Modelling and design of local energy systems incorporating heat pumps, thermal storage, future tariffs, and model predictive control

Research output: ThesisDoctoral Thesis

Abstract / Description of output

The planning-level design of local energy systems requires sufficiently capable modelling tools which incorporate heat pumps, thermal storage, future electricity markets, and predictive control strategies. Gaps were identified in a review of existing local energy system tools: (i) ability to adapt and access source code; (ii) temperature dependence for heat pump models; (iii) stratification model for thermal storage models; (iv) modelling of evolving electricity markets; and (v) ability to explore predictive controls. A novel modelling tool, PyLESA, has been developed to tackle these gaps and to explore predictive and non-predictive controls, and existing and future electricity tariffs. PyLESA possesses the following modelling capabilities: resources, and electrical and heat demands; electricity production; heat pump; hot water tank; electricity tariffs; fixed order control (FOC); model predictive control (MPC); and KPIs. A sizing study for a proposed design of a district heating network was devised to showcase an application of PyLESA. Aims were to compare control strategies and electricity tariffs, and to identify an optimal size combination of heat pump and hot water tank. Comparisons between control strategies found that MPC offers savings over FOC. The lowest levelized cost of heat for the existing electricity tariffs was for the time-of-use tariff with MPC, 750kW heat pump and 500m3 hot water tank. A wind tariff, with a 1000kW heat pump and 2000m3 hot water tank, benefits from using MPC over the FOC: levelized heat costs reduce by 41.1%, and heat demand met by RES increases from 52.8% to 70.2%. It is shown that the proposed design can be sized using existing electricity tariffs, and additional hot water tank capacity added later to benefit from future tariffs. The results convey the advantage of combining flexible tariffs with optimally sized thermal storage and showcase PyLESA as capable of usefully aiding the design of local energy systems.
Original languageEnglish
Awarding Institution
  • University of Strathclyde
Supervisors/Advisors
  • Tuohy, Paul Gerard, Supervisor, External person
DOIs
Publication statusPublished - 2020

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