Swarm intelligence based algorithms for reactive power planning with Flexible AC transmission system devices

In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive Particle Swarm Optimization) and EPSO (Evolutionary Particle Swarm Optimization) are used for the optimal setting of the Var sources and FACTS devices. The result obtained with the proposed approach is compared with the result found by the conventional RPP (Reactive power planning) approach where shunt capacitors, transformer tap setting arrangements and reactive generations of generators are used as planning variables. It is observed that reactive power planning with FACTS devices yields much better result in terms of reducing active power loss and total operating cost of the system even considering the investment costs of FACTS devices.     

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 BAT search algorithm for generation reallocation with unified power flow controller

Optimal power flow with generation reallocation is a suitable method for better utilization of the existing system. In recent years, Flexible AC Transmission System (FACTS) devices, have led to the development of controllers that provide controllability and flexibility for power transmission. Out of the FACTS devices unified power flow controller (UPFC) is a versatile device, capable of controlling the power system parameters like voltage magnitude, phase angle and line impedance individually or simultaneously. The main aim of this paper is to minimize real power losses in a power system using BAT search algorithm without and with the presence of UPFC. Minimization of real power losses is done by considering the power generated by generator buses, voltage magnitudes at generator buses and reactive power injection from reactive power compensators. The proposed BAT algorithm based Optimal Power Flow (OPF) has been tested on a 5 bus test system and modified IEEE 30 bus system without and with UPFC. The results of the system with and without UPFC are compared in terms of active power losses in the transmission line using BAT algorithm. The obtained results are also compared with Genetic algorithm (GA).     

Allocation of multi-type FACTS devices using multi-objective genetic algorithm approach for power system reinforcement

This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission systems (FACTS) devices in a power system using a multi-objective optimization function. Thyristor controlled series compensator (TCSC) and static var compensator (SVC) are the utilized FACTS devices. Our objectives are: active power loss reduction, new introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, are considered in the optimum allocation. A multi-objective genetic algorithm (MOGA) is used to approach the Pareto-optimal front (non-dominated) solutions. In addition, the estimated annual load profile has been utilized in a sequential quadratic programming (SQP) optimization sub-problem to the optimum siting and sizing of FACTS devices. IEEE 14-bus Network is selected to validate the performance and effectiveness of the proposed method.     

Optimal power flow with FACTS devices by hybrid TS/SA approach

In this paper, a hybrid tabu search and simulated annealing (TS/SA) approach is proposed to minimize the generator fuel cost in optimal power flow (OPF) control with flexible AC transmission systems (FACTS) devices. The problem is decomposed into the optimal setting of FACTS parameters subproblem that is searched by the hybrid TS/SA approach and the OPF with fixed FACTS parameters subproblem that is solved by the quadratic programming (QP). Two types of FACTS devices are used: thyristor-controlled series capacitor (TCSC) and thyristor-controlled phase shifting (TCPS). Test results on the modified IEEE 30 bus system indicates that the proposed hybrid TS/SA approach can obtain better solutions and require less CPU times than genetic algorithm (GA), SA, or TS alone.     

Assessment of techno-economic contribution of FACTS devices to power system operation

In contemporary power system studies, the optimal allocation and utilization of Flexible AC Transmission System (FACTS) devices are important issues primarily due to their cost. In this study four types of FACTS devices (Static VAr compensator (SVC), Thyristor-Controlled Series Capacitor (TCSC), Thyristor-Controlled Voltage Regulator (TCVR), and Thyristor-Controlled Phase Shifting Transformer (TCPST)) are optimally placed in a multi-machine power system to reduce the overall costs of power generation. The placement methodology considers simultaneously the cost of generated active and reactive powers and cost of selected FACTS devices for a range of operating conditions. The optimal power flow (OPF) and genetic algorithm (GA) based optimization procedure are employed to solve the allocation task. The net present value (NPV) method is used to assess the economic value of the proposed methodology. In addition to net reduction in generation cost allocated FACTS devices increased power transfer across the network and improved damping of electromechanical oscillations.     

Brainstorm optimisation algorithm (BSOA): An efficient algorithm for finding optimal location and setting of FACTS devices in electric power systems

In electric power systems, finding optimal location and setting of flexible AC transmission system (FACTS) devices represents a difficult optimisation problem. This is due to its discrete, multi-objective, multi-modal and constrained nature. Finding near-global solutions in such a problem is very demanding. Brainstorm optimisation algorithm (BSOA) is a novel promising heuristic optimisation algorithm inspired by brainstorming process in human beings. In this paper, BSOA is employed to find optimal location and setting of FACTS devices. Static var compensators (SVC’s) and thyristor controlled series compensators (TCSC’s) are used as FACTS devices. FACTS allocation problem is formulated as a multi-objective problem whose objectives are voltage profile enhancement, overload minimisation and loss minimisation. The results of applying BSOA to FACTS allocation problem in IEEE 57 bus system demonstrate its high efficacy in solving this problem both with TCSC and SVC units. BSOA leads to better voltage profile and lower losses than particle swarm optimisation (PSO), genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), hybrid of genetic algorithm and pattern search (GA–PS), backtracking search algorithm (BSA), gravitational search algorithm (GSA) and asexual reproduction optimisation (ARO). The findings of this research can be used by power system decision makers in order to establish a better voltage profile and lower voltage deviations during contingencies.     

