Policy Decision Support for Renewables Deployment through Spatially Explicit Practically Optimal Alternatives
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Abstract
Designing highly renewable power systems involves a number of contested decisions, such as where to locate generation and transmission capacity. Yet, it is common to use a single result from a cost-minimizing energy system model to inform planning. This neglects many more alternative results, which might, for example, avoid problematic concentrations of technology capacity in any one region. To explore such alternatives, we develop a method to generate spatially explicit, practically optimal results (SPORES). Applying SPORES to Italy, we find that only photovoltaic and storage technologies are vital components for decarbonizing the power system by 2050; other decisions, such as locating wind power, allow flexibility of choice. Most alternative configurations are insensitive to cost and demand uncertainty, while dealing with adverse weather requires excess renewable generation and storage capacities. For policymakers, the approach can provide spatially detailed power system transformation options that enable decisions that are socially and politically acceptable. The planning of highly renewable power systems at any scale involves compromise across diverse stakeholders. We develop a method that generates a variety of spatially explicit, alternative system configurations that can be used to balance techno-economic feasibility with social and political goals. The application of our method to Italy reveals flexibility of choice for decisions like where to locate wind power and whether to invest in particular technologies. Technology substitution and complementarity is evident: solar photovoltaic and battery capacities expand together, as do wind and synthetic gas turbine capacities, all of which must notably increase to replace bioenergy's firm capacity. We also see that highly renewable systems rely on regional interconnectivity but that gas infrastructure is only useful at a fraction of current capacity. Our approach can be similarly applied to examine trade-offs in other national systems, as well as those at district and continental scales. We develop a computational method, which shows that there is a flexibility of choice to manage contested decisions arising when planning highly renewable power systems, such as where to locate wind capacity. Within this decision space, problematic technologies, such as bioenergy, are difficult and costly to replace and are not absolute must-haves. Expansion of PV is a must-have, coupled with battery when designed to cope with low-wind conditions. Carbon-neutral gas turbines can contribute to balancing but with a minor role compared with today's use.