Leveraging heat pump flexibility in local energy markets
This article describes how the role of thermal energy assets in local electricity markets (LEM) can be evaluated using Singularity Map, Grid Singularity LEM simulation tool, enhanced with the support of HYPERGRYD Horizon 2020 project to include digital twins of heat pump and district heating. It also serves as further evidence how local flexibility can be optimised by engaging in peer-to-peer (P2P) energy trading.
Heat Pumps Potential in Energy Transition
A heat pump is an energy asset used to heat water and premises by extracting heat from one place (air source, water source, and ground source/geothermal) and boosting it to a higher temperature level than the source (note: while some heat pumps also have a cooling function, only heating is considered here). It has been established that heat pumps are three- to five-times more efficient than fossil fuel boilers (IEA, 2023), meaning that they typically provide three to four units of heat energy for each electricity unit demanded, reducing the overall energy consumption while providing sustainable energy, especially if combined with thermal storage. This is highly significant considering that heating and cooling represent approximately 50% of the total final energy consumption and more than 40% of global energy-related carbon dioxide emissions, with the primary contributors being the building and industrial sectors (IRENA, 2024). The total heat pump capacity may triple from 1000 GW today to 3000 GW by 2030 (IEA, 2023), with the potential to cut global CO2 emissions by an amount equivalent to the current annual CO2 emissions from all cars in Europe, by 2030 (IEA, 2022). Consequently, sector coupling or improved integration of thermal technology in energy markets has been garnering increasing attention. Europe has been one of the fastest regions to adapt this technology, supported by policy measures and research and innovation funding, mainly through Horizon innovation programmes and other, targeted programmes like the Recovery and Resilience Facility. Additionally, at national levels, a variety of policies aimed at phasing out fossil fuel boilers are being implemented, strengthening grant schemes for heat pumps and reducing related value added tax.
Grid Singularity Heat Pump Digital Twin Modelling
In the Grid Singularity Exchange, a heat pump is modelled as a load, which consumes electricity and generates heat. If the heat pump has a storage option (water tank) then this is accounted for by a dedicated heat pump asset trading strategy, which facilitates flexibility trading by leveraging the heat storage capabilities of the water tank.
The heat pump places bids for electrical energy ranging from an initial to final buying rate, with prices increasing incrementally within the market slot upon the update interval. Asset owners (or managers) can either set the final rate as a default preferred buying rate or select a preferred buying rate based on a smart trading algorithm.
The parameters and default values used to model the template heat pump digital twin are presented in the table below, with full documentation available in the Grid Singularity Wiki.
Grid Singularity District Heating Digital Twin Modelling (Virtual Heat Pump and Heat Market Maker)
A Virtual Heat Pump (VHP) is akin to a digital twin representing the district heating system role in the electricity market, simulating how the demand for electricity that is satisfied by district heating could be satisfied if a heat pump were used instead. Unlike the heat pump model described above, district heating networks use water pipes that are directly connected to the building, and usually the supply temperature, return temperature and water flow are measured in order to facilitate customer billing. These district heating measurements are used to calculate the heat demand of the building and to calculate the energy that needs to be consumed by the heat pump in order to satisfy that demand, taking into account the flexibility that the water tank storage provides. The VHP model comprises a set of mathematical equations that each simulates a different component of a heat pump system. The system of linear equations is optimised in order to define the state and operation of the simulated heat pump. The optimisation parameter of the proposed model is the target temperature of the storage. The system is allowed to monitor the current temperature of the storage and try to achieve a target storage temperature that is bounded by the limitations of min / max temperature of the water tank.
The Grid Singularity VHP implementation is available exclusively in the Grid Singularity Exchange backend source code, since it will more likely be used by energy researchers for more complex simulations. VHP simulations can be used to analyse how district heating could be replaced by a heat pump and to compare their respective performance, including impact on grid stability. They could also be used for heat pump sizing optimization (the selection of the model, rating or other nameplate parameters) if there is a consideration to replace the district heating connection. Inversely, this feature can be used to calculate the heat demand of homes or other energy community participants, and consequently enable the simulation of a district heating connection that would satisfy this heat demand as opposed to electricity assets. Finally, for simulations that simply want to account for the district heating connection without considering a potential replacement with heat pumps, the digital twin of the district heating supply for the measured heat demand can be modelled as a “heat market maker”, i.e. digital trading agent with a specific trading strategy representing the district heating provider, which will only sell heat energy to the heat demand digital twin of the respective community member. The selling price of this market maker will be the district heating price that the heat consumer currently pays, in cents/kWh. The heat demand digital twin, in turn, is modelled as a load with a “consumption profile” defined by the measured heat demand in kWh. Thus, the “heat market maker” will only be used in order to cover the heat demand of the heat load and accounting for the monetary cost of heating.
