Reduction of heat pump induced peak electricity use and required generation capacity through thermal energy storage and demand response

Baeten, Brecht; Rogiers, Frederik; Helsen, Lieve

doi:10.1016/j.apenergy.2017.03.055

Cited by 144 publications

(52 citation statements)

References 24 publications

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“…Control approaches based on model predictive control techniques have also been considered. In [19], a multiobjective model predictive control strategy for residential heating with heat pumps was proposed. This approach takes into account the users' energy cost, the environmental impact, and expansion of electricity generation capacity.…”

Section: Introductionmentioning

confidence: 99%

A phase model approach for thermostatically controlled load demand response

Bomela

Zlotnik

2018

Applied Energy

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A significant portion of electricity consumed worldwide is used to power thermostatically controlled loads (TCLs) such as air conditioners, refrigerators, and water heaters. Because the shortterm timing of operation of such systems is inconsequential as long as their long-run average power consumption is maintained, they are increasingly used in demand response (DR) programs to balance supply and demand on the power grid. Here, we present an ab initio phase model for general TCLs, and use the concept to develop a continuous oscillator model of a TCL and compute its phase response to changes in temperature and applied power. This yields a simple control system model that can be used to evaluate control policies for modulating the power consumption of aggregated loads with parameter heterogeneity and stochastic drift. We demonstrate this concept by comparing simulations of ensembles of heterogeneous loads using the continuous state model and an established hybrid state model. The developed phase model approach is a novel means of evaluating DR provision using TCLs, and is instrumental in estimating the capacity of ancillary services or DR on different time scales. We further propose a novel phase response based open-loop control policy that effectively modulates the aggregate power of a heterogeneous TCL population while maintaining load diversity and minimizing power overshoots. This is demonstrated by low-error tracking of a regulation signal by filtering it into frequency bands and using TCL sub-ensembles with duty cycles in corresponding ranges. Control policies that can maintain a uniform distribution of power consumption by aggregated heterogeneous loads will enable distribution system management (DSM) approaches that maintain stability as well as power quality, and further allow more integration of renewable energy sources.

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Section: Introductionmentioning

confidence: 99%

A phase model approach for thermostatically controlled load demand response

Bomela

Zlotnik

2018

Applied Energy

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“…According to [11], there are three main categories of applications using heat pumps in a smart grid context: stable and economic operation of grids, integration of Renewable Energy Systems (RES) and operation under variable electricity prices. Changing residential space heating from the use of gas boilers towards heat pumps is recognized as a method to reduce emissions and increase the energy efficiency [12]. Heat pumps might become effective in balancing the electricity supply and demand when combined with the thermal inertia of buildings, contributing as well to the integration of renewable energies.…”

Section: Thermal Mass Storage and Setpoint Strategiesmentioning

confidence: 99%

“…In [12], a residential DR context is described, using a multi-objective strategy for space heating and DHW production using heat pumps and a TES system. Chassin et al [4] presented detailed simulation and performance studies showing how thermostatically controlled electrical loads can provide very valuable energy storage and how they could be prime candidates for fast DR. Also, [26] investigated how residential heat pumps which participate in load shifting can contribute to the reduction of emissions and operational costs.…”

Section: Reported Cost Savingsmentioning

confidence: 99%

Contributions of heat pumps to demand response: A case study of a plus-energy dwelling

et al. 2018

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Demand Response programs are increasingly used in the electricity sector, since they allow consumers to play a significant role for balancing supply and demand by reducing or shifting their electricity consumption. For that purpose, incentives such as time-based rates have been proposed. The present study analyzes the potential benefits of operating the heat pump of a plus-energy dwelling which participates in a dynamic pricing market, benefitting from the thermal storage capacity of the building. The software TRNSYS 17 has been used to model the building and the supply system. A validation of the model was carried out by using available measurements of the dwelling.Three setpoint temperature scenarios have been considered for sixteen different strategies which depend on temperature and electricity price thresholds, with the aim of determining which alternatives could lead to significant savings while maintaining an acceptable thermal comfort. Several factors such as cost savings, heat pump consumption, ratio of self-consumption of the dwelling and use of the heat pump during peak hours were also evaluated in every case.The results show that dynamic price thresholds should be used instead of fixed price thresholds, which may cause low activations of the heat pump or overheat the building above the comfort limits. Cost savings up to 25% may be achieved by using optimal strategies, increasing the self-consumption ratio, having almost no influence on the thermal comfort and achieving significant peak reductions on the grid. The outcomes of this study show the importance of looking at the implications of such strategies on several criteria within a demand response framework.

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“…Heating and cooling loads vary according to various factors, including solar radiation and outdoor temperatures, and reach maximum values at specific times, leading to peak electricity loads to meet heating and cooling demands [1,2]. Therefore, heating and cooling systems require efficient operation strategies to stabilize electricity demand and reduce the peak electricity usage [3].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions

et al. 2017

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A heat pump with thermal storage system is a system that operates a heat pump during nighttime using inexpensive electricity; during this time, the generated thermal energy is stored in a thermal storage tank. The stored thermal energy is used by the heat pump during daytime. Based on a model of a dual latent thermal storage tank and a heat pump, this study conducts control simulations using both conventional and advanced methods for heating in a building. Conventional methods include the thermal storage priority method and the heat pump priority method, while advanced approaches include the region control method and the dynamic programming method. The heating load required for an office building is identified using TRNSYS (Transient system simulation), used for simulations of various control methods. The thermal storage priority method shows a low coefficient of performance (COP), while the heat pump priority method leads to high electricity costs due to the low use of thermal storage. In contrast, electricity costs are lower for the region control method, which operates using the optimal part load ratio of the heat pump, and for dynamic programming, which operates the system by following the minimum cost path. According to simulation results for the winter season, the electricity costs using the dynamic programming method are 17% and 9% lower than those of the heat pump priority and thermal storage priority methods, respectively. The region control method shows results similar to the dynamic programming method with respect to electricity costs. In conclusion, advanced control methods are proven to have advantages over conventional methods in terms of power consumption and electricity costs.

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Reduction of heat pump induced peak electricity use and required generation capacity through thermal energy storage and demand response

Cited by 144 publications

References 24 publications

A phase model approach for thermostatically controlled load demand response

A phase model approach for thermostatically controlled load demand response

Contributions of heat pumps to demand response: A case study of a plus-energy dwelling

Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions

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