Demonstration of heating demand peak shaving in smart homes

Abstract

Flexible heating demand in buildings plays an important role in achieving a carbon neutral society. For the district heating system of Copenhagen, heating demand flexibility can help to eliminate the use of fossil-fueled boilers that are used during peak-load periods. In this project, field tests in 16 apartments were conducted, aiming to gain insights into the use of information and communication technologies (ICT) to manage heating systems operation for flexible demand. The apartments are equipped with sensors and devices interfaced to an ICT system composed of blocks responsible for data storage, monitoring and control. In the experiments, we controlled temperature setpoints of individual rooms during defined periods of the day, and continuously developed control strategies throughout the tests in the heating season 2018/19. The final algorithm was implemented with features to reduce the rebound effect and include residents feedback. All the algorithms are generic and can be applied in other smart homes where heating supply to rooms is controlled using thermostats. The ICT system architecture used in the experiments showed to be a feasible way to implement demand side management (DSM) in the heating system, and the learning process of the experiments resulted in improvements on the control strategies, leading to a better system performance.

Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review

“…Using heat stored in the buildings connected to DH networks to reduce the DH demand peaks (i.e., using the buildings for so-called 'virtual' storage) is one of the strategies that has attracted increasing attention during the last years, especially in Italy [25,[69][70][71][72][73][74] and in Nordic countries, such as Finland [30,[75][76][77], Denmark [78][79][80][81][82][83][84][85], and Sweden [54,86,87]. These countries are characterized by well-developed DH sectors and a large proportion of buildings with high thermal inertia.…”

“…Even though preheating is not necessary [78][79][80], it is usually favorable and highly effective at increasing DH delivery before the shutdown periods [82]. In combination with preheating, the impact of shutdown on indoor temperature is lower, so the shutdown period can last longer [78,79].…”

“…The choice of controlling strategy for a building should also be based on the service provided by the building [88]. Related to this, several studies were performed to propose controlling strategies for residential apartment buildings [54,77,78,80,82,88,90], residential single-family houses [79,88,91], and offices [30,[75][76][77]89].…”

“…The strategy can be applied (1) at building level by remotely controlling the heat flux provided to the customers from individual substations [93], or (2) at room level by remotely controlling individual digital thermostatic radiator valves [30,75,78,80,89,94], or (3) by remotely controlling an entire area or building clusters (i.e., the buildings clustered into different groups based on similar characteristics) [39,72,86,95]. When applying the strategy at room level, the modulation should not be similar in all rooms.…”

A mixed-methods case study on resident thermal comfort and attitude towards peak shifting of space heating

“…However, they did not ask the residents about their opinion on the indoor thermal environment. At EnergyLab Nordhavn, another study developed a DR algorithm to reduce peak loads in 16 apartments [23]. The purpose was here to test if the existing smart heating control system could be used to provide DSM.…”