Abstract
The aim of the ISORC/OPTIMISER project is to increase and improve the use of solar thermal energy in district heating networks. One of the main tasks of the project is to develop an optimization tool for the sizing and operation of a solar district heating network. This is the first optimization tool using an open-source interface (Julia, JuMP) and solver (Ipopt) to solve nonlinear problems. This paper presents the multi-period optimization problem which is implemented to consider the dynamic variations in a year, represented by four typical days, with an hourly resolution. The optimum is calculated for a total duration of 20 years. First, this paper presents the modeling of the different components of a solar district heating network production plant: district network demand, storage and three sources, i.e., a fossil (gas) and two renewable (solar and biomass) sources. In order to avoid prohibitive computational time, the modeling of sources and storage has to be fairly simple. The multi-period optimization problem was formulated. The chosen objective function is economic: The provided economic model is accurate and use nonlinear equations. Finally the formulated problem is a nonlinear Programming problem. Optimization of the studied case exhibits consistent operating profiles and design. A comparison is made of different types of storage connection at the production site, highlighting the relevance of placing the storage at the solar field outlet. The optimum configuration supplies 49% of demand using solar energy, achieving a renewable rate of 69% in combination with the biomass boiler.
Highlights
Reducing CO2 emissions is one of the major challenges of the 21st century
Since this study focuses on multi-source all consumers of the district heating networks (DHNs)
This study presents the methodology used in a new optimization tool written in Julia to size a thermal production site to supply a district heating network
Summary
With regard to jurisdictional claims in (66 tonnes of oil equivalent) and 27% of greenhouse gas emissions. Heating represents 66% of a household’s energy consumption and the production of domestic hot water 11% [2]. It is in this context that the development of urban heating networks makes sense and especially fourth generation networks, which, among other things, are reducing network temperatures.
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