Optimal power flow using differential evolution algorithm

This paper presents an efficient and reliable evolutionary-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs differential evolution algorithm for optimal settings of OPF problem control variables. The proposed approach is examined and tested on the standard IEEE 30-bus test system with different objectives that reflect fuel cost minimization, voltage profile improvement, and voltage stability enhancement. The proposed approach results are compared with the results reported in the literature. The results show the effectiveness and robustness of the proposed approach.     

Artificial bee colony algorithm for solving multi-objective optimal power flow problem

This paper presents a new and efficient method for solving optimal power flow (OPF) problem in electric power systems. In the proposed approach, artificial bee colony (ABC) algorithm is employed as the main optimizer for optimal adjustments of the power system control variables of the OPF problem. The control variables involve both continuous and discrete variables. Different objective functions such as convex and non-convex fuel costs, total active power loss, voltage profile improvement, voltage stability enhancement and total emission cost are chosen for this highly constrained nonlinear non-convex optimization problem. The validity and effectiveness of the proposed method is tested with the IEEE 9-bus system, IEEE 30-bus system and IEEE 57-bus system, and the test results are compared with the results found by other heuristic methods reported in the literature recently. The simulation results obtained show that the proposed ABC algorithm provides accurate solutions for any type of the objective functions.     

Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization

The optimization is an important role in the wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. Using adaptive real coded biogeography-based optimization (ARCBBO), we present the optimization of various objective functions of an optimal power flow (OPF) problem in a power system. We aimed to determine the optimal settings of control variables for an OPF problem. The proposed approach was tested on a standard IEEE 30-bus system and an IEEE 57-bus system with different objective functions. Simulation results reveal that the proposed ARCBBO approach is effective, robust and more accurate than current methods of power flow optimization in literature.     

Determination of load shedding to provide voltage stability

A computationally simple algorithm is developed for studying the load shedding problem in emergencies where an ac power flow solution cannot be found for the stressed system. The proposed algorithm is divided into two sub-problems: restoring solvability sub-problem and improving voltage stability margin (VSM) sub-problem. Linear optimization (LP)-based optimal power flow (OPF) is applied to solve each sub-problem. In restoring solvability sub-problem, rather than taking restoring power flow solvability as direct objective function, the objective function of maximization of voltage magnitudes of weak buses is employed. In VSM sub-problem, the traditional load shedding objective is extended to incorporate both technical and economic effects of load shedding and the linearized VSM constraint was added into the LP-based OPF. Case studies with a real 682 bus system are presented. The simulation results show that the proposed load shedding algorithm is effective, fast in finding the load shedding scheme to solve the problem of restoring solvability and improving VSM.     

Optimal power flow for distribution networks using gravitational search algorithm

This paper presents a gravitational search algorithm (GSA)-based approach to solve the optimal power flow (OPF) problem in a distribution network with distributed generation (DG) units. The OPF problem is formulated as a nonlinear optimization problem with equality and inequality constraints, where optimal control settings in case of fuel cost minimization of DG units, power loss minimization in the distribution network, and finally simultaneous minimization of the fuel cost and power loss are obtained. The proposed approach is tested on an 11-node test system and on a modified IEEE 34-node test system. Simulation results obtained from the proposed GSA approach are compared with that obtained using a genetic algorithm approach. The results show the effectiveness and robustness of the proposed GSA approach.     

基于树木生长算法的含UPFC的最优潮流计算

最优潮流(OPF)计算是一个非凸优化问题,统一潮流控制器(UPFC)的引入增加了OPF问题的非凸程度,使得基于内点法的传统优化算法难以获取全局最优解。文中提出基于树木生长算法(TGA)的计及UPFC的最优潮流计算方法,将发电成本与有功网损、电压偏移加权作为目标函数,并考虑网络与UPFC设备的安全运行约束,优化了OPF模型。最后基于IEEE 30节点系统以及南京西环网116节点实际系统进行算例测试,对比TGA、粒子群与内点法的结果,并使用蒙特卡洛方法对不同的启发式算法分别进行50次计算,验证了TGA具有更好的求解精度与鲁棒性。     

A new Optimal reactive power planning based on Differential Search Algorithm

This paper proposes a new multi-level methodology based on the optimal reactive power planning. The developed methodology is designed to solve the problem of the non-feasibility solution of the fuel cost minimization problem (for a given operating point) where the classical method such as interior point method (IPM) is applied. The proposed solution to solve this problem is based on the application of the optimal reactive power planning problem considering voltage stability as the initial solution of the fuel cost minimization problem. To improve the latter the load voltage deviation problem is applied to improve the system voltage profile. For à good result improvement, the reactive power planning problem and the load voltage deviation minimization problems are solved using a new optimization method namely the Differential Search Algorithm (DSA). Moreover, the fuel cost minimization problem is solved using IPM. To identify the candidate placements of compensation devices for the optimal reactive power planning problem, a new voltage stability index namely: The Fast Voltage Stability Index (FVSI) is used. The methodology has been tested with the equivalent Algerian power system network, and the simulation results show the effectiveness of the proposed approach to improve the reactive power planning problem and to minimize the system voltage deviation.     

