Power system structure optimization subject to reliability constraints

The problem of the optimization of the structure of a power system where redundant elements are included in order to provide a desired level of reliability is considered. A procedure which determines the minimal cost series-parallel system configuration is proposed. In this procedure, system elements are chosen from a list of products available on the market and the number of such elements is determined for each system component. The elements are characterized by their capacity, availability and cost. System reliability is defined as the ability to satisfy consumer demand which is represented as a piecewise cumulative load curve. To evaluate system reliability, a fast procedure is developed which is based on a universal generating function. A genetic algorithm is used as an optimization technique. An example of the redundancy optimization of a power station coal feeding system is presented.     

Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation

Usually power energy demand increases randomly with time. To enhance system performance, expansion-planning to adapt the power system capacity to the demand is predicted. This paper uses a harmony search meta-heuristic optimization method to solve the multi-stage expansion problem for multi-state series-parallel power systems. The study horizon is divided into several periods. At each period the demand distribution is forecasted in the form of a cumulative demand curve. A multiple-choice of additional components from a list of available products can be chosen and included into any subsystem component at any stage to improve the system performance. The components are characterized by their cost, performance (capacity), and availability. The objective is to minimize each investment over its study period while satisfying availability or performance constraints. A universal generating function technique is applied to evaluate power system availability. The harmony search approach is required to identify the optimal combination of adding components with different parameters to be allocated in parallel at each stage.     

Ant colony optimization for multi-state series-parallel system expansion scheduling

The design problem is the most important phase in many industrial application cases. Usually the demand increases randomly with time. To enhance system performance, expansion scheduling to adapt the system capacity to the demand is predicted. This paper uses an ant colony meta-heuristic optimization method to solve the multi-stage expansion problem for multistate series-parallel systems. The study horizon is divided into several periods. At each period the demand distribution is forecast in the form of a cumulative demand curve. A multiple choice of additional components among a list of available products can be chosen and included into any subsystem component at any stage to improve the system performance. The components are characterized by their cost, performance (capacity) and availability. The objective is to minimize the whole investment costs over the study period while satisfying availability or performance constraints. A universal generating function technique is applied to evaluate system availability. The ant colony approach is required to identify the optimal combination of adding components with different parameters to be allocated in parallel at each stage.     

Structure optimization of power system with bridge topology

The problem of optimization of a power system structure which cannot be reduced to series or parallel combinations is considered. The system contains a bridge substructure in which redundant elements are included in order to provide a desired level of reliability. The elements of the system are characterized by their capacity, availability and cost. A procedure which determines the minimal cost system configuration subject to reliability constraints is proposed which provides solutions with different structure topology. In this procedure, system elements are chosen from a list of products available on the market. System reliability is defined as the ability to satisfy consumer demand which is represented as a piecewise cumulative load curve. To evaluate system reliability, a universal generating function technique is applied. A genetic algorithm (GA) is used as an optimization technique. Examples dealing with the determination of the optimal structure of a power station coal transportation system are presented for problems with different constraints.     

电力系统负荷恢复问题的混合遗传算法求解

对电力恢复过程中最后一个阶段的负荷恢复问题进行了研究,把电力系统的负荷恢复问题建模为带众多约束条件的0?1背包问题,并设计了一种将贪心算法与改进遗传算法相结合的改进混合遗传算法来对问题进行求解.在遗传算法之前,先用贪心算法生成该问题的贪心解,然后让每一代中有着最差适应度的个体无条件的变为此贪心解,使最终结果至少不会比贪心法差.解决了系统在负荷恢复过程中的潮流计算问题,采用先求系统的频率变化,然后再计算潮流分布的方法,将约束条件和目标函数融合在一起,通过建立一种偏序关系,避免了罚函数选择参数的困难.利用贪心算法求解背包问题的快速性和多父体杂交的非凸组合技术,使算法具有求解的快速性和在解空间内搜索的遍历性.算例求解结果表明了该算法在负荷恢复问题中的有效性.     

Identifying the optimum wind capacity for a power system with interconnection lines

This paper presents a general framework for identifying the optimum wind capacity to be integrated in a power system with interconnection lines. Wind generation is treated as negative demand, together with the load demand, which must be covered by the conventional power generation and the energy interchange with neighboring systems. Under the presumption that the time-varying wind and load together with the trading price with neighboring systems could be statistically modeled by specified probability distributions, a chance constrained programming (CCP) model is formulated to address the wind capacity planning problem. The objective is to maximize the yearly net profit of the entire power system subject to the operational constraints and the reliability requirement. Wind power curtailment and load shedding are allowed to improve the system flexibility but incur penalty costs. The optimization problem is solved using a hybrid intelligence algorithm incorporating Monte Carlo simulations, a neural network and a genetic algorithm. The feasibility of the proposed approach is verified by a case study on a given power system.     

