Solving Bid-Based Dynamic Economic Dispatch in Competitive Electricity Market Using Improved Simulated Annealing Algorithm

Abstract

Electricity markets are open after the deregulation of power systems due to competition. An optimization problem based on dynamic economic dispatch has recently come up in the new context of deregulated power systems known as bid-based dynamic economic dispatch (BBDED). It is one of the major operations and control functions in the electricity markets used to determine the optimal operations of market participants with scheduled load demands during a specified period. BBDED involves power generation companies (GENCOs) and customers to submit energy and price bids to the independent system operator (ISO) in a day-ahead market. The ISO clears the market with the objective of social profit maximization. In this paper, a BBDED problem is solved using an improved simulated annealing algorithm (ISA), including system constraints with different periods under bidding strategies. The proposed ISA technique is implemented in MATLAB and applied on a 3-unit system, a 6-unit system, and a 40-unit large-scale system. The proposed ISA is evaluated by comparison with relevant methods available in the literature, to demonstrate and confirm its potential in terms of convergence, robustness, and effectiveness for solving the BBDED problem.

Social welfare maximization in deregulated power market incorporating wind power plants using metaheuristic algorithm

“…Moreover, over the years, there has been a significant shift from the traditional regulated model to a deregulated one in the energy sector. This shift has revolutionized the power supply industry (Bouddou et al, 2020), moving away from government monopolies toward a more open and competitive electricity market. The deregulated approach involves separating generation, transmission, and distribution as independent entities, as shown in Figure 1, leading to lower costs, reduced rates, more consumer choices, and improved services.…”

Static and dynamic environmental economic dispatch using tournament selection based ant lion optimization algorithm

“…A new modified artificial bee colony algorithm (Secui, 2015b), particle swarm optimization and genetic algorithm techniques (Hussain et al, 2019), chaotic improved harmony search algorithm Several optimization strategies and procedures have been utilized to solve the dynamic economic dispatch (DED) problem with complex objective functions or constraints since the topic was proposed in the 1980s (Rezaie et al, 2019). Literature survey shows to solve this problem using conventional algorithms (Kamli and Amraee, 2017), Dynamic economic dispatch using hybrid meta heuristics (Santra et al, 2020) and Simulated Annealing method (Bouddou et al, 2020) for non-smooth or non-convex cost functions, the majority of these strategies are ineffective. To solve the DED problem, a variety of heuristic optimization methods have been used, including Ant based optimization (Secui, 2015a;Vennila and Rajesh, 2022), Dragon fly based optimization (Chandrasekaran et al, 2021), Hybrid HB-SA algorithm (Vennila et al, 2013), differential evolution techniques (Li et al, 2022;Zou and Gong, 2022), harmony search algorithm (Rezaie et al, 2019), and bee swarm based optimization algorithm (Hussain et al, 2019).…”