Abstract
The recent introduction of new power exchange product called Green Day-Ahead Market in Indian Energy Exchange with sole motive to promote short-term power trade generated from renewable energy sources is crucial for promoting green energy. Precise forecasting of market clearing price in this market is important for generating companies to strategically submit their sell offers in Day-Ahead Market which can maximize their net profit. Therefore, this work presents an advanced forecasting model for precise forecasting of market clearing price by training an ANN with its synaptic weight updated using the recently proposed Intelligent Programmed Genetic Algorithm. The performance of the proposed model is validated by comparing its result with that obtained using a simple Genetic Algorithm, Simulated Annealing, Particle Swarm Optimization, and Biogeography-Based Optimization in terms of Mean Absolute Error. Results clearly demonstrate the superiority of the proposed model in precise forecasting of market clearing in the Green Day-Ahead Market.
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Lalhungliana, Shah, D., Chatterjee, S. (2023). Application of Intelligent Programmed Genetic Algorithm for Price Forecasting in Green Day-Ahead Market of Indian Energy Exchange. In: Bhateja, V., Yang, XS., Lin, J.CW., Das, R. (eds) Evolution in Computational Intelligence. FICTA 2022. Smart Innovation, Systems and Technologies, vol 326. Springer, Singapore. https://doi.org/10.1007/978-981-19-7513-4_40
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DOI: https://doi.org/10.1007/978-981-19-7513-4_40
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