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Optimal Bidding Strategy for Profit Maximization of Generation Companies based on Whale Optimization Algorithm in Day Ahead Market

by Kavita Jain, Tanuj Manglani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 38
Year of Publication: 2018
Authors: Kavita Jain, Tanuj Manglani
10.5120/ijca2018916867

Kavita Jain, Tanuj Manglani . Optimal Bidding Strategy for Profit Maximization of Generation Companies based on Whale Optimization Algorithm in Day Ahead Market. International Journal of Computer Applications. 179, 38 ( Apr 2018), 29-41. DOI=10.5120/ijca2018916867

@article{ 10.5120/ijca2018916867,
author = { Kavita Jain, Tanuj Manglani },
title = { Optimal Bidding Strategy for Profit Maximization of Generation Companies based on Whale Optimization Algorithm in Day Ahead Market },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2018 },
volume = { 179 },
number = { 38 },
month = { Apr },
year = { 2018 },
issn = { 0975-8887 },
pages = { 29-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number38/29327-2018916867/ },
doi = { 10.5120/ijca2018916867 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:57:48.955482+05:30
%A Kavita Jain
%A Tanuj Manglani
%T Optimal Bidding Strategy for Profit Maximization of Generation Companies based on Whale Optimization Algorithm in Day Ahead Market
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 38
%P 29-41
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In a deregulated electricity market, the aim of generating companies (GENCOs) is to maximize their profit by bidding optimally in the day-ahead market, under incomplete information of the competitors. This paper proposes a methodology to acquire the optimal bidding strategy of thermal GENCO in a uniform price spot market as a precise model of nonlinear operating cost function and minimum up/down constraints of unit commitment. Rivals bidding behavior is described using different probability distribution functions: normal, lognormal, gamma and weibull probability distribution function. Bidding strategy of a generator for each trading period in a day-ahead market is solved by whale optimization algorithm (WOA).WOA can dynamically monitor the repeatedly varying market demand and supply in each trading interval. This paper explores the effectiveness of the proposed algorithm with different probability functions to obtain optimal bid quantities and prices and compare the results.

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Index Terms

Computer Science
Information Sciences

Keywords

Electricity market bidding strategies whale optimization algorithm (WOA) Monte Carlo (MC) simulation probability distribution

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