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

Cristian Sánchez, Lionel Bloch, Jordan Holweger, Christophe Ballif and Nicolas Wyrsch
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Cristian Sánchez: 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
Lionel Bloch: 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
Jordan Holweger: 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
Christophe Ballif: 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
Nicolas Wyrsch: 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

Energies, 2019, vol. 12, issue 8, 1-22

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.

Keywords: photovoltaics; demand-side management; air-to-water modulated heat pump; thermal energy storage; nonlinear programming; mixed-integer linear programming; heuristics; optimal control problem (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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