An efficient algorithm for optimal generation mix taking into account fuzziness of decision making and planning parameters

This paper presents an efficient computational algorithm for selecting the optimal generation mix under uncertain circumstances. Subjective, experiential or linguistic uncertainties are selected from among various uncertainties, i.e., we treat fuzziness in generation expansion planning. The fuzziness can be divided into: (1) the fuzziness of decision making; and (2) the fuzziness of some planning parameters, such as load growth, fuel price, and so on. Both classes of fuzziness are integrated into a fuzzy decision based on fuzzy sets theory, and then the optimal generation mix can be determined by the Fuzzy Dynamic Programming (FDP) technique. The proposed method, which is based on the dynamic programming technique, is extended by using the Bellman-Zadeh maximizing decision. In the method, each generation technology and generation capacity are selected as a stage and state, respectively. The proposed method can easily accommodate not only the fuzziness but also many constraints of generation expansion planning, such as integer solutions of unit capacities, condition of existing units, and so on. Furthermore, the arbitrary shape of membership function can be used. The effectiveness and feasibility of the proposed method are demonstrated on a typical power system model.     

电源规划优化软件实用化研究

简述电源规划算法研究现状及软件开发和应用情况后，介绍了新一代图形化电源规划软件POWERPLAN，采用快速电源优化排序法，以电源投资费用等年值最小为目标函数；以及相关技术约束（电力平衡、水火电平衡、电源投产／电厂开工时间）条件、人机交互、报表输出等关键技术。详叙了POWERPLAN软件在满足各种技术经济约束条件下，自动生成电源优化装机方案的设计思想。该软件主要由数据处理、规划计算、报表输出、图形管理等模块组成。最后，利用该软件对某省2006～2020年的电源规划工作进行了分析，结果表明．规划优化效果符合要求。     

计及分布式发电的配电网扩展规划

计及分布式发电(DG)进行配电网扩展规划.从电网年支出费用的角度出发,采用蒙特卡洛方法模拟DG的出力,建立新的数学模型.提出一种基于隐性编码方式的遗传算法,用它对待选新建或升级改造线路、DG的种类、位置和容最进行综合优化规划,并分析DG出力不确定性及其发电成本对规划的影响.经算例验证,对DG进行合理地选择、布点和定容,能够给电网带来可观的经济效益.     

基于随机期望值规划的输电网规划方法

电力市场环境下输电网规划面临大量的不确定因素的影响,运用不确定规划理论建立了输电网随机期望值规划模型,采用随机数来描述新增发电机节点出力,新增节点负荷变化值,新增线路造价的不确定性因素,利用Monte-Carlo仿真和改进小生境遗传算法求解模型,修改的18和46节点系统验证了所提模型和方法有效.     

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RGA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models.     

An algorithm for linguistic risk assessment of uncertain factors in generation planning

This paper presents an efficient computational algorithm for evaluating the risks of uncertain factors in generation planning. Uncertainty in a multiobjective risk assessment problem can be divided into (a) uncertainty of the possible conditions to be evaluated; (b) uncertainty in multiobjective decision making; and (c) uncertainty in risk which is obtained using imprecise information. The proposed method basically consists of two phases: (1) the aggregation of risks with respect to all of the objectives for each uncertain factor; and (2) the linguistic expression of the aggregated risk of each uncertain factor. In the first phase, uncertainty in possible conditions is treated as fuzziness in planning parameters, and uncertainty in multiobjective decision making is also treated as fuzziness in decision making. Furthermore, the statistical trend of risk with respect to an objective for each uncertain factor can be extracted from uncertain risks obtained using imprecise information. In this method, both classes of fuzziness and the statistical trend of risk for each uncertain factor can be integrated into the risk of each uncertain factor, and then the risks of each uncertain factor with respect to all the objectives can be aggregated by extension principle in fuzzy sets theory. In the second phase based on the linguistic approximation technique, the aggregated risk of each uncertain factor can be represented by natural language. The proposed method can realize an effective and flexible decision support for evaluating the risks of uncertain factors in generation planning. The effectiveness and feasibility of the proposed method are demonstrated on a typical power system model.     

