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dc.contributor.authorSchellenberg, Christoph
dc.contributor.authorLohan, John
dc.contributor.authorDimache, Laurentiu
dc.identifier.citationC. Schellenberg, J. Lohan, L. Dimache, Comparison of metaheuristic optimisation methods for grid-edge technology that leverages heat pumps and thermal energy storage, Renewable and Sustainable Energy Reviews, Volume 131, 2020, 109966, ISSN 1364-0321,
dc.description.abstractGrid-edge technology can unlock flexibility from consumers to contribute to meeting the growing need for flexibility in European energy systems. Furthermore, power-to-heat technology such as heat pumps and thermal energy storage has been shown to both decarbonise heat and enable the cost-effective integration of more renewable electricity into the grid. The consumer's reaction to price signals in this context presents the opportunity to simultaneously unlock operational cost reductions for consumers and localised implicit demand-side flexibility to benefit grid operators. In this paper, the prediction accuracy, run-time, and reliability of several (metaheuristic) optimisation algorithms to derive optimal operation schedules for heat pump-based grid-edge technology are investigated. To compare effectiveness, an optimisation effectiveness indicator OEI is defined. Particle Swarm Optimisation (PSO) and Genetic Algorithm (GA) were found to be most effective and robust in yielding quasi-optimal minima for the non-linear, multi-modal, and discontinuous cost function. GA optimisation with binary variables is 5–15 times more effective than with continuous variables. Using continuous variables, PSO is more effective than GA due to smaller optimisation error, shorter run-time, and higher reliability (smaller standard deviation). Simulated Annealing and Direct (Pattern) Search were found to be not very effective.en_US
dc.relation.ispartofRenewable and Sustainable Energy Reviewsen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.subjectGrid-edge technologyen_US
dc.subjectMetaheuristic optimisationen_US
dc.subjectImplicit demand responseen_US
dc.subjectHeat pumpen_US
dc.subjectThermal energy storageen_US
dc.titleComparison of metaheuristic optimisation methods for grid-edge technology that leverages heat pumps and thermal energy storageen_US
dc.contributor.affiliationDepartment of Industrial and Mechanical Engineering, Galway-Mayo Institute of Technology
dc.rights.accessOpen Accessen_US
dc.subject.departmentIndustrial and Mechanical Engineeringen_US

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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland