PES Meetings

This letter presents a hybrid genetic algorithm (GA) method to solve optimal power flow (OPF) in a power system incorporating flexible AC transmission systems (FACTS). In the solution process GA is integrated with conventional OPF to select the best control parameters to minimize the total generation fuel cost and keep the power flows within the security limits. A case study using an IEEE test system is presented to demonstrate its applicability.     

A hybrid GA approach for OPF with consideration of FACTS devices

This letter presents a hybrid genetic algorithm (GA) method to solve optimal power flow (OPF) in power systems incorporating flexible AC transmission systems (FACTS). In the solution process, GA is integrated with conventional OPF to select the best control parameters to minimize the total generation fuel cost and keep the power flows within the security limits. A case study using an IEEE test system is presented to demonstrate its applicability     

Future of Dams

This paper presents an approach for a geometrical solution of an optimal power flow (OPF) problem for a two-bus power system (slack and PV buses). The algebraic equations for the calculation of the Lagrange multipliers and for the minimum losses value are obtained. These equations are used to validate the results obtained using an OPF program.     

A new modeling and solution method for optimal energy flow in electricity‐gas integrated energy system

With the increasing interdependency of electricity and gas, it is necessary to simultaneously investigate electric power system and natural gas system from the perspective of an electricity‐gas integrated energy system (EGIES). As an extension and integration of both optimal power flow (OPF) and optimal gas flow (OGF), optimal energy flow (OEF) is regarded as the cornerstone of the EGIES and lays an essential foundation for further research on the EGIES's operation and analysis considering stochastic conditions and contingency states. The objective of this paper is to develop a generalized mathematical model and a universally applicable simulation tool for the OEF problem. First, natural gas system is modeled in a way similar to electric power system according to electricity‐gas analogy analysis, where gas admittance, gas nodal admittance matrix, and the nodal equation of gas flow conservation are derived. Then, a generalized accurate OEF model is formulated by simultaneously integrating the OPF model and the OGF model as well as their coupling constraints in a unified modeling framework. Furthermore, an available hybrid optimization approach consisting of whale optimization algorithm, MATPOWER, hydraulic calculation iterative program, and nonstationary penalty function method is put forward to solve the OEF problem. The accuracy, feasibility, and applicability of the proposed modeling and solution method is finally demonstrated by analyzing Belgian 20‐node gas system combined with IEEE 30‐bus test system.     

Optimal location of Hybrid Flow Controller considering modified steady-state model

This paper introduces a modified power flow model for Hybrid Flow Controller (HFC) as an energy flow controller. The existing power flow models for Hybrid Flow Controller are suitable only for conventional power flow analysis, and are not applicable for OPF and optimal location analysis of FACTS devices. In this paper, some modifications were applied to the existing models to promote the accuracy and improve their conformability on any power system and hence leading to a precise steady-state analysis. The modified model and the existing model are investigated using different IEEE test systems and the results are compared together. The optimization method is numerically solved using Matlab and General Algebraic Modelling System (GAMS) software environments. The solution procedure uses Mixed Integer Non-Linear Programming (MINLP) and Relaxed Mixed Integer Non-Linear Programming (RMINLP) to solve the optimal location and setting of HFC incorporated in OPF problem considering the total fuel cost, power losses, and the system loadability as objective functions for single objective optimization problem and improve the power system operation.     

Economic operation of wind farm integrated system considering voltage stability

Wind farms interconnected to power system bring new challenges to power system economic operation. It is imperative to study how to solve optimal power flow (OPF) formulation with wind farms. In this paper, a multi-period optimal power flow (DOPF) is studied based on traditional OPF algorithm. According to the characteristic equations of asynchronous generator, the paper deduces a new algorithm that fits the DOPF formulation with wind farms. Based on the primal–dual interior point algorithm (PDIPM), a new modified algorithm is proposed. Besides, the voltage stability indicator, L-indicator, is also introduced into DOPF to demonstrate voltage stability of power system after wind farms incorporation. By taking SVC reactive power compensation into account, the paper analyzes its influences on system voltage stability. In addition, four different static load models are researched to reveal their effects on system-operating characteristics. An example shows the algorithm's effectiveness and computation performance of the proposed method and several conclusions are obtained as well.     