Demonstration Study: Assessing District Heating Replacement and Heat Pump Benefits in Simulated Local Energy Community using Dataset from Sonnenplatz, Austria
To analyse the potential of sector coupling and flexibility assets (notably heat pumps), and how renewable energy sources, combined with district heating systems, can be further harnessed by enabling P2P energy trading and implementing dynamic grid tariffs, a total of 18 simulation scenarios were conducted using the Singularity Map, Grid Singularity LEM simulation tool.
The simulated community is based on a dataset from the HYPERGRYD pilot site, Sonnenplatz living lab in Großschönau, Austria for two seasons (August and November 2023), with historical electricity consumption and generation data for a total of 64 energy assets (23 metered load assets, 4 metered PV assets, 3 metered heat pumps, 11 non-metered battery storage assets, 8 non-metered PV assets and 15 heat demand assets measured in kW) owned by 13 Sonnenplatz members (six public/commercial buildings, one hotel, one office building and five residential buildings), as illustrated in the figure below.
The data collection was in part supported by the HYPERGRYD project research partners from the KTH Royal Institute of Technology in Stockholm (KTH), which developed a tool to derive data from the SONNE energy metres and operation sensors via the Internet by means of Message Queuing Telemetry Transport (MQTT) protocol. KTH also provided mathematical equations, which the Grid Singularity team then further developed and coded as part of the virtual heat pump modelling. A two-sided pay-as-bid market clearing mechanism was applied to simulate peer-to-peer energy trading in relevant scenarios. The market pricing for external supply (utility rate) and surplus sale to the grid (feed-in-tariff) and network cost (grid fees) reflect the actual conditions at the pilot site.
Two time-of-use (ToU) grid tariffs were implemented for simulation scenarios v.5 and v.6, respectively. The first is a day ToU tariff, where electricity prices are lower during the day when PV production is high, leading to increased sales of PV generation to the grid / external market and reducing self-consumption. In contrast, the night ToU tariff has high electricity prices during the day when PV production is high, incentivising all community participants to buy electricity from community-produced PV to the extent possible, increasing self-consumption.
The main study findings were the following:
- Peer-to-peer trading saves costs and increases local autonomy.
- The implementation of local, P2P energy trading resulted in a remarkable 145% reduction in net energy costs during the summer season by facilitating a more efficient use of local renewable resources. Namely, for the simulated week in the summer period (1–7 August 2023), the community generated a profit of €45, in contrast to the base case scenario where the community incurred an aggregate net cost of €100.
- The scope and therefore the benefits of P2P energy trading is lower in the winter period, due to reduced solar energy production of the community and increased heating demand. Nevertheless, there was still a 10.1% increase in the monetary benefits for the community with activated P2P trading in this period compared to the base case scenario. Importantly, all community participants benefited, with those with higher flexibility accruing a larger share of the benefit.
- From an environmental perspective, local energy trading acts as an important booster of local self-consumption and self-sufficiency (+124% increase in the summer, from 37.2.6% to 83.4%, and +105% increase in the winter, from 18.3% to 37.6%), reducing the community’s dependency on external energy sources.
Manuela Binder, Project Coordinator at Sonnenplatz Großschönau GmbH and the main counterparty for the demonstration study, observed:
“While there is increasing awareness of potential benefits of peer-to-peer trading, this is the first time that our community members could understand the scope of such benefits with quantifiable metrics”.
2. The adoption of dynamic Time-of-Use (ToU) tariffs presents substantial financial savings, particularly when combined with P2P energy trading, underscoring the importance of tailored tariff models.
