A new thief and police algorithm and its application in simultaneous reconfiguration with optimal allocation of capacitor and distributed generation units

• Published in: Energy (Oxford) Vol. 203; p. 117911
• Main Authors: Tolabi, H.B., Ara, A. Lashkar, Hosseini, R.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.07.2020; Elsevier BV
• Subjects: Algorithms; Ant colony optimization; Capacitors; Distributed generation; electric potential difference; Genetic algorithms; operating costs; Optimization; Particle swarm optimization; Photovoltaic; Photovoltaic cells; Photovoltaics; Police; Reconfiguration; Stability analysis; system optimization; Thief and police algorithm; Turbines; Voltage stability; Wind power; Wind turbine; Wind turbines; Photovoltaic; Thief and police algorithm; Wind turbine; Optimization; Reconfiguration
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2020.117911

This work aims to present a new optimization approach named Thief and Police Algorithm (TPA) to solve discrete-continuous optimization problems. The TPA performance was assessed by solving a discrete-continuous optimization problem in distribution networks. The optimization problem in this study was simultaneous reconfiguration with optimal allocation of capacitor, photovoltaic (PV) and Wind Turbine (WT) units. The objectives were considered as minimization of power loss, minimization of operational cost and improvement of voltage stability of the network. The proposed technique was evaluated using the IEEE 33 bus distribution network with eight different scenarios. Their results were compared with each other on different scenarios and with other well-known algorithms such as Symbiotic Organisms Search (SOS), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The results reveals that the TPA outperforms its counterparts in solving the mentioned problem. Also, the performance of the TPA was assessed using the 30 CEC 2017 test functions and the results were compared to the other optimization methods which confirms high capability of the TPA to solve complex optimization problems. •A new population-based algorithm to solve complex optimization problems.•Solving the thirty 2017 benchmarks using the novel Thief and Police Algorithm.•Solving reconfiguration problem with capacitor/photovoltaic/wind turbine placement.•Optimal placement and sizing of wind turbine, photovoltaic and capacitor unis•Better performance of the new algorithm than others in improving network indices.