Demand side management in urban district heating networks. (15th November 2018)

• Record Type: Journal Article
• Authors: Cai, Hanmin; Ziras, Charalampos; You, Shi; Li, Rongling; Honoré, Kristian; Bindner, Henrik W.
• Is Part Of: Applied energy. Volume 230(2018)
• Page Start: 506
• Page End: 518
• Publication Date: 2018-11-15
• Subjects: Smart energy systems -- 4th generation district heating -- Demand side management -- Data-driven modelling -- Congestion -- Energy flexibility; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2018.08.105
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Realistic method for DSM was developed for a district heating network. The method was applied in a real DHN in Denmark. Sensitivity of the optimal solution to energy, comfort and pumping costs is analyzed. Result shows up to 11% energy cost saving. Abstract: This paper proposes a realistic demand side management mechanism in an urban district heating network (DHN) to improve system efficiency and manage congestion issues. Comprehensive models including the circulating pump, the distribution network, the building space heating (SH) and domestic hot water (DHW) demand were employed to support day-ahead hourly energy schedule optimization for district heating substations. Flexibility in both SH and DHW were fully exploited and the impacts of both weekly pattern and building type were modelled and identified in detail. The energy consumption scheduling problem was formulated for both the individual substations and the district heating operator. Three main features were considered in the formulation: user comfort, the heat market and network congestion. A case study was performed based on a representative urban DHN with a 3.5 MW peak thermal load including both residential and commercial buildings. Results show an up to 11 % reduction of energy costs. A sensitivity analysis was conducted which provides decision makers with insights into how sensitive the optimum solution is to any changes in energy, user comfort or pumping costs.