Electricity markets need to keep the balance between energy generation and energy consumption. Utility companies increasingly have to deal with peak demands in constrained networks, so regulating the electricity use is critical.
Blackouts happen if the supply is incapable of meeting the demand, which can be solved either by investing in new power plants and transmission lines or by reducing the electricity demand. However, the first option might not be economically feasible if critical periods only occur a few hours per year. Electricity storage on a large scale could be a solution, but although continuous advances are currently in progress, it’s still an intricate and costly task.
In recent years, there has been an evolution from the conventional electric grids into Smart Grids. Two of the key objectives in a Smart Grid are the enhancement of its stability in stressed periods from the perspective of the utility and the achievement of cost savings from the consumer’s point of view. To achieve the goals of a Smart Grid, one of the major concepts used is Demand Side Management (DSM), a global term that includes a variety of activities such as load management, energy efficiency or energy savings.
Demand Response (DR), a subset of DSM, is defined by the US Department of Energy as “a tariff or program established to motivate changes in electric use by end-use consumers, in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized.” DR programs allow consumers to play a significant role in balancing supply and demand by reducing or shifting their electricity consumption. Although currently the concept of DR is mainly applied in relation to the electricity grid, similar benefits can also be obtained from district heating systems, especially if heat pumps are available to connect the electrical and thermal energy sectors (sector coupling).
As buildings are responsible for a large portion of the total electricity consumption in most countries, they are critical in efforts towards attaining the much needed operational flexibility in the grid. In addition, they have a thermal mass that provides inertia, taking some time to heat up or cool down. Like other technologies to store energy, this inherent property can be used to store energy at peak periods and preheat or precool the building but is available at no additional investment cost. Given the right control system, an electric heat pump could be used flexibly depending on the grid conditions, without significantly compromising the thermal comfort of the occupants and contributing to the reduction of peak loads.
That was the proposal of this study, which analyzed the potential benefits of operating the heat pump of a plus-energy dwelling in southern Germany which participated in a dynamic pricing market, benefitting from the thermal storage capacity of the building. The impact of different dynamic pricing strategies on several aspects was analyzed: cost savings, indoor comfort, heat pump consumption, reduction of the heat pump use during peak hours and photovoltaic energy self-consumption ratio of the building. The proposed controller could automatically manage the activation of the HP in response to price changes, so that cost savings could be achieved and the overload on the grid during peak periods was diminished by shifting the loads from peak to off-peak periods. The study was carried out through simulation by using the widely known software TRNSYS, which was used to model the building and the supply system. Moreover, a validation of the model was carried out by using measurements of the real system.
Sixteen different strategies were simulated for three different setpoint temperature scenarios, using data of the tariffs within a day-ahead market. Different price thresholds were used, fixed or variable, which either constrained the use of the heat pump during its normal operation or enforced its activation. Temperature thresholds were also been considered to avoid overheating.
The following figure reveals different modes of operation depending on the chosen strategy, showing the indoor temperature of the simulation as well as the price thresholds and the times at which the heat pumps were activated in each case. For example, in strategy 7 the heat pump always worked if the price was lower than 21c€/kWh and the indoor temperature was lower than 21 °C, while in strategy 8 the price threshold was increased up to 23 c€/kWh. Conversely, strategy 15 maintained the same temperature threshold, but in this case, the heat pump always worked if the electricity price was within the lowest 25% of the day. These strategies are possible due to the fact that the day-ahead market allows, as its name indicates, to know the prices the previous day.
(Reproduced with permission from Elsevier)
Several conclusions were drawn. Compared to the base case (the way in which the real household is controlled), cost savings up to 25% for the energy used to heat the building could be achieved by using optimal strategies, and at the same time increasing the self-consumption ratio and having almost no influence on the thermal comfort. The results also showed that dynamic price thresholds should be used instead of fixed price thresholds, which could cause low activations of the heat pump or overheat the building above the comfort limits. Apart from these benefits, the proposed optimal strategies accomplished significant peak reductions on the grid, since the heat pumps were mostly used during low-peak periods.
The analyzed strategies also highlighted the importance of knowing how much the users are willing to sacrifice their comfort to achieve savings: if a thermal discomfort tolerance is decided upon, this study provides answers to estimate the savings which may be achieved, helping with decision-making. The outcomes, therefore, prove the great benefits of using heat pumps and the thermal storage capacity of buildings together with dynamic pricing strategies within a DR framework.
These findings are described in the article entitled Contributions of heat pumps to Demand Response: case study of a plus-energy dwelling, recently published in the journal Applied Energy. This work was conducted by Laura Romero Rodríguez, José Sánchez Ramos and Servando Álvarez Domínguez from the University of Seville, and Ursula Eicker from the Stuttgart University of Applied Sciences.