Detailed simulation of electrical demands due to nationwide adoption of heat pumps, taking account of renewable generation and mitigation

Abstract

This study quantifies the increase in the peak power demand, net of non-dispatchable generation, that may be required by widespread adoption of heat pumps. Electrification of heating could reduce emissions but also cause a challenging increase in peak power demand. This paper expands on previous studies by quantifying the increase in greater detail; considering a wider range of scenarios, the characteristics of heat pumps and the interaction between wind generation and demand side management. A model was developed with dynamic simulations of individual heat pumps and dwellings.The increase in peak net-demand is highly sensitive to assumptions regarding the heat pumps, their installation, building fabric and the characteristics of the grid. If 80% of dwellings in the UK use heat pumps, peak net-demand could increase by around 100% (54GW) but this increase could be mitigated to 30% (16GW) by favourable conditions. Demand side management could reduce this increase to 20%, or 15% if used with extensive thermal storage. If 60% of dwellings use heat pumps, the increase in peak net-demand could be as low as 5.5GW.High-performance heat pumps, appropriate installation and better insulated dwellings could make the increase in peak net-demand due to the electrification of heating more manageable. Highlights Widespread (80% of dwellings) use of heat pumps could increase UK peak net electrical demand by 100%. A combination of measures could reduce this peak increase to approximately 30%. Demand side management has potential to further reduce the peak increase to 20%. Extensive thermal storage could further reduce the peak increase to 15%. The increase in peak net-demand due to 60% of dwellings using ASHPs could be as low as 5.5GW.

Power-to-Heat for Renewable Energy Integration: Technologies, Modeling Approaches, and Flexibility Potentials

“…While most of the reviewed models have an hourly time resolution, many do not cover all hours of the year, but make use of some time aggregation strategy. Few models have a sub-hourly resolution [56,38,66].…”

“…Some works do not rely on mathematical programming, but on heuristic methods [35,45,55,56,60,67,54,53]. Here, technologies are dispatched according to pre-specified hierarchies in case of renewable energy surplus or shortage for a number of scenarios with different data sets for demand, generation capacities or prices [55,60,67].…”

“…Power prices and electricity demand for power-to-heat Some papers explicitly consider the impact of power-to-heat applications on electricity prices. If electricity substitutes other fuels in residential heating, demand for electric power increases [37,55,63,56,65,50,39,40,52], and, in turn, power prices may rise [37,44,65]. However, the high efficiency of heat pumps and the flexibility of new loads may counteract this effect to some extent.…”

Comparative Study of Electric Energy Storages and Thermal Energy Auxiliaries for Improving Wind Power Integration in the Cogeneration System

“…The cooperation of CHP plants with EBs and energy storages in micro energy grids was explored in [31], focusing on the optimal planning problems. The HP is actuated by renewable energy for district heating in [32,33], and the utilization efficiency of renewable energy is effectively enhanced. In addition, utilizing different kinds of heating devices might be a possible choice [34][35][36], but this kind of approach should consider an increased difficulty of scheduling management.…”

Assessing the value and impact of demand side response using whole-system approach

“…Furthermore, in order to reduce further carbon emissions, at the certain extent, the use of gas for heating and hydrocarbon fuel for cars will be substituted by low-carbon energy such as electricity from renewable sources for electric vehicles, and heat pumps. Due to the load profiles, this electrification will, in turn, increase the peak demand of the system [1]. Therefore, real-time management of electricity loads, which traditionally are passive, is increasingly important as it can reduce the system (both generation and network) capacity required and enable higher utilization of lower cost resources.…”