• Energy Research

AbstractDecarbonising the energy system requires high shares of variable renewable generation and sector coupling like power to heat. In addition to heat supply, heat pumps can be used in future energy systems to provide flexibility to the electricity system by using the thermal storage potential of the building stock and buffer tanks to shift electricity demand to hours of high renewable electricity production. Bridging the gap between two methodological approaches, we coupled a detailed building technology operation model and the open-source energy system model Balmorel to evaluate the flexibility potential that decentral heat pumps can provide to the electricity system. Austria in the year 2030 serves as an example of a 100% renewable-based electricity system (at an annual national balance). Results show that system benefits from heat pump flexibility are relatively limited in extent and concentrated on short-term flexibility. Flexible heat pumps reduce system cost, CO2 emissions, and photovoltaics and wind curtailment in all scenarios. The amount of electricity shifted in the assessed standard flexibility scenario is 194 GWhel and accounts for about 20% of the available flexible heat pump electricity demand. A comparison of different modelling approaches and a deterministic sensitivity analysis of key input parameters complement the modelling. The most important input parameters impacting heat pump flexibility are the flexible capacity (determined by installed capacity and share of control), shifting time limitations, and cost assumptions for the flexibility provided. Heat pump flexibility contributes more to increasing low residual loads (up to 22% in the assessed scenarios) than decreasing residual load peaks. Wind power integration benefits more from heat pump flexibility than photovoltaics because of the temporal correlation between heat demand and wind generation.

This paper addresses the following question: How can smart energy management system (SEMS) influence the residential electricity consumption at both individual household and national level? First, we developed an hourly optimization model for individual households. The energy cost of an individual household is minimized under given assumptions on outside temperature, radiation, (dynamic) electricity price, and feed-in tariff. By comparing the optimization to the reference scenario, we show the impact of SEMS on grid-electricity consumption and photovoltaic (PV) self-consumption at the individual household level. Second, to aggregate the results to the national level, we constructed a detailed building stock taking Austria as an example. By aggregating the results of 2112 representative households, we investigate the impact of SEMS in the residential building stock on the national electricity system. As a result, we found that for individual single-family-houses (SFHs) with PV (no battery) and heat pump adoption, SEMS can significantly reduce the grid-electricity consumption up to 40.7% for a well-insulated building. At the national level we found that, for the buildings with 5 kWp PV but without hot water tank or battery storage, SEMS can still reduce the grid-electricity consumption by 7.4% by using the building mass as thermal storage.

The electrification of households’ heating systems will lead to an increase in the electricity demand, which will necessitate additional investments in the grid infrastructure. The interaction with other technologies, including PV, batteries, electric vehicles (EVs), and home energy management systems (HEMSs), further complicate the situation. In this study, we analyze the following question: How will prosumaging households, who consume, produce and manage their energy consumption with HEMS, impact the future reinforcement costs of the electricity distribution grid? We conducted case studies for two urban areas, Murcia in Spain and Leeuwarden in The Netherlands. First, by developing scenarios on the uptake of electrified heating systems, PV installations, battery storage, EVs and HEMSs, the energy demand of each building is modeled for the two areas under different scenarios. Then, the buildings’ electricity load profiles were provided to a second model, to calculate the necessary distribution grid infrastructure to cover this demand on a granular spatial level. Results show that low voltage lines and transformers will need significant investments, especially in the regions where a high share of conventional heating systems are replaced by heat pumps but also in regions where the aggregate electricity peak demand is reduced.