- The introduction of night ToU tariffs alongside P2P trading achieved an impressive 278% reduction in energy costs during the summer period for the community compared to the base case scenario, adding additional savings to those generated by P2P trading alone. The community generated a profit of €178.3, in contrast to the base case scenario v.1, where the community incurred an aggregate net cost of €100 and to scenario v.3, where the community generated a profit of €45.1 with P2P trading but no tariffs applied. Similar outcomes are evident in the November results, where the community accrued an aggregate net cost of €322.9, in contrast to the base case scenario v.1, where the community incurred an aggregate net cost of €840.5 and to scenario v.3 (€755.9). This represents a 61.6% increase in monetary benefits in comparison to scenario v.1, and 10.1% in comparison to scenario v.3. Likewise, the community’s aggregate self-sufficiency rate significantly increased by 64% (from 43.6% to 71.4%) in the summer, and by 38% (from 27.6% to 38.2%) in the winter season, when compared to the base case scenario. This is attributed to the less affordable utility rates during day-time, when the PV production is peaking, incentivising local consumption (self-consumption rate increased from 36.1% to 59.1% in August, and from 47.3% to 65.4% in November).
- During the summer period, introducing day ToU tariffs led to a significant improvement in monetary benefits compared to the base case scenario, incurring a small aggregate net cost of €8.4, which is 92% improvement compared to the base case scenario, where the community incurred an aggregate net cost of €100, but 81% deterioration compared to scenario v.3, where the community generated a profit of €45.1 with P2P trading without day ToU tariffs. In the winter, the differences are less pronounced due to higher individual self-consumption. The community accrued an aggregate net cost of €755.6, in contrast to the base case scenario v.1, where the community incurred an aggregate net cost of €840.5, representing a 10.1% increase in monetary benefits, and just a marginal increased compared to scenario v.3, when this value was €755.9. Aligned with these findings, the aggregate self-sufficiency rate decreased (from 43.6% to 33.6% in the August period, and from 27.6% to 7.7% in the November period when compared to the base case scenario), since the PVs obtained a higher revenue selling their production to the grid, disincentivizing local energy consumption. Since the benefits of day ToU tariffs are reduced when they overlap with periods of high self-consumption within the community, there should be careful curation of ToU tariffs to maximise economic benefits for the community while supporting grid resilience. Their main effect is to increase the income of the grid operator and this would need to be strongly justified.
3. Replacing district heating with heat pumps is still not financially viable but becomes more viable with P2P trading and a higher scale — and levelling of heating and electricity prices.
- At present prices (20€cts/kWh cost of electricity used to power heat pumps vs. 12.24€cts/kWh cost of district network heating), transitioning to heat pumps doubles energy costs in the summer (for the water boiler heating), with the difference reduced in the winter period to 36.9% increase, due to higher efficiency of heat pumps. This result indicates that heat pumps will become a more viable solution as district heating prices align closer to electricity pricing. This is the trend, with heating prices increasing in this pilot community in 2024.
- Another factor increasing feasibility of district heating replacement by heat pumps is local energy trading. When P2P trading is activated, however, the community cost is reduced by 69% in the summer when compared with non-P2P trading and with district heating replaced by heat pumps (scenario v.2). In the winter, the net community energy cost is still higher than in the base case where district heating is not replaced, even when P2P is introduced (€1075.4 vs. €840.5 in the simulated week in November), which means that P2P is not sufficient to counter the higher electricity cost vs. heating cost in this period at the current price levels. Therefore, the community would need to weigh economic and environmental objectives until either the heating cost approaches that of electricity cost, or the P2P scale is increased (higher number of participants and higher capacity of renewable and flexible assets) to reap higher benefits.
- There are environmental benefits of replacing district heating, which are more pronounced in the winter period when heating is used to a greater extent and the efficiency of heat pumps becomes more significant. In our study, the self-sufficiency rate of the community increased in August by 6.45% (from 37.2% to 39.6%) and in November by 18.6% (from 18.3% to 21.7%), while the aggregate self-consumption rate increased in August by 16.6% (from 36.1% to 42.1%) and in November by 22.6% (from 47.3% to 58.0%). These results are dramatically improved when P2P trading is activated. Replacing district heating by heat pumps in an actively trading energy community would increase the self-sufficiency level of the community by a stark 136% (from 37.2% to 87.8%) in the summer, and 105% in the winter (from 18.3% to 37.5), compared to the base case scenario v.1. Here we see again better results in the summer since P2P trading harnesses the benefits of all local resources. Indeed, the summer self-sufficiency rate is another 4.5% higher compared to the rate of 83.3% with P2P trading and no district heating replacement, while it is the same when compared to the winter rate in that scenario.
