发电厂热备用容量的优化分配和成本分析

在竞争的发电市场环境下，备用作为一种重要的辅助服务，其成本分析是一个急待解决的问题，对发电厂热备用容量进行优化分配和成本分析，采用电能收益和备用容量收益总和最大化的目标函数。解算方法首先是根据发电厂总的发电负荷约束获得机组的经济组合，其次是将负荷在各机组间进行经济分配实现热备用容量的优化分配，热备用容量的成本采用其机会成本等值，方法简单，计算结果符合工程实际，研究结果表明，发电厂在计及备用收益和满足发电机组最低出力约束的条件下开机台数越多总收益也越大；在给定的时段和相应的电能电价下，备用容量成本随发电厂出力的增加而增加，在给定的时段和相应的发电出力下，备用容量成本随电价的增加而有较大的增加。     

A new unit commitment method

This paper introduces a new unit commitment method based on a decommitment procedure for solving the power system resource scheduling problem. From an initial schedule of all available units committed over the study period, a `one-at-a-time' unit decommitment is accomplished by dynamic programming according to some specified economic criteria. The decommitment process continues until no further reduction in total cost is possible, or the unit schedules of two consecutive iterations over the time period remain unchanged without any violation of the spinning reserve constraint. Two criteria for decommiting a unit are introduced and described in detail. Comparisons of the proposed unit commitment method with the Lagrangian relaxation (LR) approach and Fred Lee's sequential unit commitment method (SUC) demonstrate the potential benefits of the proposed approach for power system operations planning     

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。     

A Method for Solving the Fuel Constrained Unit Commitment Problem

The unit commitment problem involves finding the hourly commitment schedule for the thermal units of an electrical system, and their associated generation, over a period of up to a week. For some utilities, contractual or other factors limit the amount of fuel available to certain of the units or plants. This paper describes a new method which solves the unit commitment problem in the presence of fuel constraints. The method uses a Lagrangian decomposition and successive approximation technique for solving the unit commitment problem where the generation, reserve and fuel constraints are adjoined onto the cost function using Lagrange multipliers. All important operating constraints have been incorporated including minimum up and down times, standby operation, ramping limits, time-dependent start-up cost, spinning and supplemental reserve. The method is being applied to a production-grade program suitable for Energy Management Systems applications.     

基于多时间尺度协调机组组合的含风电系统 旋转备用优化研究

考虑风电出力的预测误差和负荷功率的预测误差具有随预测时间尺度的缩短而减小的特点,以及电力系统旋转备用容量的配置离不开机组组合,建立了多时间尺度下协调机组组合的含并网风电电力系统旋转备用预留容量的优化模型。对该模型的求解,先采用优先顺序法求取各机组的启停机顺序,再通过粒子群算法滚动计算求解得出不同等效旋转备用容量水平下所对应的系统最经济调度计划。通过利用不断更新的风电出力预测和负荷预测结果信息来调整调度计划,在保障系统可靠性达到要求的前提下,减少含风电电力系统旋转备用容量的配置,从而提高风电并网后电力系统运     

考虑多种约束条件的机组组合新算法

提出了考虑系统降出力备用约束、机组出力变化速率、线路潮流约束和断面传输功率约束的机组组合新算法。算法没有引入任何乘子,计算单调收敛,速度快,并且不需要初始可行解。用ＩＥＥＥ ２４母线系统对算法进行了验证,结果表明,算法对各种约束条件的处理正确,解的质量好。     

Unit commitment health analysis for interconnected systems

The concepts previously published for unit commitment and operating reserve assessment in an isolated power system using a system well-being framework are extended in this paper to evaluate unit commitment and spinning reserve requirements in interconnected power systems. The problem of interconnected power systems unit commitment is decomposed into two subproblems. Unit scheduling is first performed in each isolated power system in accordance with the specified operating criterion. This is then followed by interconnected power system evaluation. The analysis is further extended to determine the operating state probabilities for the overall interconnected power system. The paper illustrates how power system well-being is improved by interconnection with other power systems. The concepts contained in the paper are illustrated by application to two radially interconnected IEEE-RTS     