Contents

Optimal power flow (OPF) is one of the main functions of power system operation and control. Solving such problems requires efficient optimization algorithms. This letter describes the development of an efficient tabu search (TS) algorithm for solving the optimal power flow problem. The developed algorithm was tested against a modified IEEE-RTS-24-bus test system. The results were compared with ones obtained from sequential quadratic programming (SQP) and evolutionary programming (EP) techniques. All approaches give more or less the same optimal solutions. Tabu search is the most efficient technique among these, since it consumes minimum computing time and provides accurate solutions.     

Multiobjective clearing of reactive power market in deregulated power systems

This paper presents a day-ahead reactive power market which is cleared in the form of multiobjective context. Total payment function (TPF) of generators, representing the payment paid to the generators for their reactive power compensation, is considered as the main objective function of reactive power market. Besides that, voltage security margin, overload index, and also voltage drop index are the other objective functions of the optimal power flow (OPF) problem to clear the reactive power market. A Multiobjective Mathematical Programming (MMP) formulation is implemented to solve the problem of reactive power market clearing using a fuzzy approach to choose the best compromise solution according to the specific preference among various non-dominated (pareto optimal) solutions. The effectiveness of the proposed method is examined based on the IEEE 24-bus reliability test system (IEEE 24-bus RTS).     

基于改进多目标蝙蝠算法的洛河流域水库优化调度

为了发挥水资源综合利用的最大效益,实现水库发电和供水效益双赢的优化调度需求,以水库发电量最大和水库下游用水区域总缺水量最小为目标建立了多目标优化调度模型。同时,提出改进多目标蝙蝠算法(IMOBA)用于求解多目标优化调度模型,该算法引入外部精英蝙蝠集EBS()来存储算法寻优过程中的非劣解,设计一种基于混沌原理的脉冲发射率生成机制来增强算法的搜索能力,并加入变异操作以提高算法的种群多样性。将改进多目标蝙蝠算法应用在洛河流域故县水库,得到丰、平、枯三种典型年下的故县水库调度方案集。结果表明,IMOBA算法合理有效且优于多目标蝙蝠算法(MOBA),能较好地反映洛河流域故县水库的发电和供水要求。同时验证了多目标优化调度模型的可行性,为流域水库多目标优化调度方案的制定提供了新途径。     

Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties

Increasing penetration of wind power in power systems causes difficulties in system planning due to the uncertainty and non dispatchability of the wind power. The important issue, in addition to uncertain nature of the wind speed, is that the wind speeds in neighbor locations are not independent and are in contrast, highly correlated. For accurate planning, it is necessary to consider this correlation in optimization planning of the power system. With respect to this point, this paper presents a probabilistic multi-objective optimal power flow (MO-OPF) considering the correlation in wind speed and the load. This paper utilizes a point estimate method (PEM) which uses Nataf transformation. In reality, the joint probability density function (PDF) of wind speed related to different places is not available but marginal PDF and the correlation matrix is available in most cases, which satisfy the service condition of Nataf transformation. In this paper biogeography based optimization (BBO) algorithm, which is a powerful optimization algorithm in solving problems including both continuous and discrete variables, is utilized in order to solve probabilistic MO-OPF problem. In order to demonstrate performance of the method, IEEE 30-bus standard test case with integration of two wind farms is examined. Then the obtained results are compared with the Monte Carlo simulation (MCS) results. The comparison indicates high accuracy of the proposed method.     

