Performance assessment of PSO,DE and hybrid PSO–DE algorithms when applied to the dispatch of generation and demand |
| |
| Affiliation: | 1. Graduate Program in Electrical Engineering, Federal University of Minas Gerais-UFMG, Av. Antônio Carlos 6627, Pampulha, 31.270-010, Belo Horizonte, MG, Brazil;2. Electrical Engineering Department, Federal University of Minas Gerais-UFMG, Av. Antônio Carlos 6627, Pampulha, 31.270-010, Belo Horizonte, MG, Brazil;1. School of Physics Science and Information Engineering, Shandong key laboratory of optical communication science and technology, Liaocheng University, Liaocheng 252000, China;2. The Key Laboratory of Photonic Devices and Materials of Anhui, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China;3. Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China;1. Department of Electrical Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. Department of Physics, Faculty of Science and Technology, Airlangga University, Surabaya, Indonesia;1. Department of Physics, Faculty of Science, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia;2. Kulliyyah of Science, International Islamic University of Malaysia, Jalan Sultan Ahmad Shah, Bandar Indera Mahkota, 25200, Kuantan, Pahang, Malaysia;3. Department of Science, Universiti Tun Hussein Onn Malaysia, Parit Raja, Johor, Malaysia;4. Photonics Research Centre, Department of Physics, University of Malaya, 50603, Kuala Lumpur, Malaysia;1. School of Information Science and Engineering, Shandong University, Jinan 250100, China;2. College of Physics and Electronics, Shandong Normal University, Jinan 250014, China;3. State Key Laboratory of Crystal Material, Shandong University, Jinan 250100, China |
| |
| Abstract: | This work presents a comparison of three evolutionary algorithms, the particle swarm optimization, the differential evolution algorithm and a hybrid algorithm derived from the previous, when applied to the generation and demand dispatch problem. An optimization problem is formulated in the context of a small grid with partially flexible demand that can be shifted along a time horizon. It is assumed that grid operator dispatches generation and flexible demand along the time horizon aiming at minimizing generation costs. Consumption restrictions associated with flexible demand are modeled by equality and inequality energy constraints. Power flow equality constraints and inequality constraints due to operational limits for each dispatch interval are represented. The paper discusses a methodology for evolutionary algorithms performance assessment and states the importance of using statistical tools. The comparison is initially conducted using the IEEE 30-bus test system. Problem dimension effect is addressed considering different number of dispatch intervals in the time horizon. Moreover, the algorithms are applied to the 192-bus system of a Brazilian distribution utility, in the particular context of a load management program for large consumers of the company. In this application, the quality of the near-optimal solution obtained with the stochastic algorithms is evaluated by comparing with an analytical optimization algorithm solution. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
