title: Development of a multi-method decision support tool for pumped hydro energy storage sites selection
Creators: name: Ali, Shahid
Publisher: name: Griffith University
Year: 2023
Subjects: subject: hydroelectricity
subject: pumped hydro energy storage (PHES)
subject: geographic information system (GIS)
subject: Bayesian network modelling
subject: multicriteria decision-making (MCDM)

description: Climate change has obligated countries worldwide to transform from centralised fossil fuel generation to decentralised renewable generation. However, renewable energy generation is typically weather dependent, and thus fluctuates significantly, making it an unreliable base load energy supply. Moreover, various socio-cultural, political, economic, technical, and institutional challenges are impediments to a seamless transition towards a renewable energy future. Finding and implementing cost-effective renewable energy solutions that provide reliable power while addressing community concerns and environmental impacts is challenging. Over time, various electrical, mechanical, thermal, and chemical energy storage technologies have been introduced to store electricity. Of these storage technologies, the pumped hydro energy storage (PHES) system appears to be one of the most mature and reliable energy storage systems (ESS) currently in the market. PHES technology has been in existence since the 1890s. Recently, the number of large-scale PHES system installations worldwide has accelerated due to the increasing demand for large-scale energy storages to support the exponential growth in intermittent renewable energy system deployments. Various challenges impeded the development of pumped hydro technologies. The first challenge to their development is the availability of a suitable topography, followed by other social, environmental, and economic challenges. Researchers worldwide have dedicated their efforts to devising diverse approaches to tackle these challenges effectively. However, they have not yet been effectively addressed. Thus, this study endeavoured to develop a GIS (Geographic Information System)-based multi-method PHES site selection decision support framework and associated tool capable of comprehensively assessing the suitability of PHES site options. The goal of the GIS based tool was to accelerate the pre-feasibility assessment process by semi-autonomously narrowing down the number of viable PHES sites based on various technical, environmental, social, and economic criteria. This PhD study firstly identified the knowledge gaps and synthesised the drivers and barriers to the development of PHES from the academic literature. These factors were then validated for the Australian context through consultation with experts. Subsequently, the conceptual framework of the study was established. The site selection procedure was carried out in two phases, where experts were engaged in the entire process. First, the techno-environmental investigation was conducted utilizing GIS spatial data (e.g., land elevations, proximity to infrastructure, etc.) to populate an Analytical Hierarchy Process (AHP) structured model to assess the various criteria. Second, a socio-economic investigation of the predetermined PHES sites was conducted utilizing GIS and Bayesian Networks (BN). The multi-method PHES site selection decision support tool was applied to identify sites in Northern Queensland (i.e., case study area). Finally, shortlisted sites were examined for financial viability using a Levelised Cost of Energy (LCOE) assessment for a number of realistic operation and utilization scenarios. As a result, this study retrieved various drivers for, and barriers to, the development of PHES. The study ranked the significance of reported drivers and barriers and the lessons learned for both developed and developing countries. The GIS-AHP techno-environmental investigation demonstrated for the case of Northern Queensland, Australia, revealed that at least fourteen PHES sites could be developed across the region. Whereas the application of the spatial-BN model reduced the suitable PHES sites to nine that are suitable from a socio-economic perspective. These nine sites could store and generate over 323 TWh of electricity over their life expectancy at a levelised cost of 0.04-0.274 AU$/kWh. The various assessment modules have been compiled into a GIS-based multi-method decision support tool for PHES sites selection. Overall, this research has contributed to the existing body of knowledge by effectively proposing a decision-making framework and tool that can be used to rapidly narrow down the ideal sites for PHES development in any geographical domain. The developed spatial-BN approach provides a novel approach to not only resolve socio-economic/techno-environmental PHES site selection decisions, but also has wide applicability to various other GIS-based site selection problems. The developed approaches described in this PhD study have implications for researchers, energy planners, and other practitioners seeking to locate feasible sites for the renewable energy resources required for transitioning to a zero-emissions economy.