Dynamic sub-transmission system expansion planning incorporating distributed generation using hybrid DCGA and LP technique

Since the emerging of distributed generation (DG) technologies, their penetration into power systems has provided new options in the design and operation of electric networks. In this paper, DG units are considered as a novel alternative for supplying the load of sub-transmission system. Thus, the mathematical model of considering DG on the expansion planning of sub-transmission system is developed. Fix and variable costs of the plan and the related constraints are formulated in the proposed model. The proposed objective function and its constraint are converted to an optimization problem where the hybrid decimal codification genetic algorithm (DCGA) and linear programming (LP) technique are employed to solve it. Solution of the proposed method gives the optimal capacity of substations; optimal location and capacity of DGs as well as optimal configuration of the sub-transmission lines. To demonstrate the effectiveness of the proposed approach, it is applied on a realistic sub-transmission system of Zanjan Regional Electrical Company, Iran, and the results are evaluated.     

Integrated distribution network expansion planning incorporating distributed generation considering uncertainties,reliability, and operational conditions

In this paper, an integrated methodology is proposed for distribution network expansion planning which considers most of the planning alternatives. The planning aims to determine the optimal reinforcement of existing medium voltage lines and high voltage/medium voltage substations, or installation of new ones to meet the load growth in the planning horizon subject to the technical and operational constraints. Also, to take the advantages of new technologies, the renewable and non-renewable distributed generations have been included in the problem as another alternative. The uncertainties related to renewable DGs, load demand, and energy price have been considered in the calculation of cost components. The load duration curve has been utilized for loads such that the results be more precise. The possibility of islanding and load transferring through the reserve feeders have been regarded in the problem to improve the reliability of the network. Also, the required condition for successful and safe operation of island considering all of uncertainty states have been checked out to accurately calculate the reliability. The genetic algorithm is employed to solve this integrated problem. Finally, the proposed method is applied to the 54-bus system and also a real large-scale distribution network, and the results are discussed. The results verify the effectiveness of the presented method.     

高比例可再生能源接入下考虑输配协同的输电网规划测试系统

以风光为主的高比例可再生能源通过不同电压等级接入电网,输电网与配电网之间的互济需求增强,促使输电网规划考虑与配电网协同,然而协同规划却面临着缺乏测试系统的难题.因此,构建了一个高比例可再生能源接入下考虑输配协同的输电网规划测试系统HRPTD-20,描述了系统的源网荷基本特性并给出了相关数据.系统包含2个区域、3个电压等级,以及3种传统和3种未来典型配电网结构场景,可再生能源装机容量占比接近55％.基于考虑输配协同的输电网规划模型求解,给出了测试系统的基准规划方案.对比分析验证了该测试系统可以用于输配电网协同规划,有助于提高可再生能源通过不同电压等级接入输配电网的消纳能力.     

用于配电网规划的改进遗传算法

针对传统遗传算法易于陷入局部最优解和随着配电网规模的扩大搜索效率降低的问题,借鉴协同进化思想提出了基于协同遗传算法的配电网规划算法。通过对目标函数进行处理引入了多个物种,并采用简单遗传算法和考虑进化稳定的改进多种群遗传算法分别对不同的物种进行操作,通过转移优秀个体实现了物种间的协同作用。同时为解决遗传算法应用于配电网规划时产生的大量不可行解的问题,借助图论知识和搜索技术给出了不可行解的修复方案,通过对孤岛、孤链和环进行修复,将非辐射状网络修复为辐射状网络。算例结果验证了该算法的实用性和有效性。     

基于蚁群最优的输电网络扩展规划

输电网络扩展规划是一个非常复杂的大规模组合优化问题。章提出了一种基于蚁群最优的输电网络扩展规划法（ACO）。ACO法来自对蚁群收集行为的研究,是一种求解组合最优问题的新型通用型发式方法。这种方法的主要特征是正反馈、分布式计算以及富于建设性的贪婪启发式搜索的运用。作初步研究了ACO法在单阶段输电网扩展规划中的应用。建立了相应的数学模型,设计了相应的算法,并在IEEE Garver-6系统上进行了测算。结果表明所提方法是有效的。     

