Multilateral trades in interconnected power systems: a local public goods approach

We study the multilateral trade problem in interconnected power systems with asymmetric information and non-strategic regional transmission operators (RTOs). We consider a physical network with finite capacity lines connecting the buses within and between RTOs. Each RTO knows the network topology, bus angle constraints, and cost functions within its own region. Each RTO also knows the topology of the network connecting its own region to its neighboring regions and the bus angle constraints of the buses of neighboring RTOs that are immediately connected to its own region. The transmission system is modeled by a modified DC approximation where the power flow equations are represented as convex functions of the angle difference between buses; such an approximation considers lossy flows. The objective is to determine multilateral trades that satisfy the network's informational and physical constraints and minimize the sum of costs of all RTOs. We formulate the above multilateral trade problem as a local public goods problem. We propose a two-layer optimization algorithm that satisfies the problem's informational and physical constraints and results in a sequence of trades that converges to a trade which achieves a local minimum of the corresponding non-convex centralized information multilateral trade problem.