Abstract

Using an integrated demand-supply optimization model, this work investigates the potential for flexible space heating demand, i.e., demand response (DR), in buildings, as well as its effects on the heating demand and the operation of a district heating (DH) system. The work applies a building stock description, including both residential and non-residential buildings, and employs a representation of the current DH system of the city of Gothenburg, Sweden as a case study. The results indicate that space heating DR in buildings can have a significant impact on the cost-optimal heat supply of the city by smoothing variations in the system heat demand. DR implemented via indoor temperature deviations of as little as +1 °C can smoothen the short-term (daily) fluctuations in the system heating demand by up to 18% over a period of 1 year. The smoothening of the demand reduces the cost of heat generation, in that the heat supply and number of full-load hours of base-load heat generation units increase, while the number of starts for the peaking units decreases by more than 80%. DR through temperature deviations of +3 °C confers diminishing returns in terms of its effects on the heat demand, as compared to the DR via +1 °C.

Highlights

  • Energy use in buildings accounts for about one-third of the total global energy use.The International Energy Agency (IEA) estimates that if no action is taken to improve energy efficiency in this sector energy consumption in buildings will rise by almost 50% between 2010 and 2050 due to the expansion of the sector [1]

  • The methodology developed and applied in this work builds on previous work by the authors in integrating two separate optimization models: (i) A physical space heating demand model of a building stock (BS), which is based on the Energy Carbon and Cost Assessment of Building Stocks (ECCABS) model developed by Mata et al [29] and further refined by Nyholm [30]; and (ii) a dynamic unit commitment model of a district heating (DH) system, as developed by Romanchenko et al [31]

  • The results show that the total space heating demand of the investigated BS is distributed between distributed between the building types as follows: 12% from single-family dwellings (SFDs); 68% from multi-family dwellings (MFDs); and 20% from the building types as follows: 12% from SFDs; 68% from MFDs; and 20% from non-residential buildings (NRBs)

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Summary

Introduction

Energy use in buildings accounts for about one-third of the total global energy use.The International Energy Agency (IEA) estimates that if no action is taken to improve energy efficiency in this sector energy consumption in buildings will rise by almost 50% between 2010 and 2050 due to the expansion of the sector [1]. Energy use in buildings accounts for about one-third of the total global energy use. Improving the energy efficiency and decreasing the energy demand of buildings are crucial factors in reaching global sustainability targets. Buildings that are equipped with advanced control systems permit the smart control of energy loads, thereby conferring flexibility on the supply side via an active demand response (DR), e.g., the shifting of the electricity consumption of electrical appliances, including heating [2] or smart charging of electric vehicles [3]. DH systems in Sweden experience significant variations in heating demand (including long-term seasonal and short-term daily variations). This results in part-load operations of base- and mid-load heat generation units and frequent starting and stopping of peaking units, which are often fossil-fueled, heat-only boilers (HOB)

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