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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/4939268 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832551892281982976 |
|---|---|
| author | Le Yang Dakuo He Bo Li |
| author_facet | Le Yang Dakuo He Bo Li |
| author_sort | Le Yang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-916ecb7e23cc4a9b8eacd25004a71e82 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-916ecb7e23cc4a9b8eacd25004a71e822025-02-03T06:00:11ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/49392684939268A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load DispatchLe Yang0Dakuo He1Bo Li2College of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaDynamic 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.http://dx.doi.org/10.1155/2020/4939268 |
| spellingShingle | Le Yang Dakuo He Bo Li A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch Complexity |
| title | A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch |
| title_full | A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch |
| title_fullStr | A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch |
| title_full_unstemmed | A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch |
| title_short | A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch |
| title_sort | selection hyper heuristic algorithm for multiobjective dynamic economic and environmental load dispatch |
| url | http://dx.doi.org/10.1155/2020/4939268 |
| work_keys_str_mv | AT leyang aselectionhyperheuristicalgorithmformultiobjectivedynamiceconomicandenvironmentalloaddispatch AT dakuohe aselectionhyperheuristicalgorithmformultiobjectivedynamiceconomicandenvironmentalloaddispatch AT boli aselectionhyperheuristicalgorithmformultiobjectivedynamiceconomicandenvironmentalloaddispatch AT leyang selectionhyperheuristicalgorithmformultiobjectivedynamiceconomicandenvironmentalloaddispatch AT dakuohe selectionhyperheuristicalgorithmformultiobjectivedynamiceconomicandenvironmentalloaddispatch AT boli selectionhyperheuristicalgorithmformultiobjectivedynamiceconomicandenvironmentalloaddispatch |