Volume 54, Number 5, September-October 2020
|Page(s)||1269 - 1289|
|Published online||12 June 2020|
A Non-Linear-Threshold-Accepting Function Based Algorithm for the Solution of Economic Dispatch Problem
Systems Engineering Department, King Fahd University of Petroleum & Minerals, 31261 Dhahran, Saudi Arabia
2 School of Electrical Engineering and Computer Science, Ottawa University, K1N 6N5 Ottawa, Canada
3 College of Energy Engineering, Aswan University, Aswan, Egypt
* Corresponding author: firstname.lastname@example.org
Accepted: 20 April 2019
This article introduces a novel heuristic algorithm based on Non-Linear Threshold Accepting Function to solve the challenging non-convex economic dispatch problem. Economic dispatch is a power system management tool; it is used to allocate the total power generation to the generating units to meet the active load demand. The power systems are highly nonlinear due to the physical and operational constraints. The complexity of the resulting non-convex objective cost function led to inabilities to solve the problem by using analytical approaches, especially in the case of large-scale problems. Optimization techniques based on heuristics are used to overcome these difficulties. The Non-Linear Threshold Accepting Algorithm has demonstrated efficiency in solving various instances of static and dynamic allocation and scheduling problems but has never been applied to solve the economic dispatch problem. Existing benchmark systems are used to evaluate the performance of the proposed heuristic. Additional random instances with different sizes are generated to compare the adopted heuristic to the Harmony Search and the Whale Optimization Algorithms. The obtained results showed the superiority of the proposed algorithm in finding, for all considered instances, a high-quality solution in minimum computational time.
Mathematics Subject Classification: 49-02
Key words: Economic dispatch / non-convex optimization / constraints optimization / meta-heuristics
© EDP Sciences, ROADEF, SMAI 2020
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