MFACTS System Studies

The unified power flow controller (UPFC) combines the advantageous features of both shunt and series compensations; therefore, it is an effective device that can adjust power system parameters in order to increase power transfer capability, stabilize the system and improve the economics of a power system. This paper presents the exact pi-model of the UPFC-inserted transmission lines from which the injection-model using two-port networks is derived. The equations derived in this paper are applied to a small test system, where the impact of UPFC on OPF results is shown.     

基于改进多种群遗传算法的节能环保多目标优化模型

电力系统多目标经济负荷分配问题是个非线性、高维的复杂优化问题。提出基于交互式的改进多种群遗传算法,通过引入精英策略和移民策略的多种群遗传算法可以有效地克服标准遗传算法容易陷入局部最优解、易早熟的缺陷。针对文中提出的煤耗和排放2个目标函数,提出了基于目标满意度和总体协调度的交互式多目标处理方法,通过寻求向量空间内满足总体协调度的最短”欧氏距离”,来贴近决策者满意的理想值,解决了各目标函数之间最优解的相互冲突,达到协调好各个目标函数的目的,充分体现了决策者的意愿。试验算例表明,该算法能够有效地解决电力系统多目标经济负荷分配问题。     

基于随机潮流的分布式电源多目标优化配置

风光等间歇性分布式电源(DG)出力具有随机性和波动性,在规划过程中采用确定性变量和约束处理间歇性DG出力与实际发电情况不符,难以得到真实的规划结果,同时也会造成不必要的资源浪费。对此,采用机会约束规划方法,建立综合投资效益、网损和电压偏差的DG多目标优化配置模型,采用基于半不变量法的随机潮流结果对相关机会约束进行概率校验,并将累积排序操作、精英保留操作和拥挤距离操作引入随机黑洞粒子群算法,提出一种改进多目标粒子群算法对模型求解。PGE-33节点配电系统仿真结果表明,DG合理接入与优化配置能有效提高电网运行经济性和供电可靠性,且从概率角度分析源荷侧不确定因素对电压水平的影响,评估规划方案与实际电网运行契合度,辅助规划人员进行科学决策。     

Optimal operation of autonomous microgrid including wind turbines

This paper gives a novel hybrid optimization method to find optimal sitting and operation of an autonomous MG at the same time. The operation is optimized via finding the optimal droop gain parameters of DGs. The optimization problem is formulated as a multi-objective problem where the objectives are applied to minimize the fuel consumption of DGs and to improve the voltage profile and stability of MG subject to operational and security constraints. A hybrid algorithm, named HS-GA, is developed to solve the paper optimization problem. A new formulation of power flow is derived to run the proposed algorithm where the steady state frequency of system, reference frequency, reference voltage and droop coefficients of DGs, based on a droop controller, are considered as optimization variables. The performance of the paper approach is compared with other optimization and non-optimization methods in MG with 33and 69 buses using MATLAB. The performance of the proposed method is compared with a method that the parameters of DGs are pre-determined without conducting any optimization process. The results show, which optimized droop parameters improves the operation of the MG.     

矢量化技术在电力系统高性能计算中的应用

将矢量化技术应用到电力系统计算中可以极大的提高程序运行速度并降低建模和算法开发的复杂程度。介绍了矢量化技术的基本原理及其在高性能科学数值计算领域的应用情况．推导了直角坐标和极坐标下潮流计算的相关矢量化计算式,说明了矢量化在电力系统建模和算法实现中的应用可行性。设计和开发了电力系统矢量化运算库,并基于该库开发了最优潮流程序,通过算例数据说明了矢量化技术能够提高计算速度。提出了矢量化电力系统程序开发的解决方案,该方案缩短了高性能计算程序的开发周期,加速了算法的实用化进程。     

Interactive DE for solving combined security environmental economic dispatch considering FACTS technology

