Demand response (DR) is a powerful tool to maintain the stability of the power system and maximize the profit of the electricity market, where the customers engage in the pricing scheme and adjust their electricity demand proactively based on the price. In DR programs, most existing works are based on the assumption that the prediction of the electricity demand from customers is always accurate and trustworthy, which will lead to high cost and fluctuation of the electricity market once the prediction is obeyed. In this paper, we design a reward and punishment mechanism to constrain customers’ dishonest behaviors and propose a novel pricing algorithm based on the reward and punishment mechanism to relax the assumption, which guarantees the total electricity demands of all customers are within a secure range and obtain the maximum profit of the supplier. Meanwhile, we obtain the optimal demand and provide a upper and lower bound of the proposed price for the electricity market. In addition to a single type of customer, we also consider multiple types of customers, each of whom has different characteristics to prices. Extensive simulation results are constructed to demonstrate the effectiveness of the proposed algorithm compared with other pricing algorithms. It also shows that the average electricity consumption of a whole community is mostly affected by the residents’ electricity consumption and the balance of the supply and all types of customers is achieved under the proposed pricing algorithm.
An Economic Evalution of Demand-side Energy Storage Systems by using a Multi-agent based Electricity Market
