Distributed Optimal Gas-Power Flow Using Convex Optimization and ADMM

TL;DR

This paper introduces a distributed convex optimization algorithm for multi-period gas-power flow problems, significantly improving computational efficiency and robustness over traditional methods using ADMM and convex relaxations.

Contribution

It develops a novel distributed approach combining convex relaxations and ADMM for coupled gas-power systems, enhancing solution speed and accuracy.

Findings

Two orders of magnitude faster than nonlinear methods

High-quality solutions from convex quadratic initialization

Improved robustness and efficiency in numerical tests

Abstract

This paper proposes a convex optimization based distributed algorithm to solve multi-period optimal gas-power flow (OGPF) in coupled energy distribution systems. At the gas distribution system side, the non-convex Weymouth gas flow equations is convexified as quadratic constraints. The optimal gas flow (OGF) subproblem is solved by an iterative second-order cone programming procedure, whose efficiency is two orders of magnitudes higher than traditional nonlinear methods. A convex quadratic program based initiation scheme is suggested, which helps to find a high-quality starting point. At the power distribution system side, convex relaxation is performed on the non-convex branch flow equations, and the optimal power flow (OPF) subproblem gives rise to a second order cone program. Tightness is guaranteed by the radial topology. In the proposed distributed algorithm, OGF and OPF are solved independently, and coordinated by the alternating direction multiplier method (ADMM). Numerical results corroborate significant enhancements on computational robustness and efficiency compared with existing centralized OGPF methods.