求解非光滑燃料费用函数的基于进化规划的机组最优潮流

提出求解具有非光滑燃料费用函数的存在爬坡率限制的最优潮流方法。针对两次、阶梯形、联合循环机组的非光滑燃料费用函数,介绍一个基于进化规划的算法。在该算法中,为避免早熟,交叉操作随后代的数目非线性变化。介绍了所提出的进化算法应用于有线路约束的IEEE30节点系统和印度62节点系统的情况。以MVA为单位的线路潮流直接采用牛顿-拉夫逊法计算。算例证明所提出的进化算法简单,对求解具有非光滑燃料费用函数的存在很多约束的最优潮流问题有效。     

Multi-objective harmony search algorithm for optimal power flow problem

This paper proposes a multi-objective harmony search (MOHS) algorithm for optimal power flow (OPF) problem. OPF problem is formulated as a non-linear constrained multi-objective optimization problem where different objectives and various constraints have been considered into the formulation. Fast elitist non-dominated sorting and crowding distance have been used to find and manage the Pareto optimal front. Finally, a fuzzy based mechanism has been used to select a compromise solution from the Pareto set. The proposed MOHS algorithm has been tested on IEEE 30 bus system with different objectives. Simulation results are also compared with fast non-dominated sorting genetic algorithm (NSGA-II) method. It is clear from the comparison that the proposed method is able to generate true and well distributed Pareto optimal solutions for OPF problem.     

Security constrained optimal power flow considering detailed generator model by a new robust differential evolution algorithm

This paper presents a new multiobjective model, including two objective functions of generation cost and voltage stability margin, for optimal power flow (OPF) problem. Moreover, the proposed OPF formulation contains a detailed generator model including active/reactive power generation limits, valve loading effects, multiple fuel options and prohibited operating zones of units. Furthermore, security constraints, including bus voltage limits and branch flow limits in both steady state and post-contingency state of credible contingencies, are also taken into account in the proposed formulation. To solve this OPF problem a novel robust differential evolution algorithm (RDEA) owning a new recombination operator is presented. The proposed RDEA has a minimum number of adjustable parameters. Besides, a new constraint handling method is also presented, which enhances the efficiency of the RDEA to search the solution space. To show the efficiency and advantages of the proposed solution method, it is applied to several test systems having complex solution spaces and compared with several of the most recently published approaches.     

Impact of Optimal Unified Power Flow Controller in Electrical Transmission Systems in Reducing Transmission Cost

This paper presents an approach to optimal placement of optimal unified power flow controller (OUPFC) in electrical transmission systems utilizing genetic algorithm (GA), while reducing transmission systems cost using MATLAB and MATPOWER. The proposed approach is based on optimal power flow (OPF) considering optimization of power systems operation conditions. In order to determine the appropriate place for installation of OUPFC, while considering power injection model of this controller, OPF is utilized to obtain multi-objective function of the optimization problem. In this regard, the objective function comprises generation cost, transmission cost, and OUPFC installation cost. The proposed approach is applied to IEEE 30-bus test system, where the obtained results demonstrate remarkable reduction in overall cost of power system.     

基于半定规划法的含分布式潮流控制器最优潮流

分布式潮流控制器能够灵活地提升现有线路的输电能力,从而降低系统运行成本,但该设备的引入会增加电力系统最优潮流问题的复杂度与非凸程度。针对分布式潮流控制器的结构及原理进行了分析,提出一种简化的稳态功率模型,并考虑到装置运行时各串联单元自身容量限制,给出实际电网中分布式潮流控制器线路的潮流可行域。基于此,采用对初值选取不敏感的半定规划法建立含分布式潮流控制器的系统最优潮流模型,并选用原对偶内点法进行求解。算例测试结果表明,所提方法能有效解决含分布式潮流控制器的系统潮流优化问题。     

Planning of multi-type FACTS devices in restructured power systems with wind generation

Many electrical power systems are changing from a vertically integrated entity to a deregulated, open-market environment. This paper proposes an approach to optimally allocate multi-type flexible AC transmission system (FACTS) devices in restructured power systems with wind generation. The objective of the approach is to maximize the present value of long-term profit. Many factors like load variation, wind generation variation, generator capacity limit, line flow limit, voltage regulation, dispatchable load limits, generation rescheduling cost, load shedding cost, and multilateral power contracts are considered in problem formulation. The proposed method accurately evaluates the annual costs and benefits obtainable by FACTS devices in formulating the large-scale optimization problem under both normal condition and possible contingencies. The overall problem is solved using both Particle Swarm Optimization (PSO) for attaining optimal FACTS devices allocation as main problem and optimal power flow as sub optimization problem. The efficacy of the proposed approach is demonstrated for modified IEEE 14-bus test system and IEEE 118-bus test system.     

