Research

In this project, we have proposed a priority based energy scheduling mechanism for a distributed network with multiple microgrids. A novel method for calculating priority index is proposed in which the past contributions made by a microgrid and local load demand are considered as vital parameters. Each buyer decides its optimal strategy for buying energy from DNMS using optimal buyer strategy algorithm which gives Nash equilibrium solution of a non-cooperative energy competition game. The DNMS allocates optimal energy to each buyer microgrid using optimal DNMS decision algorithm. Energy allocated by the DNMS is directly proportional to the priority index of the buyer. The proposed system is stable enough for real-time implementation in the electricity market.

This project presents a novel centralized pricing approach (CPA) for energy trading among smart MGs. The novelty of the proposed method lies with designing seller strategies and introduction of a new pricing mechanism. The concept of an aggregator is used as a mediator between the trading parties. Depending on the priority index, each buyer MG decides it's strategy for energy demand from the surplus using a non-cooperative game theory based algorithm. The interests of seller MGs are protected by allowing them to decide the amount of energy they want to share out of their total surplus. A simple pricing mechanism is introduced to ensure proactive energy trading among MGs. This is a centralized approach. To avoid the selfish behaviour of any buyer MG, an algorithm is used by the energy market operator which varies the strategies submitted by buyer MGs before releasing set points to the generators. Apart from fairness and stability, the extensive numerical study confirms the ascendancy of the CPA method.