市场竞争条件下发电机组启停机计划优化研究

探讨市场竞争条件下的发电机组启停机计划问题有助于发电厂制定发电机组安全经济运行方案。文章以发电厂收益最大化为目标函数,考虑了无功和备用收益的影响,以机组本身的可用状态、发电功率限制、爬坡速率以及系统备用容量和电力市场交易等为约束条件,构造了市场竞争条件下发电机组启停机计划问题的数学模型,并提出了一种综合了二次规划、遗传算法、模拟退火算法的优点的混合优化方法进行解算。对某8机系统进行的算例分析表明:市场竞争条件下考虑了备用收入影响的发电厂启停机计划发生了一些变化;发电厂为了追求更大的收益更加注重生产成本问题;其通过竞争获得的发电功率直接影响发电机组启停计划及其功率分配;文中提出的混合优化算法较适用于求解市场条件下的启停机计划等优化问题。     

基于免疫算法的机组组合优化方法

机组组合是改善传统电力系统运行经济性和电力市场出清的重要手段。基于群体进化的智能优化算法存求解过程中存在计算效率低和易于早熟收敛等缺点。提出机组组合的免疫算法，利用免疫算法保持种群多样性的内在机制和免疫记忆特性改进既有的智能优化方法。新算法扩展了约束处理技术，能更好地对可行解空间搜索，采用一种由后向前、由前及后、双向迂回推进的精简程序改善个体可行解的局部最优性，同时利用优先级顺序法产生能较好反映问题先验知识的初始种群。典型算例证实新算法能获得更优的结果，具有更快的收敛速度，且在系统规模扩大时有大致线性的计算复杂性，是一种新的高效的机组组合智能优化算法。     

多主体利益制衡的综合能源系统日前-实时出清方法

为解决现货市场和配售侧放开环境下综合能源系统与外部电网联合出清问题,提出一种多主体利益互相制衡的日前-实时两阶段出清方法。该方法考虑日前出清阶段驱动各方利益,实施多轮迭代竞价,并将互保、备用、移峰等因素纳入竞价过程中;实时出清阶段统筹内、外备用,细化供能和利益分配,形成产能商、上级电网、旋转备用服务商三联供能体系。分别构建了产能商、运营商、负荷聚合商的出清决策模型,最后通过算例仿真分析了需求响应、互保合同以及旋转备用市场对移峰和内、外备用的有效作用,表明该方法可以实现供需平衡和各主体利益均衡。     

含风电电力系统机组组合的量子离散差分进化方法

风电具有天然的不可控性和随机性,大量并网给电力系统调度计划带来困难,在电力系统日前机组组合计划中计及风电出力的不确定性,有利于提高电力系统优化运行的精细度.文中通过系统旋转备用将风电出力的预测误差纳入机组组合的数学模型中,为求解含风电的机组组合问题,设计了双层求解方法,外层采用量子离散差分进化法优化传统火电机组的启停状...     

The challenges of the unit commitment problem for real-life small-scale power systems

Small-scale power systems mainly present two particular problems when it comes to their modeling and solution. Due to their size, it is important to consider and meet various types of reserve requirements in order to have a reliable operation of the power system. It is also important to consider variable start-up costs in order to obtain a more accurate unit commitment. In this paper six different types of reserve requirements are considered for the unit commitment problem: spinning reserve, regulation reserve (AGC per unit), ten-minute reserve, ten-minute non-synchronized reserve, ten-minute operational reserve, and ten-minute distributed reserve. Additionally, a Mixed Integer Programming formulation is introduced to represent variable start-up costs. The model introduced here is currently in use by the Baja California (México) power system operator.     

Binary fireworks algorithm for profit based unit commitment (PBUC) problem

The deregulation of electricity markets has transformed the unit commitment and economic dispatch problem in power systems from cost minimization approach to profit maximization approach in which generation company (GENCO)/independent power producer (IPP) would schedule the available generators to maximize the profit for the forecasted prices in day ahead market (DAM). The PBUC is a highly complex optimization problem with equal, in equal and bound constraints which allocates scheduling of thermal generators in energy and reserve markets with no obligation to load and reserve satisfaction. The quality of the solution is important in deciding the commitment status and there by affecting profit incurred by GENCO/IPPs. This paper proposes a binary coded fireworks algorithm through mimicking spectacular display of glorious fireworks explosion in sky. In deregulated market GENCO/IPP has the freedom to schedule its generators in one or more market(s) based on the profit. The proposed algorithm is tested on thermal unit system for different participation scenarios namely with and without reserve market participation. Results demonstrate the superiority of the proposed algorithm in solving PBUC compared to some existing benchmark algorithms in terms of profit and number of iterations.     

