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A Novel Approach Based on Modified and Hybrid Flower Pollination Algorithm to Solve Multi-objective Optimal Power Flow

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IAENG International Journal of Applied Mathematics 2021年第4期51卷 1-18页

作者： Chen, Gonggui Qin, Qilin Zhou, Ping Kang, Peng Zeng, Xianjun Long, Hongyu Zou, Mi Professor of Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Master degree candidate of Chongqing University of Posts and Telecommunications Chongqing400065 China Senior engineer of Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing401120 China Senior engineer of State Grid Chongqing Electric Power Company Chongqing400015 China Professor level senior engineer of Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Assistant professor of Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

In this paper, a modified and hybrid flower pollination algorithms (MHFPA) is proposed for dealing with the multi-objective optimal power flow (MOOPF) problem with conflictive objectives. The algorithm combines the mutation and crossover process in the differential evolution (DE) algorithm, introduces the sinusoidal nonlinear dynamic switching probability (SNDSP) and the elite strategy of elder generation (ESEG), which can improve the shortcomings of the original pollen algorithm that it is easy to fall into the local optimum and the diversity is insufficient. A screening approach with Pareto-dominant rule (SAPR) is proposed to ensure that the state variable can satisfy the inequality constraints of the power system. A uniformly distributed Pareto optimal set (POS) is obtained by the non-dominant sorting with elite strategy (NSES) based on Rank and Density estimation, and the best trade-off solution (BTS) is determined from the POS obtained by the fuzzy affiliation theory. For practicality, the total fuel cost, active power loss, emissions and voltage deviation are selected as objective functions. Due to the limitations of the actual power system, the valve point effect is also considered. The IEEE30-, 57- and IEEE118-bus test systems are used to verify the performance of the proposed MHFPA. In addition, two © 2021. All Rights Reserved.

关键词： Electric load flow

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An Improved Marine Predators Algorithm for Short-term Hydrothermal Scheduling

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IAENG International Journal of Applied Mathematics 2021年第4期51卷 1-14页

作者： Chen, Gonggui Xiao, Ying Long, Fangjia Hu, Xiaorui Long, Hongyu Professor of Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Master degree candidate of Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Senior engineer of State Grid Chongqing Electric Power Company Chongqing400015 China Professor level senior engineer of Marketing Service Center State Grid Chongqing Electric Power Company Chongqing401123 China Professor level senior engineer of Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

In this paper, an improved marine predators algorithm (IMPA) is proposed to solve the short-term hydrothermal scheduling (STHS) problem. The marine predators algorithm (MPA) owns low diversity of the initial population and is easy to fall into local optima in the optimization process. Facing these challenges, three improvements are presented. Tent map is applied to initialize the population, which makes the population more uniformly distributed. An average fitness preferential strategy is adopted to improve the quality of population, which provides more possibility for MPA to find better solutions. By segmenting the probability factor in fish aggregating devices (FADs) effect on the optimization process, the premature convergence of MPA is improved. Moreover, a selective repair strategy and an economic priority strategy are proposed to handle dynamic water balance of reservoirs and the power balance, respectively. Three hydrothermal test cases are employed to verify the feasibility and effectiveness of the proposed method, and the results show that IMPA can obtain solutions of high quality. Compared with other methods, IMPA can get better results, which reflects its strong competitiveness in tackling the STHS problem. © 2021. All Rights Reserved.

关键词： Scheduling

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Fuzzy PID controller Optimized by Improved Gravitational Search Algorithm for Load Frequency control in Multi-area Power System

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2022年第1期49卷 125-139页

作者： Chen, Gonggui Qin, Feng Long, Hongyu Zeng, Xianjun Kang, Peng Zhang, Jinming Professor of Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Graduate student of Chongqing University of Posts and Telecommunications Chongqing400065 China Professor level senior engineer of Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Senior engineer of State Grid Chongqing Electric Power Company Chongqing400015 China Senior engineer of Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing401120 China

In this paper, an objective function considering performance index and an improved gravitational search algorithm (IGSA) are proposed to optimize the parameters of fuzzy PID (FPID) controller. IGSA is obtained by combining elite strategies and the mining capability of PSO algorithm. The IGSA FPID method which integrates IGSA and FPID controller is tested in a typical two-area non-reheat system, and system responses reflect the advantages of proposed objective function and IGSA. Additionally, the proposed IGSA FPID method still has excellent effects even on the two-area multi-source system with thermal power, hydropower and gas turbines. Meanwhile, the effect of high voltage direct current (HVDC) links in suppressing fluctuations is verified. Due to the popularity of wind power, a novel three-area interconnected power system with nonlinearity connected wind turbine (WT) is designed. Under the control of IGSA FPID, the good stability and dynamic performance of mentioned three-area system are verified. Therefore, FPID controller optimized by IGSA has excellent control effects, stability and universal applicability on the different power systems with multiple area and sources. © 2022. All Rights Reserved.

关键词： Wind turbines

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Optimal Placement and Capacity of Combined DGs and SCs in Radial Distribution Networks Based on PSO-OS Algorithm

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2021年第2期48卷 1-14页

作者： Chen, Gonggui Zhang, Ao Zhao, Chenxu Zhang, Zhizhong Professor of Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China A master degree candidate of Chongqing University of Posts and Telecommunications Chongqing400065 China Co. Ltd Inner Mongolia Power Economy and Technology Research Institute Hohhot010010 China A professor of Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China

The distribution of power flow can be effectively improved by optimizing the configuration of Distributed Generators (DGs) and Shunt Capacitors (SCs). Proper placements and capacities of DGs or SCs for real power loss minimization at the radial distribution network (RDN) is attracting more attention as people become more and more dependent on electric power resources. In order to overcome the slow convergence and poor effect of intelligent algorithms in this problem, Particle Swarm Optimization with Orientation and Shrinking factor (PSO-OS) is proposed in this paper. In the suggested PSO-OS algorithm, sensitivity analysis sort of distribution network is introduced to guide the direction of variation to simplify the search space, and shrinking factor is introduced to balance search capabilities in various RDN systems. The proposed method is applied to IEEE-33, IEEE-69 and IEEE-119 systems to solve the problem of simultaneous allocation of DGs and SCs. Simulation results show that the energy loss of the system is reduced and the stability is improved after reconfiguration. By repeating the experiment independently with the traditional PSO algorithm, the comparative analysis of the results proves the superior performance of the improved algorithm. By comparing with the results in recent literature, it reveals the effectiveness of the proposed PSO-OS algorithm in finding the optimal position and capacity of DGs and SCs in the distribution network. © 2021. All Rights Reserved.

关键词： Sensitivity analysis

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