A multi-stage optimisation-based decision-making framework for sustainable hybrid energy system in the residential sector

Integrating renewables into existing energy infrastructure to construct hybrid energy systems (HES) plays a vital role for advancing energy sustainability. While various approaches, such as energy systems analysis and linear or non-linear optimisation, have been employed to achieve energy sustainability mainly at the national or city level, there has been a lack of focus on achieving energy sustainability in the residential sector through a holistic optimal decision-making approach for efficient HES design. This study focuses on developing a multi-stage optimisation-based decision-making framework that models, quantifies, and optimises the performance indicators of HES, allowing for an assessment of the trade-off between benefits and systems costs under various design scenarios. The initial step involves designing the HES model and constructing scenarios that cater to the electrification requirements of water, energy, and food elements in the residential sector by using a systematic thinking approach. Then, a preliminary evaluation of the modelled scenarios is conducted to assess energy sustainability in terms of technical and economic aspects. Afterwards, an optimal decision-making setup is established by integrating a multi-objective HES model into the NSGA-II algorithm, which approximates the Pareto optimal solutions. These solutions are then ranked by using a multi-criteria decision-making method. According to the findings, the Quetta region in Pakistan contains the best optimal solution. The results underscore the utility of the developed framework in facilitating the optimal design of renewables-integrated HES for the residential sector. Furthermore, intergovernmental organizations can leverage this framework to formulate effective policies aimed at encouraging residents to invest in HES installation.