A Day Ahead Market Energy Auction for Distribution System Operation

In this paper, we study a day ahead double energy auction in a distribution system involving dispatchable generation units, renewable generation units supported by battery storage systems(BSSs), fixed loads, price responsive loads, and supply from the Whole Sale Market(WSM) at Locational Marginal Price(LMP). The auction is implemented within a Distribution System Operator (DSO) premises using Mixed Integer Linear Programming (MIP). The proposed auction is cleared at the Distribution LMP (DLMP) and is observed to be weakly budget balanced if no penalty is applied for DSO's deviation from originally committed supply from the WSM. Furthermore, the dynamics of LMP and DLMP, and their effect on distribution market participants scheduled quantities as well as the WSM supply to the distribution system is investigated.Comment: Electro Information Technology (EIT), 2017 IEEE International Conference o

A Decentralized Distribution Market Mechanism Considering Renewable Generation Units With Zero Marginal Costs

A key feature of electricity generation in a distribution network is manifested by renewable generation with zero marginal cost. Existing market mechanisms are likely to fail in supporting such decentralized transactions while providing a reasonable price signal to compensate for the investment cost of renewable generators. Given this background, this paper first describes an average pricing market (APM) mechanism for pricing zero marginal cost renewable generation outputs in the distribution network. Then, a decentralized formulation of the APM mechanism is derived using the alternating direction method of multipliers (ADMM). Convergence of the decentralized mechanism can be guaranteed under some mild conditions for parameter setting. Finally, case studies are carried out to demonstrate the presented market mechanism. Simulation results show that the problem of always bidding a zero price by renewable generators in some existing markets can be avoided. The presented method also provides a solution for organizing decentralized electricity transactions in the distribution network and can converge to similar results with those obtained by the centralized one, with a relative error less than 5%