- Batteries and increased local generation also play a role as a higher capacity would allow heat pumps to use more of locally produced, inexpensive energy, which should be a topic of further research. The source of district heating is also an important consideration for a more encompassing environmental assessment. In this pilot site it is biomass as opposed to coal-powered thermal plants that serve many other sites.
- Finally, our study demonstrated that optimising the virtual heat pump trading strategy by setting a preferred trading rate and thereby accounting for the price and not just storage optimisation, leads to further economic and environmental gains. When compared to scenarios v2 (district heating replaced by heat pumps) and v4 (v2+P2P), we observe a 74.8% and 19.0% benefit in the energy bill of the community in the summer period, and 11.4% and 5.3% benefit in the winter period. We also, as expected, find a significant increase in self-sufficiency: in the summer from 39.6% (v.2) and 87.8% (v.4) to 92.0%, and in the winter from 21.7% (v.2) and 37.5% (v.4) to 38.9%. By shifting the heat demand, the renewable assets were used much more efficiently, and the community imported less energy from the utility. This shows that P2P trading benefits can be further catalysed with smart asset trading approaches.
In a stakeholder meeting that discussed the results of the demonstration study, an active member of the Sonnenplatz community, Mr Martin Bruckner, major of the municipality Großschönau, concluded:
“We wish to proceed with these innovations, especially peer-to-peer trading. For sector coupling, however, we need to consider infrastructure costs and design a system that is more flexible to allow for alternatives such as use of heat pumps in the summer season and district heating in the winter.”
Action in lieu of conclusions:
If you are an energy management company — or an active energy citizen or a community manager — explore heat pump technologies and smart trading tools to maximise renewable energy use and minimise energy costs.
If you are a policy maker, consider supporting the transition to heat pumps and other renewable and flexible energy resources with reduced administrative requirements and incentives, facilitating the advance of local energy trading, and promoting dynamic tariffs for efficient energy use.
If you are a grid operator, look into integrating dynamic tariffs and energy trading mechanisms to improve grid resilience and manage congestion.
If you are an energy researcher, use Grid Singularity tools enhanced with digital twins for heat pumps and district heating in simulations to analyse performance and contribute to informed, optimised energy use and further innovation.
References
Grid Singularity Exchange, with backend source code at https://github.com/gridsingularity/gsy-e and documentation including technical approach and licensing described in GSY Wiki
Grid Singularity Wiki, Virtual Heat Pump, https://gridsingularity.github.io/gsy-e/virtual-heat-pump/
Grid Singularity Wiki, Heat Pumps and District Heating, https://gridsingularity.github.io/gsy-e/heat-pumps-general/
Grid Singularity Wiki, Results Dashboard (Key Performance Indicators), https://gridsingularity.github.io/gsy-e/results-dashboard/
HYPERGRYD, Hybrid Coupled Networks for Thermal-Electric Integrated Smart Energy Districts, https://hypergryd.eu/
International Energy Agency (IEA), The Future of Heat Pumps, 2022. Available at https://iea.blob.core.windows.net/assets/4713780d-c0ae-4686-8c9b-29e782452695/TheFutureofHeatPumps.pdf (accessed on 22 April 2024)
International Energy Agency (IEA), Net Zero Roadmap: A Global Pathway to Keep the 1.5 °C Goal in Reach, 2023. Available at https://iea.blob.core.windows.net/assets/9a698da4-4002-4e53-8ef3-631d8971bf84/NetZeroRoadmap_AGlobalPathwaytoKeepthe1.5CGoalinReach-2023Update.pdf (accessed on 2 May 2024)
International Renewable Energy Agency (IRENA), Power to heat and cooling: Status. Available at https://www.irena.org/Innovation-landscape-for-smart-electrification/Power-to-heat-and-cooling/Status, based on IEA heating statistics available at https://www.iea.org/energy-system/buildings/heating (accessed on 2 May 2024)
This article was authored by Fatuma Ali-Will, Spyridon Tzavikas and Ana Trbovich with contributions from Hannes Diedrich, Tiago Tavares and other colleagues at Grid Singularity, as well as important insights from partners at HYPERGRYD project.