Optimal power flow by a fuzzy based hybrid particle swarm optimization approach

This paper presents a fuzzy based hybrid particle swarm optimization (PSO) approach for solving the optimal power flow (OPF) problem with uncertainties. Wind energy systems are being considered in the study power systems. OPF is an optimization problem which minimizes the total thermal unit fuel cost, total emission, and total real power loss while satisfying physical and technical constraints on the network. When performing the OPF problem in conventional methods, the load demand and wind speed must be forecasted to prevent errors. However, actually there are always errors in these forecasted values. A characteristic feature of the proposed fuzzy based hybrid PSO method is that the forecast load demand and wind speed errors can be taken into account using fuzzy sets. Fuzzy set notations in the load demand, wind speed, total fuel cost, total emission, and total real power loss are developed to obtain the optimal setting under an uncertain environment. To demonstrate the effectiveness of the proposed method, the OPF problem is performed on the IEEE 30- and 118-Bus test systems.     

一种确定电力系统最优安全运行点的新方法

针对当前电力系统运行点趋于稳定边缘的现象,提出了一种确定电力系统最优安全运行点的新方法.文中考虑电压安全裕度的改进的多目标最优潮流模型在确保系统运行于理想负荷裕度的同时优化系统的综合运行成本.该方法采用连续潮流法与传统最优潮流模型确定多目标最优潮流模型的初始权重系数,然后用预测-校正原对偶内点法求解改进模型.仿真结果表明,文中提出的改进模型与基于目标规划的多目标最优潮流模型相比,不仅能有效确定系统的最优安全运行点,而且在系统运行偏离理想负荷裕度时具有二次惩罚策略,其优化目标将最终迫使系统运行点向理想负荷点靠近.     

应用粒子群优化算法求解可用输电能力

在电力市场环境下,诸多问题(例如实时电价、网络阻塞等)都需要最优潮流作为理想的工具.本文以最优潮流为基础,应用一种简单有效、且收敛性很好的演化计算算法--粒子群优化算法(PSO)进行可用输电能力(ATC)问题的求解.根据约束条件的越限量大小,动态地调整罚函数,在保证全局搜索能力的基础上改进了收敛速度.应用此算法对IEEE-30节点系统进行了可用输电能力计算,并与传统的最优潮流算法进行了比较,结果表明该算法的有效性,具有实用意义.     

考虑电压稳定约束的最优潮流

采用指数负荷模型研究了有载调压变压器对系统最优潮流的影响。在阐述电压稳定性L指标的基础上,将L指标引入传统最优潮流中形成电压稳定约束的最优潮流,运用原-对偶内点法求解该模型。算例结果表明,该模型鲁棒性较好,能更加真实地反映系统实际运行情况。不同静态负荷模型对系统电压稳定性和经济性有一定的影响,系统电压稳定性的提高是以牺牲经济性为代价的,在考虑电压稳定性时,有载调压变压器的加入可以有效降低系统燃料费用,平抑系统有功出力和燃料费用的波动,将波动维持在一个较小的范围内。     

Cost-based reactive power pricing with voltage security consideration in restructured power systems

In the restructuring power industry, voltage security has become a challenging problem since power systems tend to operate closer to security boundaries and as a consequence, the voltage instability, which is caused by insufficient reactive power supply, poses a serious threat to system security and reliability. Establishing an equitable and effective reactive power market with consideration of the voltage security problem is very important to provide a reliable restructured power system. Therefore, this paper proposes a cost-based reactive power pricing, which can integrate the reactive power cost minimization and the voltage security problem into the optimal power flow (OPF) problem, and the sequential quadratic programming (SQP) is employed to solve the optimization problem. The effectiveness of the proposed method is verified using a modified IEEE 14-bus system. A study on the effects of the voltage stability margin (VSM) requirement under normal condition and contingencies on the reactive power cost is also presented.     

Optimal reactive power dispatch using quasi-oppositional teaching learning based optimization

This paper presents a newly developed teaching learning based optimization (TLBO) algorithm to solve multi-objective optimal reactive power dispatch (ORPD) problem by minimizing real power loss, voltage deviation and voltage stability index. To accelerate the convergence speed and to improve solution quality quasi-opposition based learning (QOBL) concept is incorporated in original TLBO algorithm. The proposed TLBO and quasi-oppositional TLBO (QOTLBO) approaches are implemented on standard IEEE 30-bus and IEEE 118-bus test systems. Results demonstrate superiority in terms of solution quality of the proposed QOTLBO approach over original TLBO and other optimization techniques and confirm its potential to solve the ORPD problem.     

Optimal power flow with emission and non-smooth cost functions using backtracking search optimization algorithm

Economic operation of electric energy generating systems is one of the prevailing problems in energy systems. In this paper, a new method called the Backtracking Search Optimization Algorithm (BSA) is proposed for solving the optimal power flow problem. This method is tested for 16 different cases on the IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus test systems. In addition to the traditional generating fuel cost, multi-fuels options, valve-point effect and other complexities have been considered. Furthermore, different objectives such as voltage profile improvement, voltage stability enhancement and emission reduction are considered. The obtained results are compared with those obtained using some well-known optimization algorithms. This comparison highlights the effectiveness of the BSA method for solving different OPF problems with complicated and non-smooth objective functions.