Optimal Scheduling of a Residential Energy Prosumer Incorporating Renewable Energy Sources and Energy Storage Systems in a Day-ahead Energy Market
DOI:
https://doi.org/10.13052/dgaej2156-3306.3542Keywords:
Energy prosumer, day-ahead scheduling, energy storage sys- tems, renewable energy sources, electricity price forecasting.Abstract
Due to the world rapid population growth, the need for energy is acceler-
ated especially in the residential sector. One of the most efficient ways of
responding to energy demand is the utilisation of energy prosumers (EPs).
EPs are able to consume and produce energy by using renewable energy
sources (RESs) and energy storage systems (ESSs). In this paper, optimal
scheduling and operation of a residential EP is proposed considering elec-
tricity price forecasting. A hybrid adaptive network-based fuzzy inference
system (ANFIS)-genetic algorithm (GA) model is proposed for day-ahead
price forecasting. Then, forecasted price values are applied to a real-world
EP test system. It is revealed that the proposed hybrid ANFIS-GA model
can forecast electricity prices properly. However, due to the high linearity
of price patterns, the proposed algorithm was not able to accurately forecast peak-prices. Based on the results, the optimal operation of ESSs is affected
by the uncertainty of electricity price.
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