Self-scheduling approach for large consumers in competitive electricity markets based on a probabilistic fuzzy system

In competitive energy markets, large energy consumers are confronted with risks associated with energy prices. As the volatility in price of electricity is higher than that of other energy sources, this problem may become more pronounced for large electricity consumers. Hence, large industries should always seek sound paradigms for maximisation of their profit considering the risk caused by uncertainty within the planning horizon. In this study, a new fuzzy-based decision-making system for procurement of electricity from different sources is proposed which helps large industries to reach a compromise between the profit and risk. The simple but efficient technique of fuzzy α-cuts is applied for modelling the mentioned electricity pool price uncertainty in our problem. By using this modelling, a decision is made to maximise the profit of a consumer for different α-cuts corresponding to different levels of uncertainty. Therefore a range of decision-making with different strategies of profit-uncertainty is established and the consumer, depending on being a risk-taker or being risk-averse, can choose the appropriate strategy. To evaluate the proposed approach, a cement factory in north-eastern part of Iran (Khorasan Province) has been selected as the industrial consumer through a 12-week scheduling plan.