مديريت انرژي الكتريكي يك ريزشبكه هوشمند با هدف بهبود همزمان سود بهره بردار، سود مشتركين و رفاه اجتماعي درحضور برنامه هاي پاسخگويي بار

Electric energy management of a smart microgrid with the aim of simultaneously improving the user s profit, subscriber s profit and social welfare in the presence of load response programs.

In this research, two-level optimization has been used for the exploitation of renewable resources and energy storage in a microgrid in the presence of load response programs. Also, a real-time and dynamic pricing scheme is proposed that simultaneously increases the profit of consumers and the distribution system operator. It is possible for consumers to buy the energy they need from the retail market or to participate in the load response plan provided by the power system operator. The presented model is multi-objective and two-level optimization. The upper level refers to increasing the profit of the distribution system operator, and the lower level deals with optimizing the profit of subscribers and increasing social welfare. In the following, the proposed multi-objective problem is transformed into a single-objective problem using the Pareto optimization technique based on the fuzzy method. Then, the ant-catcher algorithm is used to achieve the optimal solution in responding. Finally, the effectiveness of the proposed method is evaluated in a sample microgrid.

In this research, two-level optimization has been used for the exploitation of renewable resources and energy storage in a microgrid in the presence of load response programs. Also, a real-time and dynamic pricing scheme is proposed, which simultaneously increases the profit of consumers and the distribution system operator. It is possible for consumers to buy the energy they need from the retail market, or to participate in the load response plan provided by the power system operator. The presented model is multi-objective and two-level optimization, the upper level refers to increasing the profit of the distribution system operator, and the lower level deals with optimizing the profit of subscribers and increasing social welfare. Next, the proposed multi-objective problem is transformed into a single-objective single-objective problem by using the Pareto optimization technique based on the fuzzy method, then the ant-catcher algorithm is used to achieve the optimal solution in response. Finally, the efficiency of the proposed method is evaluated in a sample microgrid.