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.     

基于分布式电源有功无功调节能力的配电网无功规划

传统的无功规划方法在应对小概率极端电压场景时往往要求配电网投资大量的无功补偿装置。为此,基于分布式电源及负荷场景,提出一种配电网无功规划模型,该模型充分利用了分布式电源的有功、无功调节能力,在小概率极端电压场景下将分布式电源有功调节作为一种附加电压调节手段,并以无功补偿装置投资费用和分布式电源有功调节费用之和最小为目标以减少系统总支付费用。提出一种嵌入原始对偶内点法的粒子群优化算法对模型进行求解。通过对自定义IEEE 30节点系统进行仿真分析,验证了所提模型的经济性和所提算法的有效性。     

Optimal location and sizing of Unified Power Flow Controller (UPFC) to improve dynamic stability: A hybrid technique

In this paper a hybrid technique based optimal location and sizing of UPFC to improve the dynamic stability is proposed. Here, the maximum power loss bus is identified at the most favorable location for fixing the UPFC, because the generator outage affects the power flow constraints such as power loss, voltage, real and reactive power flow. The optimum location has been determined using the Artificial Bees Colony (ABC) algorithm. Depending on the violated power flow quantities the Gravitational Search Algorithm (GSA) optimizes the required quantity of the UPFC to recover the initial operating condition. Then the proposed work is implemented in the MATLAB/simulink platform and the performance is evaluated by using the comparison, at different techniques like ABC and GSA. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem.     

Analysis of FACTS devices on Security Constrained Unit Commitment problem

This paper focuses on solving Security Constrained Unit Commitment (SCUC) problem using ABC algorithm incorporating FACTS devices. The objective of the SCUC problem is to obtain the minimum operating cost simultaneously maintaining the security of the system. The SCUC problem is decomposed into Unit Commitment (UC), the master problem and Security-Constrained Economic Dispatch (SCED) as the sub-problem. The existing generation constraints, such as hourly power demand, system reserves, and minimum up/down time limits, ramp up/down limits are included in the SCUC problem formulation. The ability of FACTS devices to control the power flow through designated routes in transmission lines and thereby reducing the overloading of lines are studied. The solution of SCUC problem is also analyzed during a single line outage contingency. The SCUC is carried out incorporating FACTS devices such as SVC, TCSC, STATCOM, SSSC, UPFC and IPFC. The modeling of the FACTS devices within the power system network and finding a suitable location are discussed. The SCUC has been solved and validated on an IEEE 118-bus test system and a practical South Indian 86 bus utility.     

统一潮流控制器(UPFC)对次同步振荡的影响及抑制策略

FACTS等快速控制装置在一定条件下可能激发电力系统的次同步振荡问题,导致发电机轴系失稳,造成重大事故,危害电力系统的安全稳定运行。UPFC作为一种新型FACTS元件,虽然能实现母线电压控制和线路有功、无功功率的调节,但对次同步振荡影响的研究较少。同时,目前的UPFC阻尼控制器多针对低频振荡模态。故在搭建UPFC模型的基础上,运用测试信号法,研究了系统运行参数和UPFC电压有功控制等对次同步振荡的影响,并设计了相应的UPFC附加阻尼控制器。在IEEE第二标准测试系统上的计算机仿真说明,该控制器能有效提高多个扭振模态的电气阻尼,抑制系统的次同步振荡。     

Constraints violation handling of SSSC with multi‐control modes in Newton–Raphson load flow algorithm

The static synchronous series compensator (SSSC ) is an important component of flexible AC transmission systems (FACTS ) devices. SSSC can be used to control the active and reactive power flow in transmission lines. This paper presents a simplified model for SSSC in Newton–Raphson (NR ) load flow algorithm. It also presents strategies for handling the operating constraints of SSSC including the series‐injected voltage and current passing through this device. The presented strategies are based on modifying the specified active and reactive powers with the maximum limits of the operating constraints. However, the SSSC is simply implemented in NR load flow algorithm based on the power injection approach. In this model, the SSSC is represented as injected loads as a function of the desired power flow through the transmission line. The main advantages of this model are avoiding the modification of Jacobin matrix and reducing the complexities of incorporating SSSC in the load flow algorithm. Moreover, the resistance of SSSC is considered in this model. Standard IEEE 14‐bus and 30‐bus test systems are used to verify the performance of the developed model and strategies handling the constraints of the SSSC model. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A new method for secured optimal power flow under normal and network contingencies via optimal location of TCSC

In the deregulated power industry, private power producers are increasing rapidly to meet the increase demand. The purpose of the transmission network is to pool power plants and load centers in order to supply the load at a required reliability, maximum efficiency and at lower cost. As power transfer increases, the power system becomes increasingly more difficult to operate and insecure with unscheduled power flows and higher losses. FACTS devices such as Thyristor Controlled Series Compensator (TCSC) can be very effective to power system security. Proper location of TCSC plays key role in optimal power flow solution and enhancement of system performance without violating the security of the system. This paper applied min cut algorithm to select proper location of TCSC for secured optimal power flow under normal and contingencies operating condition. Proposed method requires a two-step approach. First, the optimal location of the TCSC in the network must be ascertained by min cut algorithm and then, the optimal power flow (OPF) with TCSC under normal and contingencies operating condition is solved. The proposed method was tested and validated for locating TCSC in Six bus, IEEE 14-, IEEE-30 and IEEE-118 bus test systems. Results show that the proposed method is good to select proper location of TCSC for secured OPF.     