This paper presents an efficient interactive differential evolution (IDE) to solve the multi-objective security environmental/economic dispatch (SEED) problem considering multi shunt flexible AC transmission system (FACTS) devices. Two sub problems are proposed.The first one is related to the active power planning to minimize the combined total fuel cost and emissions, while the second is a reactive power planning (RPP) using multi shunt FACTS device based static VAR compensator (SVC) installed at specified buses to make fine corrections to the voltage deviation, voltage phase profiles and reactive power violation. The migration operation inspired from biogeography-based optimization (BBO) algorithm is newly introduced in the proposed approach, thereby effectively exploring and exploiting promising regions in a space search by creating dynamically new efficient partitions. This new mechanism based migration between individuals from different subsystems makes the initial partitions to react more by changing experiences. To validate the robustness of the proposed approach, the proposed algorithm is tested on the Algerian 59-bus electrical network and on a large system, 40 generating units considering valve-point loading effect. Comparison of the results with recent global optimization methods show the superiority of the proposed IDE approach and confirm its potential for solving practical optimal power flow in terms of solution quality and convergence characteristics.     

A practical multi-objective PSO algorithm for optimal operation management of distribution network with regard to fuel cell power plants

In this paper a novel Multi-objective fuzzy self adaptive hybrid particle swarm optimization (MFSAHPSO) evolutionary algorithm to solve the Multi-objective optimal operation management (MOOM) is presented. The purposes of the MOOM problem are to decrease the total electrical energy losses, the total electrical energy cost and the total pollutant emission produced by fuel cells and substation bus. Conventional algorithms used to solve the multi-objective optimization problems convert the multiple objectives into a single objective, using a vector of the user-predefined weights. In this conversion several deficiencies can be detected. For instance, the optimal solution of the algorithms depends greatly on the values of the weights and also some of the information may be lost in the conversion process and so this strategy is not expected to provide a robust solution. This paper presents a new MFSAHPSO algorithm for the MOOM problem. The proposed algorithm maintains a finite-sized repository of non-dominated solutions which gets iteratively updated in the presence of new solutions. Since the objective functions are not the same, a fuzzy clustering technique is used to control the size of the repository, within the limits. The proposed algorithm is tested on a distribution test feeder and the results demonstrate the capabilities of the proposed approach, to generate true and well-distributed Pareto-optimal non-dominated solutions of the MOOM problem.     

Study on optimal configuration of the grid-connected wind–solar–battery hybrid power system

The capacity allocation of each energy unit in the grid-connected wind–solar–battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind–solar–battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind–solar–battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.     

Optimal hybrid PV/WT/FC sizing and distribution system reconfiguration using multi-objective artificial bee colony (MOABC) algorithm

In this paper, a novel multi-objective artificial bee colony algorithm is presented to solve the distribution system reconfiguration and hybrid (photo voltaic/wind turbine/fuel cell) energy system sizing. The purposes of the multi-objective optimization problem include the total power loss, the total electrical energy cost, and the total emission produced by hybrid energy system and the grid minimization, and the voltage stability index (VSI) of distribution system maximization. In the proposed algorithm, an external archive of non-dominated solutions is kept which is updated in each iteration. In addition, for preserving the diversity in the archive of Pareto solutions, the crowding distance operator is used. This algorithm is tested on 33 bus distribution systems and obtained non-dominated solutions are compared with the well-known NSGA-II and MOPSO methods. The solutions obtained by the MOABC algorithm have a good quality and a better diversity of the Pareto front compared with those of NSGA-II and MOPSO methods.     

基于单机无穷大等效的暂态稳定约束最优潮流算法

为解决传统的考虑暂态稳定约束的最优潮流(TSOPF)方法暂态约束条件数量庞大、计算复杂性高等问题,可通过修改Matpower工具包和PSS/E软件,进而实现了一种故障初始时刻考虑暂态约束的TSOPF算法,通过对等效系统初始稳态功角偏差的约束,一般TSOPF方法中数量庞大、复杂的暂态约束条件被简化为数量唯一的稳态约束条件,TSOPF方法的问题规模被降低到与传统最优潮流问题相同的程度。基于IEEE3机9节点系统和10机新英格兰系统的算例,验证了该算法的有效性。