Optimal Bidding Strategy in Deregulated Power Market Using Invasive Weed Optimization

Sudhakar, A.; Chandram, K.; Laxmi, A. Jaya

doi:10.1007/978-981-13-1822-1_39

Cited by 7 publications

(2 citation statements)

References 12 publications

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“…After using classical methods for solving bidding problem, the authors in refs. [5][6][7][8][9][10] uses different optimization techniques considering the factors like cost of generations, market constraints and rival's bidding behaviour that affect the bidding strategy problem. The risk issue is chosen as the key issues for bidding problem [11] where the risk is minimized for profit maximization in a competitive electricity market.…”

Section: Introductionmentioning

confidence: 99%

Impact of renewable energy sources on modelling of bidding strategy in a competitive electricity market using improved whale optimization algorithm

Sahoo

Hota

2021

IET Renewable Power Gen

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In a competitive power market, generating utilities can be enhanced to achieve maximum profit by implementing a process of bidding strategy. Now‐a‐days renewable sources like solar and wind have become better alternatives significantly than other sources prior to power generation. These sources have extensive utilisation day‐by‐day in power sector and their impact in developing precise bidding strategies is getting more challenging aspect in the market. Since these renewable sources possess intermittent nature and undergo many uncertainties, the generating utilities encounter an unavoidable problem. Taking these aspects into consideration, attempts have been made using improved whale optimization algorithm to make the bidding strategy model for maximizing the power supplier's profit. Weibull and Beta distribution functions are used for modelling the stochastic characteristics of wind‐speed profile and solar‐irradiation, respectively. The proposed technique is tested and clarified with an IEEE‐30, IEEE‐57 and practical 75‐bus Indian system. The outcomes of this method were taken into comparison with other optimization techniques and found that it has an advantage upon other methods in solving bidding problems. Further, it is observed that the impact of renewable sources on bidding strategy reduces the market clearing price and the generation of thermal power while increases the total bidding power.

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Section: Introductionmentioning

confidence: 99%

Impact of renewable energy sources on modelling of bidding strategy in a competitive electricity market using improved whale optimization algorithm

Sahoo

Hota

2021

IET Renewable Power Gen

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“…Strategic bidding problem for competitive power suppliers in the England -wale electricity markets is provided in [11,12]. These algorithms such as genetic algorithm (GA) [13], particle swarm optimization algorithm (PSO) [14], differential evolution (DE) [15], invasive weed optimization (IWO) [16] and krill herd algorithm (KHA) [17], bacterial foraging algorithm [18], agent-based algorithm [19], bat inspired algorithm [20] have been applied in solving the DSOBS problem. Advantages and limitations of these methods are explained by few researchers.…”

Section: Introductionmentioning

confidence: 99%

Supplier side optimal bidding strategy for electricity market using bacterial foraging optimization algorithm

L¹,

Raju²,

Chandram

2021

IJAPE

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<p class="Title1">In this article, bacterial foraging optimization (BFO) algorithm is developed for single side optimal bidding strategy in an electricity market. Optimal bidding strategy is one of the important functions in the electricity market along with forecasting of the electricity price and the profit based unit commitment. The prime objective of generating company (Genco) is to maximize their profit when they participate in the bidding process. The BFO algorithm has been used to maximize the probability density function (pdf). In the second stage the BFO algorithm is again applied to maximize the profit of the suppliers. The Proposed algorithm is developed in MATLAB (Version, 2019) and tested on standard test case available in the literature. Also, the simulation results are presented and compared. It is noticed that the proposed method yields the best results in terms of profit.</p>

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A novel harbor seal whiskers optimization algorithm

Zaher,

Al-Wahsh,

Eid

et al. 2023

Alexandria Engineering Journal

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Optimal Bidding Strategy in Deregulated Power Market Using Invasive Weed Optimization

Cited by 7 publications

References 12 publications

Impact of renewable energy sources on modelling of bidding strategy in a competitive electricity market using improved whale optimization algorithm

Impact of renewable energy sources on modelling of bidding strategy in a competitive electricity market using improved whale optimization algorithm

Supplier side optimal bidding strategy for electricity market using bacterial foraging optimization algorithm

A novel harbor seal whiskers optimization algorithm

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