Numerical modeling for the retrofit of the hydraulic cooling subsystems in operating power plant

This paper presents the possibility of using the numerical methods to analyze the work of hydraulic systems on the example of a cooling system of a power boiler auxiliary devices. The variety of conditions at which hydraulic system that operated in specific engineering subsystems requires an individualized approach to the model solutions that have been developed for these systems modernizing. A mathematical model of a series-parallel propagation for the cooling water was derived and iterative methods were used to solve the system of nonlinear equations. The results of numerical calculations made it possible to analyze different variants of a modernization of the studied system and to indicate its critical elements. An economic analysis of different options allows an investor to choose an optimal variant of a reconstruction of the installation.     

Distribution systems expansion planning by multi-stage branchexchange

The authors present a multistage branch exchange algorithm for solving expansion planning problems in distribution systems. Since it is formulated as a combinatorial optimization problem, it is difficult to solve such a large-scale problem accurately. Therefore, in order to find a solution quickly, the authors have developed a method based on the branch exchange technique which is able to find an approximate solution. To obtain a more accurate solution, the multistage branch exchange algorithm is introduced. The validity and effectiveness of the proposed algorithm are demonstrated by applying it to a 59-node, 69-branch numerical example system     

区域电力系统最优备用容量模型与算法

建立实现备用容量最小的区域互联电力系统最优备用容量数学模型,推算多区域互联电力系统的联络线功率增量方程,以及区域互联电力系统频率偏差与区域备用容量的关系表达式。针对问题的具体特点,运用自适应免疫遗传算法对该模型进行求解,充分考虑频率偏差、负荷的随机波动以及区域互联系统运行的各种可靠安全约束,分别对独立的电力系统以及通过交直流联络线互联组成的区域电力系统进行仿真计算,可得到一天中24个时段的弹性备用容量。独立电力系统的算例表明：随着电力系统规模的扩大以及装机容量的逐步增大,最优备用容量占最大负荷的比例会逐步减小,可以减小0.395%~9.366%。对区域互联系统的算例表明：当区域系统互联时可以在一定程度上减小区域系统的备用容量,互联区域系统比各个独立系统的备用容量要减少1.036%~1.858%,节约了互联区域电力系统的成本,在一定程度上提高了区域互联系统运行的经济性。实例计算结果验证了所提模型的合理性、所提方法的可行性。     

Reliability evaluation of electrical power systems including multi-state considerations

A new approach is introduced for calculating the electrical network reliability indices, such as multi-state stationary availability, expected multi-state capacity, expected unsupplied demand, loss of load probability and total failed system probability. The universal moment generating function approach (UMGF) is used to evaluate the different reliability indices of the power system. In this paper we present a survey of recent work which treats the more sophisticated and realistic models in which components and systems may comprise many states ranging from perfect-working to complete failure. Such systems are multi-state (MSS) as they can have different levels of output performance. The objective is to determine the power structure which minimizes costs and satisfies reliability levels. A computer program has been developed to implement the UMGF technique, and an illustrative example is presented.     

Transmission Network Expansion Planning Considering Uncertainty in Demand

This paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand     

基于系统功效的保护及控制系统可靠性评估

采用元件可靠度和系统可靠度两个可靠性指标,提出功效评估法：通过硬件模块、接口模块、功能模块、功效模块对继电保护及控制系统进行建模。针对二次系统对一次系统的产生的功效,提出一次系统的典型功能事件,并分别通过串并联网络法定量评估二次系统的可靠性。深入到元件层面对硬件模块进行重要度分析并重新排序,从而有针对性的发现系统薄弱环节,提高二次系统的可靠性。     

基于系统功效的保护及控制系统可靠性评估

采用元件可靠度和系统可靠度两个可靠性指标,提出功效评估法:通过硬件模块、接口模块、功能模块、功效模块对继电保护及控制系统进行建模.针对二次系统对一次系统的产生的功效,提出一次系统的典型功能事件,并分别通过串并联网络法定量评估二次系统的可靠性.深入到元件层面对硬件模块进行重要度分析并重新排序,从而有针对性的发现系统薄弱环节,提高二次系统的可靠性.     

