scholarly journals Impacts of Renewable Sources of Energy on Bid Modeling Strategy in an Emerging Electricity Market Using Oppositional Gravitational Search Algorithm

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5726
Author(s):  
Satyendra Singh ◽  
Manoj Fozdar ◽  
Hasmat Malik ◽  
Irfan Ahmad Khan ◽  
Sattam Al Otaibi ◽  
...  

Power suppliers in a dynamic power market can achieve full benefit by introducing a bidding strategy mechanism. In the power sector, renewable resources have significant gradual usage and their effect on the production of detailed bidding approaches is becoming further complicated in the industry. Due to the irregular nature of these renewable resources and because they are subject to several fluctuations, there is an inherent issue with generating electricity. Taking these considerations into account, attempts have been made to create a model of bidding strategy to optimize the benefit of the electricity producers using the oppositional gravitational search algorithm. The Weibull and Beta distribution functions are utilized to describe the stochastic characteristics of the wind-speed profile and solar-irradiation, respectively. For the IEEE-30 and IEEE-57 frameworks, the suggested method is being checked and explained. In comparison to other optimization approaches, the results of this approach were taken into account, and it was discovered that it outperformed other techniques in addressing bid difficulties. In addition, it is worth noting that the impact of renewable energy on the bidding strategy lowered market clearing and thermal power generating costs, and encouraged renewable influenced producers to put forward the excess electricity into the real-time market.


2021 ◽  
Vol 11 (10) ◽  
pp. 4438
Author(s):  
Satyendra Singh ◽  
Manoj Fozdar ◽  
Hasmat Malik ◽  
Maria del Valle Fernández Moreno ◽  
Fausto Pedro García Márquez

It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.



2016 ◽  
Vol 3 (4) ◽  
pp. 1-11
Author(s):  
M. Lakshmikantha Reddy ◽  
◽  
M. Ramprasad Reddy ◽  
V.C. Veera Reddy ◽  
◽  
...  


2013 ◽  
Vol 32 (10) ◽  
pp. 2732-2735
Author(s):  
Chun-long LI ◽  
Juan DAI ◽  
Feng PAN




2019 ◽  
Vol 33 (7) ◽  
pp. 2335-2356 ◽  
Author(s):  
Sarita Gajbhiye Meshram ◽  
M. A. Ghorbani ◽  
Ravinesh C. Deo ◽  
Mahsa Hasanpour Kashani ◽  
Chandrashekhar Meshram ◽  
...  


Author(s):  
Umit Can ◽  
Bilal Alatas

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.



2021 ◽  
Vol 1755 (1) ◽  
pp. 012007
Author(s):  
Khin Maung Htay ◽  
Rozmie Razif Othman ◽  
Amiza Amir


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