基于自适应多种群遗传算法的配电网规划

针对传统遗传算法易于陷入局部最优解和随着配电网规模的扩大搜索效率降低的问题,借鉴多种群和自适应思想,提出了基于自适应多种群遗传算法的配电网规划算法。通过对目标函数进行处理,引入了多个物种,并采用自适应遗传算法和考虑进化稳定的改进多种群遗传算法分别对不同的物种进行操作,通过转移优秀个体,实现了物种之间的协同作用。同时为解决遗传算法应用于配电网规划时产生的大量不可行解的问题,借助图论知识和搜索技术给出了不可行解的修复方案,通过对孤岛,孤链和环进行修复,将非辐射状网络修复为辐射状网络。算例结果验证了该算法的实用性和有效性。     

分布式风电源选址定容规划研究

针对风电机组出力的间歇性、波动性,以及负荷变化的不确定性,应用机会约束规划建立了分布式风电源(distributed wind generation,DWG)接入现有配电网的选址定容规划模型,以独立发电商(independent power producer,IPP)收益最大为目标函数,采用随机潮流判断规划方案是否违反节点电压约束和支路功率传输约束。将模拟植物生长算法(plant growth simulation algorithm,PGSA)应用到DWG选址定容规划中。33节点配电系统DWG规划结果验证了模型的合理性和PGSA算法的有效性。     

基于混合整数二阶锥的配电-气网联合规划

提出了一种考虑配电网重构及小时级潮流变化的配电-气网(EGDN)联合规划模型。一方面,融入配电网重构来优化系统的运行状态,两网协同规划能发挥不同能源间的互补共济作用,提升系统的可靠性和运行效率;另一方面,所提模型考虑小时级配电网和配气网的潮流方程,以精细化描述系统的运行状态。为了求解该非线性非凸模型,适当松弛原问题,将其转换为可直接求解的混合整数二阶锥规划(MISOCP)问题。仿真结果表明所提规划模型显著提升了系统的可靠性,降低了相关设备的配置容量,减少了能量传输损耗,降低了总体规划与运行费用,证明了MISOCP模型与简单的混合整数线性规划模型相比,更能获得满足实际工程需求的规划方案。     

A novel modified GBMO algorithm based static transmission network expansion planning

Due to the growing demand of electricity, transmission sector has become important part of the power sector. The penetration level of renewable energy resources has increased presently, which gives more challenges to the transmission expansion planner. To overcome this problem better transmission expansion planning (TEP) needs to be done. Hence, it is necessary to incorporate the impact of high wind power penetration in TEP problem. In this paper wind farm are considered as an alternative source for supplying the load to the transmission networks. The complex wind energy cost model is incorporated with the traditional transmission network expansion planning (TNEP) problem. Factors accounting for wind power utilization cost, underestimation, and overestimation cost model of wind power are included. Static transmission network expansion planning (STNEP) problem is modeled using the DC power flow model. The main objective function is to minimize the total cost of the system, which consists of transmission line investment cost, fuel cost of generators and wind energy cost. To solve this non-linear, non-convex optimization problem with a novel optimization algorithm i.e. Modified Gases Brownian Motion Optimization (MGBMO) algorithm is applied. To validate the capability of the proposed method is tested with modified Garver’s 6-bus system, IEEE 24-bus system and IEEE 25-bus system.     

Parallel simulated annealing applied to long term transmissionnetwork expansion planning

The simulated annealing optimization technique has been successfully applied to a number of electrical engineering problems, including transmission system expansion planning. The method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Moreover, it has the ability to provide solutions arbitrarily close to an optimum (i.e. it is asymptotically convergent) as the cooling process slows down. The drawback of the approach is the computational burden: finding optimal solutions may be extremely expensive in some cases. This paper presents a parallel simulated annealing (PSA) algorithm for solving the long-term transmission network expansion planning problem. A strategy that does not affect the basic convergence properties of the sequential simulated annealing algorithm have been implemented and tested. The paper investigates the conditions under which the parallel algorithm is most efficient. The parallel implementations have been tested on three example networks: a small 6-bus network; and two complex real-life networks. Excellent results are reported in the test section of the paper: in addition to reductions in computing times, the PSA algorithm proposed in the paper has shown significant improvements in solution quality for the largest of the test networks     

