Minimisation of energy costs considering electric vehicle for a smart home system

Student thesis: Doctoral Thesis


Smart residential home systems have good potential for more efficient use of energy, reduced cost and less effects to environment. In order to adapt to new technologies such as electric vehicles (EVs), photovoltaic (PV) system, photovoltaic-thermal (PV-T) system, and solar water heater (SWH) system, novel demand side management (DSM) methods are required to effectively control EV and renewable technologies for residential energy systems. More importantly, customers play a key role in DSM as they have the energy usage choices according to their preferences. To understand the benefits for residential EV end users, their usage behaviours, such as driving behaviour, charging and discharging periods, willingness to participate to vehicle to grid (V2G), need to be considered in the DSM.In this thesis work, a novel DSM model framework is developed for a residential home system, considering EV, energy storage system (ESS), renewable technologies, and human behaviours. Survey data are collected and analysed to support the model development. Based on model, minimisation of the energy costs of residential home systems is explored by controlling the charging/discharging status of EV and a separate ESS under practical constraints. Key factors such as the degradation cost of EV and ESS batteries, user’s driving behaviour, and different types of electricity tariffs are included in the optimisation. Extensive case studies have been undertaken to investigate the operation strategies under various scenarios. The options and potential benefits of V2G are discussed.To further investigate the DSM for residential homes with the use of renewable energy, two solar water heating systems, the hybrid PV-T and the PV-SWH, are considered into the energy cost evaluation. Models for both PV-T and PV-SWH are formulated and added into the modelling framework for residential home systems. Built on the work of optimal charging/discharging of EV and ESS, the optimal switch operations of the PV-SWH system have been calculated, through which further cost reduction can be achieved. For the option of PV-SWH with limited solar panel space, the split of areas between PV and SWH is determined through a pseudo-optimisation route. Numerical studies have been conducted to examine the economic benefits of solar thermal collectors, the comparisons between PV-T and PV-SWH, and the effective use of the limited solar panel area for PV-SWH.Finally, different appraisal methods are applied to analyse the investment worth of the residential energy household systems with optimal DSM. The most beneficial investment solutions are obtained from the relevant case studies.Through the above systematic investigation of DSM for smart home energy systems, improved understanding on how to reduce energy cost for end users are obtained, including new insights on the benefits and conditions of V2G for EV users. The established modelling framework can easily include sub energy systems, e.g. EV, ESS, and renewable energy systems. Complex variation factors such as EV driving behaviour, external environment temperature, solar radiation, electricity tariffs are considered to achieve optimal operation strategies to reduce energy cost at residential home level. Financial analysis is applied to analyse the investment worth of these residential energy household systems. The optimal system choices for the end user are discussed through case studies.
Date of Award23 Jan 2020
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SupervisorHong Yue (Supervisor) & Campbell Booth (Supervisor)

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