An efficient linear model for optimal day ahead scheduling of CHP units in active distribution networks considering load commitment programs

Abstract

The Optimal day-ahead Scheduling of Combined Heat and Power (OSCHP) units is a crucial problem in the energy management of Active Distribution Networks (ADNs), especially in the presence of Electrical and Thermal Energy Storages considering Load Commitment (LC) programs. The ADN operator may use Combined Heat and Power (CHP) units to supply its Industrial Customers (ICs) and can transact electricity with the upstream wholesale electricity market. The OSCHP problem is a Mixed Integer Non Linear Programming (MINLP) problem with many variables and constraints. However, the optimal operation of CHP units, Electrical and Thermal Energy Storages considering LC programs and contingency scenarios, may highly complicate this problem. In this paper, linearization techniques are adopted to linearize equations and a two-stage Stochastic Mixed-Integer Linear Programming (SMILP) model is utilized to solve the problem. The first stage models the behavior of operation parameters and minimizes the operation costs, verifies the feasibility of the ICs' requested power exchanges and the second stage considers LC programs and the system's stochastic contingency scenarios. The effectiveness of the proposed algorithm has been demonstrated considering 18-bus, 33-bus and 123-bus IEEE test systems.