A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch
Dynamic economic and environmental load dispatch (DEED) aims to determine the amount of electricity generated from power plants during the planning period to meet load demand while minimizing energy consumption costs and environmental pollution emission indicators subject to the operation requiremen...
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| Published in | Complexity (New York, N.Y.) Vol. 2020; no. 2020; pp. 1 - 18 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Cairo, Egypt
Hindawi Publishing Corporation
20.01.2020
Hindawi John Wiley & Sons, Inc Wiley |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1076-2787 1099-0526 |
| DOI | 10.1155/2020/4939268 |
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| Abstract | Dynamic economic and environmental load dispatch (DEED) aims to determine the amount of electricity generated from power plants during the planning period to meet load demand while minimizing energy consumption costs and environmental pollution emission indicators subject to the operation requirements. This planning problem is usually expressed using a nonsmooth cost function, taking into account various equality and inequality constraints such as valve-point effects, operational limits, power balance, and ramp rate limits. This paper presents DEED models developed for a system consisting of thermal units, wind power generators, photovoltaic (PV) generators, and energy storage (ES). A selection hyper-heuristic algorithm is proposed to solve the problems. Three heuristic mutation operators formed a low-level operator pool to direct search the solution space of DEED. The high level of SHHA evaluates the performances of the low-level operators and dynamically adjusts the chosen probability of each operator. Simulation experiments were carried out on four systems of different types or sizes. The results verified the effectiveness of the proposed method. |
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| AbstractList | Dynamic economic and environmental load dispatch (DEED) aims to determine the amount of electricity generated from power plants during the planning period to meet load demand while minimizing energy consumption costs and environmental pollution emission indicators subject to the operation requirements. This planning problem is usually expressed using a nonsmooth cost function, taking into account various equality and inequality constraints such as valve-point effects, operational limits, power balance, and ramp rate limits. This paper presents DEED models developed for a system consisting of thermal units, wind power generators, photovoltaic (PV) generators, and energy storage (ES). A selection hyper-heuristic algorithm is proposed to solve the problems. Three heuristic mutation operators formed a low-level operator pool to direct search the solution space of DEED. The high level of SHHA evaluates the performances of the low-level operators and dynamically adjusts the chosen probability of each operator. Simulation experiments were carried out on four systems of different types or sizes. The results verified the effectiveness of the proposed method. |
| Audience | Academic |
| Author | Yang, Le He, Dakuo Li, Bo |
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| Copyright | Copyright © 2020 Le Yang et al. COPYRIGHT 2020 John Wiley & Sons, Inc. Copyright © 2020 Le Yang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Algorithms Alternative energy sources Analysis Cost function Deeds Economic aspects Electrical loads Electricity distribution Energy consumption Energy costs Energy storage Environmental aspects Green technology Heuristic Heuristic methods Industrial plant emissions Mathematical models Operators (mathematics) Optimization algorithms Optimization techniques Photovoltaic cells Power dispatch Power plants Renewable resources Solution space System effectiveness Wind power Windpowered generators |
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| Title | A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch |
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