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Optimised Heat Pump Management for Increasing Photovoltaic Penetration into the Electricity Grid

1
École Polytechnique Fédérale de Lausanne (EPFL), Institute of Microengineering (IMT), Photovoltaics and thin film electronics laboratory (PV-LAB), Rue de la Maladière 71b, 2000 Neuchâtel, Switzerland
2
Centre Suisse d’Electronique et de Microtechnique (CSEM), PV-Center, Rue Jaquet-Droz 1, 2000 Neuchâtel, Switzerland
*
Author to whom correspondence should be addressed.
Energies 2019, 12(8), 1571; https://doi.org/10.3390/en12081571
Received: 29 March 2019 / Revised: 10 April 2019 / Accepted: 19 April 2019 / Published: 25 April 2019
(This article belongs to the Special Issue Integration of PV in Distribution Networks)
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Abstract

Advanced control of heat pumps with thermal storage and photovoltaics has recently been promoted as a promising solution to help decarbonise the residential sector. Heat pumps and thermal storage offer a valuable flexibilisation mean to integrate stochastic renewable energy sources into the electricity grid. Heat pump energy conversion is nonlinear, leading to a challenging nonlinear optimisation problem. However, issues like global optimum uncertainty and the time-consuming methods of current nonlinear programming solvers draw researchers to linearise heat pump models that are then implemented in faster and globally convergent linear programming solvers. Nevertheless, these linearisations generate some inaccuracies, especially in the calculation of the heat pump’s coefficient of performance ( C O P ). In order to solve all of these issues, this paper presents a heuristic control algorithm (HCA) to provide a fast, accurate and near-optimal solution to the original nonlinear optimisation problem for a single-family house with a photovoltaic system, using real consumption data from a typical Swiss house. Results highlight that the HCA solves this optimisation problem up to 1000 times faster, yielding an operation that is up to 49% cheaper and self-consumption rates that are 5% greater than other nonlinear solvers. Comparing the performance of the HCA and the linear solver intlinprog, it is shown that the HCA provides more accurate heat pump control with an increase of up to 9% in system Operating Expense OPEX and a decrease of 8% in self-consumption values. View Full-Text
Keywords: photovoltaics; demand-side management; air-to-water modulated heat pump; thermal energy storage; nonlinear programming; mixed-integer linear programming; heuristics; optimal control problem photovoltaics; demand-side management; air-to-water modulated heat pump; thermal energy storage; nonlinear programming; mixed-integer linear programming; heuristics; optimal control problem
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Sánchez, C.; Bloch, L.; Holweger, J.; Ballif, C.; Wyrsch, N. Optimised Heat Pump Management for Increasing Photovoltaic Penetration into the Electricity Grid. Energies 2019, 12, 1571.

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