基于并行动态规划的水库发电优化

动态规划是水库发电优化调度研究中的经典方法。为了提高动态规划算法计算性能以及适应多核计算技术发展趋势,本文在分析传统串行动态规划算法计算特点的基础上,建立基于主从模式的并行动态规划模型,并将其运用到水布娅水库的发电优化计算中。计算结果表明,在多核运算平台下,并行动态规划算法能够充分利用多核资源,有效提高算法计算效率,缩短计算时间。     

基于动态规划算法的配电网孤岛划分策略

配电网发生故障后,失电区域内应该形成含分布式电源(DG)的电力孤岛保证负荷供电的连续性。在孤岛形成算法中充分考虑负荷等级及其可控性,建立孤岛划分问题的数学模型,并利用动态规划算法形成含单DG或多DG组合的初级孤岛划分方案;根据一定的规则修正初级孤岛,形成次级孤岛;校验岛内各负荷点的电压和潮流约束,确定最优孤岛。算例验证了所提模型的有效性和优越性。     

电源规划模型及求解方法研究综述

对传统的电源规划模型结合需求侧管理、考虑环境保护和电力市场环境下的电源规划模型进行了详细的研究,总结了实施需求侧管理、环境保护对电源规划的影响和电力市场改革对电源规划的新要求,分析了各种模型中电源规划目标函数和考虑约束条件的不同。然后将电源规划问题所采用的求解方法主要分为数学优化方法和人工智能方法进行归纳,包括动态优化法、混合整数规划法、专家系统、模糊理论、遗传算法和人工神经网络等,对比了各种方法的优缺点。最后阐述了当前电源规划过程中尚待深入研究的问题。     

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.     

Application of parallel genetic algorithms to generation expansion planning using parallel processors

This paper presents an application of parallel genetic algorithms (PGA) to the optimal long-range generation expansion planning. The problem can be formulated as a combinatorial optimization problem that determines the order of introduced generation units at each interval of the year. The proposed method considers introduced power limits of each technology, maximum loads at each interval, and load duration curves at each interval. Appropriate string representation for the problem is presented. Binary and decimal coding and three selection methods are compared. The method is developed on a transputer that is one of the parallel processors. The feasibility of the proposed method is demonstrated using a typical expansion problem with four technologies and five intervals. The method is then compared with conventional dynamic programming and a simple genetic algorithm with promising results.     

Proposal of a simplified method for integrating reduction of effective power of pumped storage into a generation system planning method

Pumped storage hydropower stations are extensively used as peaking and reserve power plants. The current trend in this area is to increase their power output relative to the capacity of reservoirs, which results in a shorter maximum duration of full‐power operation while availability of the energy required for the pumping becomes less evident. This increases the possibility of reducing the effective power of pumped storage units in the case of a tight supply–demand balance in the power system. Although many studies have examined a role of pumped storage in generation systems, few studies have explicitly dealt with the power reduction. This paper proposes a new linear programming model that incorporates the reduction of effective power of pumped storage. The proposed model makes it possible to easily incorporate the power reduction in computations by employing hypothetical daily load curves and dispatching loads to the curves. The model also includes LNG combined cycle power generation plants that are now being intensively implemented. The developed model is applied to a power system model. The sample study reveals that the reduction of effective power considerably varies from season to season and the reduction highly affects the optimal generation mix, that is, the optimal share of pumped storage. © 2001 Scripta Technica, Electr Eng Jpn 134(4): 50–61, 2001     

Novel approach of modeling load duration curve for generation expansion planning based on Hill's function

A novel approach of modeling the load duration curve (LDC) based on Hill's function is proposed in this article. On the contrary to traditional models, the proposed model is completely an analytical one which can be determined by historic load data. This method is effective in calculating efficiency as well as controlling errors and it is quite simple in application because the model has only a few parameters, each of which has a definite economic or fiscal meaning. Based on the historic model, this method is easy and accurate in estimating the LDC model for a future year by changing the parameters of Hill's function, where only the peak load and the total demand in each year may be given. Results on the load data from IEEE reliability test system (IEEE‐RTS), PJM and Beijing Electric Power Corporation (BEPC) are presented to demonstrate the effectiveness of the proposed model. Numerical examples show that the modeling errors in both peak load and total demand, which are key indices for generation expansion planning and reliability evaluation, are less than 1%. The LDC model for a future year is also accurately estimated in these examples. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于改进Benders分解的配电网扩展规划机会约束优化方法

