Optimal electric power distribution system reliability indices using binary programming

Abstract

At present, most electric distribution utilities measure their reliability performance using reliability indices such as system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI). However, using SAIFI and SAIDI as performance indices is insufficient to measure the outage cost of utilities and customers. The outage cost reflects actual damage efficiently. Additionally, life cycle cost (LCC) and investment cost of protective devices are important factors, which the utility providers need to consider. Adding protective devices in an electrical distribution system can decrease the outage cost by protecting public customers from local faults, but it may also increase the LCC and investment cost of the protective devices. In this paper, we propose an optimization technique to identify types and positions of protective devices to minimize the outage cost, the LCC and the investment cost according to system requirement constraints. This research aims to help the decision-maker in providing appropriate protective device allocations in the electrical distribution system. We apply our optimization technique with a nonlinear binary programming tool.