Power flow control approach to power systems with embedded FACTS devices

This paper focuses on developing an approach to steady-state power flow control of flexible AC transmission systems (FACTS) device-equipped power systems. Based on a power-injection model of FACTS devices and an optimal power flow model, a novel versatile power flow control approach is formulated, which is capable of implementing power flow control incorporating any FACTS device flexibly. Different from existing FACTS device control approaches, the active and (or) reactive power injections are taken as independent control variables. Therefore, using this method, Jacobian matrix need not be changed, although various FACTS devices possess different physical models and different control parameters. Furthermore, it enables the integration of FACTS devices into the existing power system analysis and control programs efficiently. Physical limits of the FACTS devices are also considered in the model. Numerical results on a reduced practical system and a 1500-bus practical system with various FACTS devices are presented to illustrate the vigorousness of the proposed approach.     

Network loss minimization with voltage security using differential evolution

This paper presents a differential evolution (DE) based optimal power flow (OPF) for reactive power dispatch in power system planning studies. DE is a simple population-based search algorithm for global optimization and has a minimum number of control parameters. The problem is formulated as a mixed integer non-linear optimization problem taking into account both continuous and discrete control variables. The proposed method determines control variable settings such as generator voltages (continuous), tap positions (discrete) and the number of shunt reactive compensation devices to be switched (discrete) for real power loss minimization in the transmission system using DE algorithm. Most of the evolutionary algorithm applications to optimization problems apply penalty function approach to handle the inequality constraints, involving penalty coefficients. The correct combination of these coefficients can be determined only by a trial and error basis. In the proposed approach, the inequality constraints are handled by penalty parameterless scheme. Voltage security margin was evaluated using continuation power flow (CPF), to ensure the feasibility of the optimal control variable setting. The suitability of the method was tested on IEEE 14 and IEEE RTS 24-bus systems and results compared with sequential quadratic programming (SQP) method. The DE provides near global solutions comparable to that obtained using SQP.     

有源配电网分布式电源与智能软开关三层协调规划模型

当前配电系统调节能力的欠缺严重限制了高比例可再生分布式电源(DG)的广泛并网。在以智能软开关(SOP)为代表的电力电子装置接入系统的趋势下,考虑系统规划与运行优化相结合,协调DG运营商与配电公司的利益需求,提出一种有源配电网DG与SOP三层协调规划模型。上层以DG运营商单位容量收益最大化为目标进行DG规划,中层以配电公司年综合成本最小化为目标进行SOP规划,下层以场景内运行成本最小化为目标优化系统运行状态,决策DG消纳量返回上层与中层模型。采用场景分析法解决DG与负荷的随机性问题,基于并行遗传算法和锥规划的混合算法求解模型。最后以IEEE 33节点系统为例,与仅规划DG,DG和SOP先后规划的情况对比,结果表明兼顾系统运行优化的DG与SOP协调规划有利于满足不同主体的利益需求,提高规划方案可行性。     

含风电机组的配电网中分布式电源的最优配置

为解决配电网中含风电机组分布式电源的最优配置问题,首先根据风速概率密度分布函数,推导出风电机组的输出功率函数,之后构建了含有分布式电源的固定投资费用、负荷增量与分布式电源出力的相关费用和以最小网损和最小常规发电机有功出力为目标的风电机组的惩罚成本的目标函数,并以配电系统中电压、电流等为约束条件,提出了一种以自适应惯性粒子群算法为全局搜索和以混沌算法为局部搜索的混合粒子群算法来获取目标函数的最优解。最后通过IEEE 69节点系统验证了所提出模型和算法的优异性。     

Modeling of the generalized unified power flow controller (GUPFC)in a nonlinear interior point OPF

With the progress of installing the latest generation of FACTS devices, namely, the convertible static compensator (CSC), several innovative operating concepts have been introduced to the historic development and application of FACTS. One of the novel concepts is the generalized unified power flow controller (GUPFC) or multi-line UPFC, which can control bus voltage and power flows of more than one line or even a sub-network. The GUPFC should have stronger control capability than the UPFC. A mathematical model for the GUPFC consisting of one shunt converter and two or more series converters is developed and implemented in a nonlinear interior point OPF algorithm. Numerical results with various GUPFC devices based on the IEEE 30 bus system and IEEE 118 bus system demonstrate the feasibility as well as the effectiveness of the GUPFC model established and the OPF method proposed