为了解决已有配电系统规划中非线性潮流模型建模问题和不确定性优化效率问题,本文提出了基于双线性Benders分解的配电网扩展规划机会约束优化方法。首先通过在规划投资层面和运行优化层面进行分阶段,构建了两阶段随机混合整数二阶锥规划模型;然后为了避免极端场景下导致的高昂投资成本,进一步扩展了传统的Benders分解方法,设计了基于双线性Benders分解的机会约束优化方法。通过三个算例系统验证了本文所提出方法的卓越的优化性能。     

基于改进型动态规划算法的厂级负荷优化分配

在详细介绍了实行厂级负荷优化分配的重要性后,着重论述了用于火电厂厂级负荷优化分配的一般动态规划算法并指出其不足,提出了一种改进的动态规划算法,它根据经验所形成的策略来变换步长,再对不同步长下的所求解进行二次寻优,基本上克服了因步长选取不当而带来的非最优化问题.案例表明：改进型动态规划算法效果良好,具有不错的工程应用价值.     

An evaluation of the optimal generation mix for controlling carbon dioxide emissions

This paper presents an efficient computational algorithm for selecting the optimal generation mix considering CO₂ emissions. To demonstrate the effectiveness and feasibility of the proposed method, a fundamental study of the evaluation of the optimal generation mix for controlling CO₂ emissions is indicated. Furthermore, by using a parametric analysis which considers load characteristics as parameters, a general trend for the optimal generation mix which is affected by controlling CO₂ can be derived. The proposed method is based on an optimization method known as simulated annealing. In the method, solutions in a generation mix problem are equivalent to state of a physical system, and the cost of a solution is equivalent to the energy of a state. The proposed method can easily accommodate not only CO₂ emissions but also many practical constraints of generation expansion planning, such as integer solutions of unit capacities, condition of existing units, and so on. Case studies with various annual load patterns (combinations of annual load factors and the shapes of annual load duration curve) are presented and discussed. Consequently, a general trend for selecting generation technologies that should be added to a power system is derived, i.e., a useful guideline for studying generation expansion planning under controlling CO₂ emissions can be provided.     

基于分布式电源的孤立系统规划初探

现代自动化信息化技术的广泛应用对重要场所供电保障系统可靠性提出了很高要求,分布式发电技术和孤立电力系统的发展为提供新型可靠性供电提供了新的选择。提出分布式电源应用于孤立系统提高系统供电安全可靠性的思想,介绍了分布式发电技术,阐述了分布式电源提高孤立系统可靠性的基本思路,在充分考虑分布式电源不同形式、冷热电联产系统等因素基础上,建立了分布式电源的经济模型,研究了孤立电网规划模型。算例计算证明了规划模型的正确性和有效性,并表明了分布式电源对孤立系统可靠性提高的显著作用。     

梯级水库综合利用调度的动态规划方法研究

黄河上游梯级水库水电站群承担发电、灌溉、防洪、防凌等任务,是目前国内综合利用要求最多的梯级水电站群。本文针对该系统的特殊要求,建立了含有水位、流量和出力等式约束的梯级优化调度模型,目标函数为兼顾保证出力要求的发电量最大,采用约束惩罚法将等式约束转化为目标函数的一部分,然后应用DP-DDDP组合算法求解。研究表明,这种方法可以有效地求解具有复杂、多变约束条件的长期联合优化调度模型。     

Transmission expansion planning based on Locational Marginal Prices and ellipsoidal approximation of uncertainties

This paper proposes an algorithm for transmission expansion planning (TEP) which minimizes the congestion surplus calculated from optimized nonlinear (AC) Optimal Power Flow (OPF) and Locational Marginal Prices (LMPs). Uncorrelated and correlated uncertainties related to operating conditions of the future transmission network and expected costs of the submitted energy bids to the energy market are constrained by bounding hyper-ellipsoid around base case AC OPF solution, with assumption of additive uncertainties. Perturbed uncertain points inside a hyper-ellipsoid are selected by proposed quasi-random sampling algorithm. For these points, the linearized OPF around base case AC OPF solution is proposed. The Genetic Algorithm (GA) does selection of lines and years for transmission expansion, where the increments of the fitness function are calculated by proposed linearized AC OPF model. The results and practical aspects of the proposed methodology are illustrated on 12- and 118-bus test power system examples.     

基于动态规划的分布式电源优化配置

电源规划是电力系统中非常重要的规划。本论文在分析平顺绿色能源资源条件、电力负荷需求的基础上,根据当地实际情况,应用动态规划的优化方法结合各种约束条件,得到分布式电源的规划方案。