Profit Maximization Bidding Strategy for a GENCO using Whale Optimization Algorithm

Jain, Pooja; Saxena, Akash

doi:10.1109/witconece48374.2019.9092917

Cited by 1 publication

(3 citation statements)

References 12 publications

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“…Now using MCP, net profit of generating utilities and large buyers and total power dispatch are calculated for this case. The outcomes thereof have been compared with different optimization technique like MC [7], GSA [25] and WOA [31] and summarized in Table 4.…”

Section: Case Studiesmentioning

confidence: 99%

“…From the above comparative analysis of 30‐bus system, it is found that the parameters required for bidding, attained by IWOA technique are optimised and also it gives maximum profit as compared to MC [7], GSA [25], and WOA [31] techniques. Figure 5 shows the convergence characteristics of the proposed approach with other approaches.…”

Section: Case Studiesmentioning

confidence: 99%

“…In this concern, a novel Meta‐heuristic approach known as whale optimization algorithm is introduced by Mirjalili and Lewis [30] which is based on hunting behavioural nature of whales and its application in formulating optimal strategic problem has been studied in ref. [31]. As the randomization plays a dynamic role in this approach so the process of searching is slow to get optimum value.…”

Section: Introductionmentioning

confidence: 99%

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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: Case Studiesmentioning

confidence: 99%