A simulated rebounding algorithm applied to the multi-stage security-constrained transmission expansion planning in power systems

This research discusses the multi-stage security-constrained transmission network expansion planning. In modern power systems, the problem is formulated as a large-scale, mixed-integer, non-linear programming problem, which for a real power systems is very difficult to solve. Although remarkable advances have been made in optimization techniques, finding an optimal solution to a problem of this nature can still be extremely challenging. In this paper, a new constructive heuristic approach, based on a local controlled random search (simulated rebounding algorithm) is proposed to choose the decision variables. The model can produce better solutions than other references techniques such as particle swarm optimization, evolutionary particle swarm optimization, genetic algorithms, and simulated annealing algorithm, among other evolutionary methods. The methodology is applied to assess the capabilities of the proposed approach in the Ecuadorian and Chilean Power Systems as an example of application. Simulation results show that the proposed approach is accurate and very efficient, and it has the potential to be applied to real power system planning problems. The algorithm has been presented and applied to the multi-stage security-constrained transmission expansion planning.     

面向地区电网的EMS应用软件

地区电网EMS应用功能是地区电网调度和商业化运营的重要辅助决策工具,是继SCADA实用化后,地区电网调度自动化技术发展的必然趋势。但传统的EMS应用软件面向发输电系统,主要在大区电网和省网中应用。通过研究地调和网(省)调在调度管理职能、电网运行特点和自动化水平等方面的不同,设计和开发了面向地区电网的EMS应用软件系统,该系统在功能、算法和应用方法上都具有地调特色,并已在国内多家地调投入在线运行     

遗传禁忌混合算法及其在电网规划中的应用

电网规划是一个较难解决的NP难问题。文中首先就遗传算法、禁忌搜索算法(TS)及其两者的混合算法在旅行商问题(TSP)中的应用来比较它们之间的优缺点,认为采用了TS变异算子的改进遗传算法将大大提高其优化能力;然后通过该混合算法在典型电网扩展规划算例中的应用来看,认为该混合算法适用于求解复杂的电网规划问题;最后通过对该混合算法在求解实际的城市中压配电网络规划问题时与其他两种单一算法的结果比较来看,其搜索效率相比单一算法得到了很大程度的提高,体现了很好的应用前景。     

基于混沌自适应分组和声搜索算法的输电网规划

针对目前大规模输电网规划求解中难以快速地求得全局最优解的问题,给出了基于线路的建设费用、网络损耗费用、输电线路走廊的建设费用、各支路总的过负荷惩罚费用和N-1约束的过负荷惩罚费用为目标函数的输电网规划模型。分析了和声搜索算法随着输电网规模的扩大、优化问题维数的增加,算法求解精度和收敛速率明显降低且易陷入局部寻优的现象及其原因的基础上,设计了一种混沌自适应分组和声搜索算法。该算法通过维数分组、变异和混沌扰动来提升算法的搜索能力,使其能够快速地求解大规模的输电网规划问题。通过对IEEE18节点和巴西南部46节点系统的计算,证明了算法及模型应用于输电网规划的可行性,为实际工程应用打下了基础。     

Comparative studies on nonconvex optimization methods fortransmission network expansion planning

We have investigated and extensively tested three families of nonconvex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized     

考虑低碳和柔性负荷的有源配电网混合整数二阶锥规划

在配电网低碳化背景下,提出了考虑碳排放和柔性负荷的有源配电网混合整数二阶锥规划模型,目标是在满足网络运行约束和CO₂排放上限的前提下,给出总成本最小的投资策略。考虑新能源、负荷和能源价格的不确定性,提出了基于k均值的场景聚类方法。模型的决策变量为更换过载线路、投建新能源和储能装置,以及投建稳压器和电容器组等电压控制设备,并考虑了多项式形式的电压相关型的柔性负荷、网络重构以及碳排放额约束。针对规划模型的非凸非线性特征,采用虚拟需求法将网络重构建模为混合整数线性规划形式,并提出了一种基于泰勒展开的改进二阶锥松弛方法,以解决柔性负荷模型给传统二阶锥松弛带来的难题。通过69节点系统对该模型进行测试,结果表明,所提模型不仅总规划成本较低,而且有助于减少碳排放。     