主动配电网多目标网络重构研究

本文提出了一种适用于主动配电网的多目标网络重构混合进化算法。选择目标函数为网损最小、供电可靠率最高,并在约束条件中考虑了分布式电源(DG)的出力约束,在可靠性计算中考虑了主动配电网中DG的计划孤岛作用;算法首先利用最优流模式算法(OFP)得到接近最优的局部最优解,再利用树形结构编码单亲遗传算法(TSE-PGA)搜索最优解;提出了适用配电网重构的TSE-PGA对应的移位、重分配操作算子;用改进非支配排序遗传算法(NSGA-II)的非支配排序策略对迭代过程的个体进行排序,最终得到Pareto前端解集。选择改进TPC 84节点算例验证所提出的混合进化算法,与其他算法的结果进行比较,证明了该算法的优越性。     

Reliability planning for composite electric power systems

This paper proposes a reliability design approach using network flow technique, genetic algorithms, and Monte Carlo simulation for composite electric power systems. With increased emphasis on reliability design and cost control in electric power system planning and operation, particularly in composite electric power system, we are therefore striving to achieve an optimal reliability design solution under a reliability/cost implemented model. Because the floating-point representation is more efficient than the binary representation in genetic algorithms application, and the former also has more robust operators to locate near optimal solutions in most cases, we will employ the floating-point representation. The proposed method primarily finds out the optimal values of reliability indices for the components such that the objective function composed of interruption cost and installation cost is minimized. The reliability indices adopted include expected demand not served (EDNS) and forced outage rate (FOR). Application of the proposed method is demonstrated using a 23-bus test system.     

Static transmission capacity expansion planning under uncertainty

This paper presents a new formulation of the static optimization problem in long-range transmission capacity expansion planning. A quantitative reliability technique is used in conjunction with a stochastic load flow formulation in order to accommodate uncertainty in system component availability and demand projections. The problem is solved using chance-constrained programming. Application of the formulation is demonstrated using the IEEE five-bus test system.     

市场环境下基于系统阻塞指标约束的多阶段输电网规划

电力市场环境下的多阶段输电网扩展规划在满足发电公司和用户的需求的同时,对减缓输电系统阻塞,促进市场的公平竞争具有重要作用。在此背景下,利用系统阻塞指标和系统阻塞成本分别作为评估规划网络可靠性指标和运行指标,以改进的小生境遗传算法为研究方法,提出了基于阻塞指标约束下的输电网多阶段规划模型。IEEE-24节点系统上算例分析表明该模型综合考虑了各规划阶段输电系统的经济运行,能更科学地指导输电网规划决策,有效减缓系统阻塞发生,提高规划系统的网络充裕性。     

交直流系统可靠性评估

直流系统传输容量大、元件多、故障率高,对电力系统的可靠性影响较大.随着实际系统中直流输电工程的陆续投运,迫切需要研究如何定量考虑直流系统对系统可靠性的影响.文章根据双极直流系统的结构和特点,采用故障树分析法,将直流故障结果分为单极停运、双极停运和容量降低;然后应用频率和持续时间法计算得出直流系统的多状态模型嵌入发输电系统可靠性评估软件中;并在系统状态分析中考虑了直流控制措施的影响.建立了交直流混合系统可靠性评估的模型、算法及指标体系,并开发了相应软件.对南方电网2005年规划方案的500kV交直流系统的评估结果验证了所提出的算法和软件的可行性和有效性.     

Analysis of interruptible electric power in deregulated power systems

Assuring appropriate levels of generation capacity adequacy at the minimum possible cost using market-based approaches is a contemporary issue attracting much attention in deregulated power systems. Introduction of interruptible electricity contracts could provide a possible solution to such a problem. However, theoretical frameworks for examining the impacts of these contractual arrangements on system operations have not been maturely developed. This paper presents a probabilistic production simulation based framework for modeling and analyzing interruptible electricity contracts. The interdependence between the pricing models of interruptible electric power and the operations of the whole system is addressed and solved by an iterative coordinating algorithm. The probabilistic production simulation framework allows the uncertainties inherent in both the forced outages of generators and system load demand at the contract delivery time to be taken into account. The proposed approach is capable of achieving comprehensive analysis and systematic pricing for interruptible electric power. A numerical case study is presented to illustrate the effectiveness and validity of the methodology.     

A multistage multiobjective substation siting and sizing model based on operator–repair genetic algorithm

The establishment of a multistage multiobjective substation siting and sizing planning model, taking into account various constraints such as load flow constraint, maximum capacity constraint, and maximum power supply radius constraint makes possible substation planning between multiple years to be adjusted to achieve an optimal overall plan. Through multiple optimization objectives, it is possible to prevent the plan from becoming useless because of excessive changes in power supply affiliation during the multistage optimization process. To find the optimal solution for the model, a repair operator is proposed and used with an improved multiobjective genetic algorithm to repair the decision variables for each chromosome corresponding to one stage so as to satisfy the constraints while ensuring that population diversity evolves heuristically to the optimal solution. Moreover, a tournament selection operator based on crowding distance is adopted, which can prevent the algorithm from premature convergence and make populations trend to the Pareto frontier. Experimental results show that the proposed model and algorithm can efficiently solve the issue of rolling planning between multiple target years and achieve a joint optimal planning. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.