reserve maintained at each hour. TS are used to solve the combinatorial sub-problem of the UCP. An improved random perturbation scheme and a simple method for generating initial feasible commitment schedule are proposed for the TS method. The non-linear programming sub-problem of the UCP is solved using the hybrid PSO–SQP technique. Simulation results on a practical Neyveli Thermal Power Station system (NTPS) in India and several example systems validate, the presented UCP model is reasonable by ensuring quality solution with sufficient level of spinning reserve throughout the scheduling horizon for secure operation of the system.     

考虑频率与区间联络线功率安全约束的两区互联电力系统机组组合

随着电源结构与电网形态的转变,互联电力系统频率时空分布特征日益显著,区域频率差异与区间联络线功率振荡增大,基于统一频率假设的频率安全约束机组组合方法不再适用。针对考虑频率时空分布特征的两区互联电力系统安全约束机组组合,推导区域频率与区间联络线功率闭式解,并基于闭式解的两项划分,推得区域频率最低点、最大变化率、准稳态值以及区间联络线功率振荡峰值、准稳态值等一系列解析安全量化指标。基于所得指标,构建考虑区域频率与区间联络线功率安全约束的机组组合模型。并根据调度模式与指标特点,提出兼顾区域能力保障与区间能力协调的两级两阶段迭代求解算法。结果表明,所得指标可准确描述两区互联电力系统的安全特征,所提模型和算法可有效保障两区互联电力系统机组组合方案的运行安全。     

Allocation of transmission losses to bilateral contracts in acompetitive environment

Under open access, market driven transactions have become the new independent decision variables defining the behavior of the power system. Understanding the impact of bilateral transactions on system losses is important to be able to allocate a loss component to each individual transaction and improve economic efficiency. The theory presented here is based on the argument that it is always possible to compute the exact loss allocation corresponding to an infinitesimal bilateral transaction. This leads to a set of governing differential equations whose solution yields the loss allocation for contracts of any size. Several examples illustrate the properties of both the proposed allocation equations and other methods, the dependence of the proposed solution on the path of integration, and a number of implementation issues     

A probabilistic approach to generation maintenance scheduler with network constraints

Most generating unit maintenance scheduling packages consider the preventive maintenance schedule of generating units over a one or two year operational planning period in order to minimize the total operating cost while satisfying system energy requirements and maintenance constraints. In a global maintenance scheduling problem, we propose to consider network constraints and generating unit outages in generation maintenance scheduling. The inclusion of network constraints in generating unit maintenance will increase the complexity of the problem, so we decompose the global generator scheduling problem into a master problem and sub-problems using Benders decomposition. At the first stage, a master problem is solved to determine a solution for maintenance schedule decision variables. In the second stage, sub-problems are solved to minimize operating costs while satisfying network constraints and generators’ forced outages. Benders cuts based on the solution of the sub-problem are introduced to the master problem for improving the existing solution. The iterative procedure continues until an optimal or near optimal solution is found.     

机组组合问题的仿射可调整鲁棒优化模型与算法

为了有效应对电力系统调度决策中的不确定因素,尤其是大规模间歇式能源并网所带来的不确定性,提出基于仿射可调整鲁棒优化理论的不确定机组组合求解方法。建立了不确定机组组合问题的仿射可调整鲁棒优化模型,利用线性决策规则建立决策变量与不确定参数之间的仿射关系,从而将两阶段问题转化为单个阶段优化问题,在此基础上,采用对偶理论将模型转化为可以直接求解的标准混合整数规划模型。通过标准算例测试,验证了该方法的有效性。     

Unbundling of transmission and ancillary services. I. Technicalissues

This paper presents derivations of basic formulae for computing the contributions of each economic transaction to the network power flows throughout the system in steady-state operation of interconnected electric power systems. It is shown that the net system power imbalance caused by each transaction can be obtained as a function of all transactions present on the system. In addition, formulae are proposed for calculating the contributions of every ancillary generation unit to each transaction. This generation is needed to balance the system in response to economic transactions. Formulae supporting this are based on reformulating the load flow problem in terms of distributed slack bus     

计及实时电量交易的售电公司日偏差电量考核优化模型

启动现货市场的目的是建立电力中长期交易和现货交易相结合的市场化电力电量平衡机制,而在市场运营机制不完善的建设初期,以日为结算期的短期考核机制有利于市场公平交易,稳定现货市场中的电力电量波动。为了更直观地体现短期偏差电量考核对售电公司收益及经营策略的影响,构建了计及日偏差电量考核机制的售电公司日前市场收益模型。基于实时市场购电和与储能电站电量交易,建立了以售电公司收益最大化为目标的日偏差电量考核优化模型。基于广东省2017年交易数据模拟典型日现货交易和实际用电情况,对比分析模型优化效果,并对统一出清价和单位考核成本及与储能电站的交易电价、正、负偏差量进行了敏感性分析。结果表明：该优化策略可明显提高售电公司收益;统一出清价、单位考核成本和向储能电站购电电价对额外成本影响最大,向储能电站售电电价对额外收益影响最大,正、负偏差量对售电公司整体收益影响最大。     

面向大规模中长期交易的事前电量安全分析机制设计

大规模中长期市场交易可能产生极端的电网运行方式,而事后安全校核直接调整电量交易结果会影响市场成员的生产计划,增加市场成员的生产经营风险。在交易过程提供前置的安全分析服务,引导市场成员不断修正中长期物理交易,对保障电力中长期市场的有序开展具有重要意义。文中设计了一种基于市场成员申报交易意愿的中长期电量安全分析机制。首先提出了集中式电量安全分析、极限电量计算的两步校核体系;然后建立了基于安全约束机组组合的优化分析模型;最后通过统筹电力电量平衡和电网安全的多时段优化计算,评估电量计划的可执行性,并量化后续电量可交易空间。基于省级电网实际数据的案例分析结果表明了该机制的有效性。     

计及N-k网络安全约束的二阶段鲁棒机组组合

为提高调度决策的安全性以增强其应对偶发线路故障扰动的能力,文中提出一种计及N-k网络安全约束的二阶段鲁棒机组组合模型。首先,介绍了2种当前研究中采用的N-k不确定集合,并对集合特点进行了阐述;其次,基于2种N-k不确定集合,构建了一般形式的二阶段鲁棒机组组合模型。其中,第一阶段为线路故障前的机组启停决策;第二阶段为观测到线路故障最坏情况下的经济调度决策。所提模型可采用列与约束生成(CCG)算法将第一阶段、第二阶段问题分别对应转化为主问题与子问题进行迭代求解,并且运用对偶原理和线性化技术,可将主问题与子问题均转化为混合整数线性规划(MILP)模型。最后,通过对IEEE 14节点及IEEE 118节点系统的测试分析,验证了所提模型的有效性。