基于配电自动化故障管理的配电网扩展规划方法

针对现阶段配电网规划过程中面临的可靠性问题,提出一种基于配电自动化故障管理的配电网扩展规划方法。首先对配电自动化的故障管理功能进行介绍;其次根据配网公司的盈利性,以其自身利益最大化建立目标函数,决定线路建设、变电站位置和容量,从而提出一种基于配电自动化的配电网扩展规划模型;然后针对所提模型和所研究的规划问题,采用遗传算法对其进行求解,并对配电系统可靠性进行评估;最后,基于仿真算例验证了所提规划模型的有效性。     

Greenfield distribution network expansion strategy with hierarchical GA and MCDEA under uncertainty

Distribution network expansion planning (DNEP) is becoming more complex in nature. Addition of new load centers, due to increasing conversion of greenfield areas into habitats, have generated need of more intense and highly structured planning strategies. Micro level work on distribution expansion planning has been ignored by most of the researchers mainly in Indian scenario. Since practical distribution networks are quite large, number of candidates (load centers) will be more and, hence, number of variables (electrical parameters and new load center feasible connections with the existing system) are remarkable. Optimizing a large system may result in significant decrease of accuracy and increase of computation time. For deciphering this issue, segmentation procedure has been applicable. For this purpose, a sensitivity analysis has been applied to find dependent variables. It is obvious that a correct segmentation can decrease computation time (as a single task is operated in segments simultaneously) while accuracy decreases negligibly. In present work, a scheme has been introduced to connect three greenfield load centers with existing primary distribution system by using hierarchical genetic algorithm (HGA). HGA is an integrated approach of analytical hierarchical process and genetic algorithm. The paper reports best selection of investment with finest voltage profile and least losses while maintaining radiality of the system. DNEP has been done at micro level and proposed methodology has been tested on a small dimension practical distribution system. The novelty of this paper is to optimize the best possible selection of connection of new load centers with existing system with the help of AHP and GA and results have been verified with advance optimal tool multiple criteria data envelopment analysis (MCDEA). HGA and MCDEA are applied to practical nine bus distribution system and the results are presented and compared.     

基于蚁群最优的配电网规划方法

详细探讨了现代启发式方法家族中新兴成员蚁群最优(Ant Colony Optimization, ACO)在配电网络扩展规划中的应用。蚁群最优是一种通用的内启发式(meta-Heuristic)算法,能够有效地求解大规模组合优化问题。文中给出了同时考虑配电网络扩展的固定费用和与电能损失相关的可变费用的配电网络规划的非线性混合整数规划模型,探讨了基于ACO的配电网络规划方法,并用该方法对一具有6个变电所、102条馈线的配电网络进行了测试。结果表明,文中所提方法是可行的、有效的。     

配电网自动化信息在不同传输协议下的性能分析

IEC61850标准可以为配电网自动化提供标准化、统一化的信息模型和信息交换模型,能有效解决终端的互操作性问题,但是仅仅解决了配电网自动化信息的描述问题,而相应的传输协议尚未得到统一规范,不同协议的传输性能缺乏定量化的分析手段。此外,随着IP网络在配电网自动化通信领域的不断推广,大量的配电网自动化信息可否在IP网络上进行传输也需要经过定量化的论证。针对这些问题,本文基于OPNET 仿真平台,对配电网自动化业务进行精细的建模,探讨了IEC60870-5-104和MMS+GOOSE等不同传输协议应用于配电网自动化信息传输的可行性,最后定量化地分析了不同传输协议下配电网自动化信息在IP网络中的传输性能。仿真结果表明,在IP网络中,IEC60870-5-104、MMS+GOOSE over TCP以及MMS+GOOSE over UDP三种传输协议的最大传输延时都在10ms以内,均能满足配电网自动化信息传输的实时性要求,但在遥测/遥信数据发送时间间隔较小的情况下,MMS+GOOSE over UDP的丢包率明显小于其余两种传输协议。#$NL关键词: IEC61850;配电网自动化;传输协议;IP网络;传输性能