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

Abstract

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 a-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 a-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 northeastern part of Iran (Khorasan Province) has been selected as the industrial consumer through a 12-week scheduling plan.

Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation

“…Moreover, a technique based on the information gap decision theory is proposed in [17, 18] to assess the different acquisition strategies for large consumers to supply their electricity demand from different resources, e.g., power pool, BCs and even their own generating facilities. A fuzzy‐based decision‐making system for acquisition of electricity from different sources is proposed in [19], which helps large industries to reach a compromise between the profit and risk. Also, in [20], the second‐order stochastic dominance is developed for mid‐term scheduling problems of the large industrial consumers.…”

Robust Self-Scheduling of Operational Processes for Industrial Demand Response Aggregators

“…where (13) guarantees that the production level satisfies the customer ordered value, ( 14) restricts the production level of each sub-process to a lower ϕ ̅ , and upper ϕ ̅ , bound; (15) limits the flow of output from the previous storage to the next sub-process; finally the capacity of storage is bounded to lower , and upper , capacities through (16). To clarify the proposed mathematical model, Figure 2 describes the schematic diagram for the whole production line of the cement manufacturing plant.…”

“…In this way, on one hand, they take the advantage of cost-effective operation strategies, and on the other hand, they reduce the needs of the power system for more expensive alternative forms of flexibility like costly fastrun power plants or storage systems. In this regard, a selfscheduling for a cement plant participating in the electricity market is proposed in [16] to reach a compromise between risk and profit. In this paper, the fuzzy α-cuts is used to model a range of decision-making with different production strategies.…”

Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program

“…In [23,24], the information gap decision theory is used to assess different acquisition strategies for large consumers. A fuzzy-based decision-making system is presented in [25] for energy procurement from alternative resources. Also, the second-order stochastic dominance is developed in [26] for mid-term scheduling problem of large industrial consumers.…”