Potential of a population of domestic heat pumps to provide balancing service

This paper investigates the model of aggregated heat pumps as a source of the flexible load in Great Britain. A thermal model of a domestic heat pump was presented. A decentralised temperature control algorithm was proposed to control the building temperature, and heat pump’s ON and OFF cycles. Seven case studies were used to identify the suitable number of individual heat pump models that can be aggregated to accurately represent the projected number of heat pumps connected to the 2030 GB’s power system. The simulation results revealed that an aggregated model of 5,000 individual heat pumps was accurately representing the entire number of heat pumps in the Great Britain power system. Also, the power consumption of a group of heat pumps was examined in response to the grid frequency. Simulation results showed that the power consumption of aggregated heat pumps was successfully controlled in response to a frequency change. The controlled heat pumps reduced the dependency on the frequency service obtained by expensive peaking generators

Central model predictive control of a group of domestic heat pumps, case study for a small district

In this paper we investigate optimal control of a group of heat pumps. Each heat pump provides space heating and domestic hot water to a single household. Besides a heat pump, each house has a buffer for domestic hot water and a floor heating system for space heating. The paper describes models and algorithms used for the prediction and planning steps in order to obtain a planning for the heat pumps. The optimization algorithm minimizes the maximum peak electricity demand of the district. Simulated results demonstrate the resulting aggregated electricity demand, the obtained thermal comfort and the state of charge of the domestic hot water storage for an example house. Our results show that a model predictive control outperforms conventional control of individual heat pumps based on feedback control principles

Dynamic frequency response from controlled domestic heat pumps

The capability of domestic heat pumps to provide dynamic frequency response to an electric power system was investigated. A thermal model was developed to represent a population of domestic heat pumps. A decentralized dynamic control algorithm was developed, enabling the heat pumps to alter their power consumption in response to a system frequency. The control algorithm ensures a dynamic relationship between the temperature of building and grid frequency. The availability of heat pumps to provide low-frequency response was obtained based on data supplied by Element Energy. Case studies were carried out by connecting a representative model of the aggregated heat pumps to the regional Great Britain (GB) transmission system model, which was developed by National Grid. It was shown that the dynamically controlled heat pumps distributed over GB zones have a significant impact on the GB system frequency and reduce the dependency on frequency services that are currently supplied by expensive frequency-sensitive generators. The rate of change of frequency was also reduced when there is a reduction in system inertia

Potential of demand side response aggregation for the stabilization of the grids frequency

The role of ancillary services related to the frequency control have become increasingly important in the smart grids. Demand Side Response is a competitive resource that can be used to regulate the grid frequency. This paper describes the use of heat pumps and fridges to provide ancillary services of frequency response so that to continuously balance the supply with demand. The power consumption of domestic units is usually small and, therefore, the aggregation of large numbers of small units should be able to provide sufficient capacity for frequency response. In this research, dynamic frequency control was developed to evaluate the capacity that can be gathered from the aggregation of domestic heat pumps and fridges for frequency response. The potential of frequency response was estimated at a particular time during winter and summer days. We also investigated the relationship between both loads (domestic heat pumps and fridges) to provide Firm Frequency Response service. A case study on the simplified Great Britain power system model was developed. Based on this case study, three scenarios of load combination were simulated according to the availability of the load and considering cost savings. It was demonstrated that the aggregation of heat pumps and fridges offered large power capacity and, therefore, an instantaneous frequency response service was achievable. Finally, the economic benefit of using an aggregated load for Firm Frequency Response service was estimated

Adaptive control and dynamic demand response for the stabilization of grid frequency

