Abstract

The deployment of renewable energy sources has been rapidly increasing due to environmental constraints but renewable electricity suppliers face an inevitable problem of uncertainty which is caused by the intermittent nature of renewable sources. In real-time operation, compromises have been made in cost and power to balance the power which reduces supplier benefits. Therefore, the functions of Weibull and Beta distribution of probability are used to handle the adverse impact of wind speed uncertainty and solar irradiation, respectively, and scenarios are reduced using the forward-reduction algorithm. Moreover, to measure the deviation of renewable power, underestimation and overestimation cost functions are utilised. This study proposes a suitable double-sided strategic bidding problem as a multi-objective optimisation problem to maximise the profits of suppliers and buyers to minimise uncertainty of rivals and renewable power. The formulated problem is solved by Technique for Order of Preference by Similarity to Ideal Solution along with Gravitational Search Algorithm, and simulation results are obtained in absence and presence of both solar and wind power on IEEE standard 30-bus and 57-bus test systems. The obtained results prove the suitability of the proposed bidding strategy in the presence of uncertainty of solar and wind power.

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