Multi-Objectives, Multi-Period Optimization of district heating networks Using Evolutionary Algorithms and Mixed Integer Linear Programming (MILP)

Abstract

A systematic procedure, including process design and integration techniques for sizing and operation optimization of a poly-generation plant and design of a district heating network is presented in this paper. In the developed model a simultaneous multi objectives and multi-period optimization are principally investigated. The goal is to simultaneously minimize costs and CO 2 emission using multi-objective evolutionary algorithms (EMOO) and Mixed Integer Linear Programming (MILP). Typical days definition and the extension of the post processing phase are the novelty of this work. The proposed method helps the decision maker to know; which type and configuration of poly-generation technologies (centralized and decentralized) are best suited for the district? Is it viable to combine these technologies with other technologies (like heat pumps, solar PV)? Where in the district shall these technologies be implemented (geographically)? what are the optimal flow, supply and return temperatures of the distribution networks (heating and cooling) considering the requirements of the district and the technical limitations of the technologies?