A Distributed Constraint Optimization (DCOP) Approach to the Economic Dispatch with Demand Response

With the growing complexity of the current power grid, there is an increasing need for intelligent operations coordinating energy supply and demand. A key feature of the smart grid vision is that intelligent mechanisms will coordinate the production, transmission, and consumption of energy in a distributed and reliable way. Economic Dispatch (ED) and Demand Response (DR) are two key problems that need to be solved to achieve this vision. In traditional operations, ED and DR are implemented separately, despite the strong inter-dependencies between these two problems. Therefore, we propose an integrated approach to solve the ED and DR problems that simultaneously maximizes the benefits of customers and minimizes the generation costs, and introduce an effective multi-agent-based algorithm, based on Distributed Constraint Optimization Problems (DCOPs), acting on direct control of both generators and dispatchable loads. To cope with the high complexity of the problem, our solution employs General Purpose Graphical Processing Units (GPGPUs) to speed up the computational runtime. We empirically evaluate the proposed algorithms on standard IEEE bus systems and test the stability of the proposed solution with a state-of-the-art power system simulator on the IEEE 30-bus system.