Export/import of spinning reserve in interconnected generationsystems

Interconnected power systems may import energy and/or purchase spinning reserves from neighbors in order to reduce risk. A probabilistic technique is presented to assess import and/or spinning reserve purchase requirements of interconnected systems in order to overcome the effects of inadequate operating capacity on unit commitment risk. A unit commitment technique which can include options of spinning reserve purchase/sale is presented. A method of assessing the portion of the running cost in interconnected power systems due to export/import and purchase of spinning reserve is also illustrated     

应用MAS解决基于利润的机组组合问题研究

电力系统引入放松管制的市场运行机制之后,形成一种基于利润的机组组合问题:①优化目标从费用最小转为利润最大;②各发电公司从自身利益出发,可以不完全满足中心调度的要求。针对以上特点,提出一种基于多Agent系统的解决方法。仿真结果表明,该方法能够适应解决现代电力系统机组组合问题的新需要,能够获得更大的经济效益。     

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     

Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network

This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time constraint, generation ramp limit constraints, and minimum up and down time constraints. The IPL is a priority list enhanced by a heuristic search algorithm based on the average production cost of units, and the ALH is a continuous Hopfield network whose energy function is based on augmented Lagrangian relaxation. The IPL is used to solve unit scheduling problem satisfying spinning reserve, minimum up and down time constraints, and the ALH is used to solve ramp rate constrained economic dispatch (RED) problem by minimizing the operation cost subject to the power balance and new generator operating frame limits. For hours with insufficient power due to ramp rate or 15 min spinning reserve response time constraints, repairing strategy based on heuristic search is used to satisfy the constraints. The proposed IPL-ALH is tested on the 26-unit IEEE reliability test system, 38-unit and 45-unit practical systems and compared to combined artificial neural network with heuristics and dynamic programming (ANN-DP), improved adaptive Lagrangian relaxation (ILR), constraint logic programming (CLP), fuzzy optimization (FO), matrix real coded genetic algorithm (MRCGA), absolutely stochastic simulated annealing (ASSA), and hybrid parallel repair genetic algorithm (HPRGA). The test results indicate that the IPL-ALH obtain less total costs and faster computational times than some other methods.     

考虑虚拟电厂多类电力产品的配电侧市场出清策略

为完善电力市场运营机制,挖掘不同类别虚拟电厂各自的优势,提出了一种虚拟电厂介入的配电侧市场出清策略。文中首先对虚拟电厂参与配电侧市场的商业运营模式和组织方法进行探讨,进而提出了一种考虑多种电力市场产品耦合关系的配电侧市场联合出清模型并推导了相应定价方法,所涉及的电力市场产品包括有功功率、无功功率、旋转备用、调频容量和调频里程。中国中山25节点实际配电系统和Matpower 141节点标准配电系统的案例仿真结果表明,所提配电侧市场方法具有高求解效率和普遍适用性。     

电力市场中火电机组自组合的模糊优化方法

机组启停机计划是发电公司参与电力市场竞争的重要决策依据。市场环境下,出清价格具有高度不确定性,必须在机组自组合决策中给予考虑。在市场出清价格模糊描述的基础上,提出不确定环境下含有启停机爬坡速率和升降出力爬坡速率约束的火电机组自组合模糊优化方法,通过分析真实市场参与者的决策取向,提出一种新的精确化方法,并采用动态规划模型求解精确优化问题,同时给出了精确化过程中多目标偏好系数的选择建议。算例分析表明,模糊机组自组合方法能灵活反映决策目标,是市场环境下一种新的不确定性决策方法。     

运行备用市场定价机制对机组报价行为的影响

运行备用是保障电力系统高可靠供电的必要手段。能量市场和运行备用市场之间存在着内在联系。如果备用市场的定价机制能够引起能量市场出清价格的变化，对系统的影响将很大。文中首先按照不同的备用市场定价原则，即市场出清价格方式和按报价结算方式，获得了机组基于成本报价时的利润分布，并分析了分布的合理性及其对机组报价行为的影响。然后利用博弈模型，考察了备用市场不同的定价方法对能量市场机组的报价行为的影响，认为在运行备用市场使用按报价结算方式定价比统一的出清电价方式能更好地引导机组在能量市场报成本价格。仿真计算结果说明了理论分析的意义。