LMP-based real time pricing for optimal capacity planning with maximal wind power integration

With the proposed penetration of electric vehicles and advanced metering technology, the demand side is foreseen to play a major role in flexible energy consumption scheduling. On the other hand, over the past several years, there has been a growing interest for the utility companies to integrate more renewable energy resources. Such renewable resources, e.g., wind or solar, due to their intermittent nature, brought great uncertainty to the power grid system. In this paper, we propose a mechanism that attempts to mitigate the resulting grid operational uncertainty by properly exploiting the potentials offered by demand flexibility. To address the challenge, we develop a novel locational marginal price (LMP) based pricing scheme that involves active demand side participation by casting the network objectives as a two-stage Stackelberg game between the local grid operator and several aggregators. We use the solution concept of subgame perfect equilibrium to analyze the resulting game and derive the optimal pricing scheme. Subsequently, we discuss the optimal real time conventional capacity planning for the local grid operator to achieve the minimal mismatch between supply and demand with the wind power integration. Finally, we assess our proposed scheme with field data. The simulation results further confirm the optimality of our scheme and suggest reasonably well long term performance with simplified heuristic approaches.