Abstract

Due to the target of carbon neutrality, energy saving has become more important than ever. At the same time, the widespread use of distributed energy systems and the regional utilization of industrial waste heat leads to the existence of multiple heat sources in an area. Therefore, how to design an economical and reliable pipeline network to meet energy-saving demand under multiple heat source conditions becomes a problem. In this work, an optimization method is established to determine the optimal pipeline network topology with minimum total annual cost. In this optimization method, Star tree algorithm, Kruskal algorithm and GeoSteiner algorithm are combined with a linear programming model to establish a distributed energy pipeline network for multiple heat sources. The model incorporates Euclidean Steiner Minimum Tree and Rectilinear Steiner Minimum Tree in the consideration of the topology optimization of Distributed Energy System pipeline networks. Four pipeline network topologies, STAR, Minimum Spanning Tree, Euclidean Steiner Minimum Tree and Rectilinear Steiner Minimum Tree, are evaluated in this paper from economic and reliability perspectives. A case extracted from a real industrial park where steam is the medium is used to prove the validity of the model. The optimization results show that a Euclidean Steiner Minimum Tree pipeline network has a lower total annual cost than three other types of pipeline network and ranks second in reliability. Considering the comprehensive economy and reliability, ESMT is the optimal pipeline network type of distributed energy system with steam as the medium.

Highlights

  • Based on the proposal of carbon neutrality target, optimization for energy-saving and emission-reduction in energy system field attracts various academic research

  • STAR is solved by Star tree algorithm, MST is solved by Krusalgorithm, and RSMT and ESMT are solved by GeoSteiner algorithm

  • Kal algorithm, and RSMT and ESMT are solved by GeoSteiner algorithm

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Summary

Introduction

Based on the proposal of carbon neutrality target, optimization for energy-saving and emission-reduction in energy system field attracts various academic research. As a high efficiency and promising technology [1] for energy conservation, a distributed energy system (DES) can use natural gas and renewable clean energy as primary energy source, including biomass, solar energy and hydrogen, and achieve the step utilization of the energy. It has become very popular recently compared with traditional centralized energy systems. DES can be improved from several aspects and a number of progress have been made. DES can be improved by optimizing the process within the station. Ren et al [2]

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