Feminisms that Condemn the Growth Economy

The core focus of this section is to provide greater detail into studies of low-carbon island electricity systems. (Eurelectric, 2012; MIT-Portugal, 2013; Vallvé, 2013; IRENA, 2014a; Chmiel and

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Bhattacharyya, 2015) give tremendous insights into a host of projects explored for future electricity systems using islands as “living laboratories” for the testing of future electricity system solutions.

These major projects have driven and supported the growing interest of researchers keen to use island systems as case studies for improved understanding. Of these studies, highlighted above, are some that are of key relevance to this thesis. One such example is the work of Pina, Silva and Ferrão (2012), where the authors made use of the island of Flores in the Açores, characterised by high renewable energy penetration. They developed a TIMES MARKAL model with exogenous electricity demand growth. These authors sought optimal solutions for the energy system design and management, in the face of different possible exogenous evolutions of electricity demand. They also analysed the impact of demand-side management options, such as energy efficiency measures and dynamic demand response, to show that load shifting strategies can delay new investments while rendering the current investments on renewable resources more economically viable.

A different model of similar emphasis is an energy storage study on small isolated islands, also in the Açores, by Cross-Call (2013). A least-cost unit commitment model analysis was applied in order to determine the expected cost savings from introducing energy storage into existing electricity grid networks. The study highlighted some challenges and identified potential cost savings arising from energy storage within an evolving low-carbon electricity system. Similar to this is the work of Silva (2013) who employed multi-criteria decision methods to compare energy storage and other planning options for sustainable development within an island. Additionally, Parness (2007), made use of an economic dispatch and unit commitment model to explore environmental sustainability options on São Miguel in the Açores, giving attention to the optimal charging strategies for EVs, as needed to reduce electricity and transportation costs and to minimise CO2 emissions. Of similar scope, Baptista et al. (2009) made use of the island of São Miguel to assess the impact of introducing EVs, applying a short-term discrete scenario-based life-cycle approach, quantifying the impact of EVs on the electricity demand and the CO2 emissions.

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Other works such as Critz, Busche and Connors (2013) used the Wind Integration in Liberalized Markets (WILMAR) model, balancing supply and demand on an hourly basis to model the Hawaii Island’s electricity unit commitment scheme, with and without, demand response. That study used exogenous demand and treated demand response as a fully shift-able resource constrained by capacity and operational costs. Bruchon (2013) adopted the same model to study the island of Cyprus, in order to explore the potential of demand response programmes for integrating renewables into the electricity system from an hourly unit commitment perspective using stochastic optimisation. Perez and Real (2008) explored the creation of a European-type integrated electricity market within a small and isolated island group, the Canary Islands. These authors sought to understand better the challenges in creating such a market. Their results show that the designs of both the vertical industrial structure and the electricity grid operator (and its attributes) are key determinants of the successful operation of such an electrical system. In addition, the use of HOMER and PLEXOS to support IRP within the context of isolated island systems is used for such transitioning systems.

Collectively, the majority of these studies do not account for endogenous demand dynamics of the system but rather include the use of exogenous demand growth. They are also mainly stochastic optimisation models operated with the purpose of balancing short-term grid mismatch and/or investments. As shown in Section 2.2.3, modelling the salient features, such as the endogenous demand dynamics and longer-term system factors, can give useful insights into the long-term evolution of the electricity system. The use of SD is anticipated to help with capturing these details.

However, for such small island contexts, the use of SD is very limited. In addition and in particular, the number of long-term investment and resource planning models is very limited. We posit this is because of a tendency of previous research work to focus on short-term policy and design requirements for small island systems, hence lacking exposure to the already used systems thinking best practice occurring in larger systems.

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As mentioned above, the availability of SD studies in regard to small island electricity systems is limited. One study (Balnac, Bokhoree and Bassi, 2009) made use of a tool called Threshold-21 (T21) which applies SD to policy making in an integrated manner. The study provided a T21 electrical power sector model of the isolated islands of Mauritius. Although supply and demand load were endogenous to the model it assumed a least-cost-first rule when allocating demand to predominately fossil-fuel generating sets. According to the authors, the study allowed for a better understanding of Mauritius’ power sector and provided an initial structure for an electrical power grid model with scope for improvements. This adds merit to the use of SD for understanding low-carbon island electricity systems. To the best of this author’s knowledge, there does not exist any other literature targeted to SD modelling of isolated low-carbon electricity systems on islands, apart

from our own works (Matthew et al., 2014, 2015, 2016, 2017).

The research work that is undertaken in this thesis differentiates from Balnac, Bokhoree and Bassi (2009) in that the focus is not only modelling the dynamics of the physical and technical electricity system interactions, but also endogenous demand load, renewable resources, and key socio-economic aspects. Our intention is to give stakeholders insights into the emerging long-term characteristics of the system, leading to more informed policy decisions for satisfying the evolving demand and the required low-carbon objectives in general. The next section highlights a brief background to emerging policy and investment challenges for transitioning low-carbon electricity systems.