Over the past few years, there has been a marked increase in the output from wind and solar generation in many countries. High levels of distributed generation provide variable energy and the increasing share of converter-connected plant results in a reduction in system inertia. Consequently, the rate of change of frequency, especially during and after severe faults, becomes more rapid. This thesis describes the use of heat pumps and fridges to provide ancillary services of frequency response so that to continuously balance the supply with demand. A decentralized digital controller namely: Adaptive DeadBeat (ADB) is designed to improve the frequency behaviour in an interconnected power system during and after faults. Simulation results show that the ADB controller can be considered as a contribution of digital control application to improve the frequency behaviour in an interconnected power system with reduced system inertia. The thermal performance of domestic buildings using heat pumps, and of fridges using thermostat temperature control is modelled. A dynamic frequency control (DFC) algorithm is developed to control the power consumption of the load in response to the grid frequency without affecting the overall performance of the load. Then, the dynamic frequency control algorithm is applied to a population of over 10 million aggregated units that represent the availability of load to provide frequency response. A dynamic relationship between the temperature and pre-defined trigger frequencies is given to ensure smooth and gradual load switching. A simulation is undertaken by connecting the controllable heat pumps to the reduced dynamic model of the Great Britain power system. Following a loss of 1,800 MW of generation, it is shown that the DFC reduces 1,000 MW of heat pumps demand and hence the frequency deviation is maintained within acceptable limits. In addition, a population of heat pumps and fridges are connected to the electrodynamic master model of the GB power system that is at present used by the ii GB transmission system operator, National Grid plc. Results show that the aggregated domestic heat pumps and fridges controlled by the DFC algorithm can participate in the Firm Frequency Response (FFR) service and provide rapid frequency response to the GB power system, mimicking the behaviour of the frequency-sensitive generators

Heuristic optimization of clusters of heat pumps: A simulation and case study of residential frequency reserve

The technological challenges of adapting energy systems to the addition of more renewables are intricately interrelated with the ways in which markets incentivize their development and deployment. Households with own onsite distributed generation augmented by electrical and thermal storage capacities (prosumers), can adjust energy use based on the current needs of the electricity grid. Heat pumps, as an established technology for enhancing energy efficiency, are increasingly seen as having potential for shifting electricity use and contributing to Demand Response (DR). Using a model developed and validated with monitoring data of a household in a plus-energy neighborhood in southern Germany, the technical and financial viability of utilizing household heat pumps to provide power in the market for Frequency Restoration Reserve (FRR) are studied. The research aims to evaluate the flexible electrical load offered by a cluster of buildings whose heat pumps are activated depending on selected rule-based participation strategies. Given the prevailing prices for FRR in Germany, the modelled cluster was unable to reduce overall electricity costs and thus was unable to show that DR participation as a cluster with the heat pumps is financially viable. Five strategies that differed in the respective contractual requirements that would need to be agreed upon between the cluster manager and the aggregator were studied. The relatively high degree of flexibility necessary for the heat pumps to participate in FRR activations could be provided to varying extents in all strategies, but the minimum running time of the heat pumps turned out to be the primary limiting physical (and financial) factor. The frequency, price and duration of the activation calls from the FRR are also vital to compensate the increase of the heat pumps’ energy use. With respect to thermal comfort and self-sufficiency constraints, the buildings were only able to accept up to 34% of the activation calls while remaining within set comfort parameters. This, however, also depends on the characteristics of the buildings. Finally, a sensitivity analysis showed that if the FRR market changed and the energy prices were more advantageous, the proposed approaches could become financially viable. This work suggests the need for further study of the role of heat pumps in flexibility markets and research questions concerning the aggregation of local clusters of such flexible technologies.Comisión Europea 69596

Techno-economic analysis of residential thermal flexibility for demand side management

The continuing rise in solar and wind production leads to an increasing demand of flexibility to stabilize the electricity grid. Furthermore, we can assume a gradual but intensive rise in the use of electrical heatpumps for household spatial heating, for different reasons. Therefore, this paper investigates the feasibility and viability of entering the flexibility market by aggregating residential thermal loads. For this research, a dataset of 200 dwellings in the Netherlands, equipped with a heatpump and smart metering infrastructure, is analysed. By means of a greybox modeling approach, a thermal model and control framework have been set up for every house, in order to identify the load shift potential and the accompanying cost of providing flexibility for the houses. We find that thermal flexibility is asymmetric: downwards flexibility is, apart from much more dependent on outdoor temperature than upwards flexibility, strictly lower than upwards flexibility. The cost for downwards flexibility is strictly negative in terms of the prosumer. Concerning upwards flexibility, the cost is most of the time positive. Moreover, it can be concluded that there is a potentially viable business case for the flexibility aggregator