Abstract-The classical optimal power flow problem optimizes the power flow in a power network considering the associated flow and operating constraints. In this paper, we investigate optimal power flow in the context of utility-maximizing demand response management in distribution networks, in which customers' demands are satisfied subject to the operating constraints of voltage and transmission power capacity. The prior results concern only elastic demands that can be partially satisfied, whereas power demands in practice can be inelastic with binary control decisions, which gives rise to a mixed integer programming problem. We shed light on the hardness and approximability by polynomial-time algorithms for optimal power flow problem with inelastic demands. We show that this problem is inapproximable for general power network topology with upper and lower bounds of nodal voltage. Then, we propose an efficient algorithm for a relaxed problem in radial networks with bounded transmission power loss and upper bound of nodal voltage. We derive an approximation ratio between the proposed algorithm and the exact optimal solution. Simulations show that the proposed algorithm can produce close-to-optimal solutions in practice.
A recent work REF extends the greedy algorithm to solve the optimal power flow problem (OPF) with inelastic demands, a generalization of CKP to a networked setting including voltage constraints.
Optimal Power Flow with Inelastic Demands for Demand Response in Radial Distribution Networks
IEEE Transactions on Control of Network Systems (pp513 - 524, Volume: 5, Issue: 1, March 2018)
Computer Science Mathematics