Policy calibration frameworks to reduce power sector emissions while mitigating impacts to wholesale electricity prices

Abstract

Decarbonising electricity generation is a critical component of international efforts seeking to mitigate the adverse effects of anthropogenic climate change. Given the integral role electricity plays within the proper functioning of modern society, policies seeking to reduce power sector emissions can have significant impacts on the wider economy. Scheme design can play an important role in determining the magnitude of a mechanism's economic impost, and also its political feasibility. For instance, the perceived inevitability of higher electricity prices following the introduction of a carbon price may be used by opponents to rally support in order to scupper scheme implementation. However, there exists a class of mechanisms that largely attenuates wholesale price shocks following a scheme's commencement. This thesis focuses on the design of two mechanisms belonging to this class of policy instruments: a Tradable Performance Standard and a Refunded Emissions Payment scheme. Counter-intuitively, wholesale prices may be lower following the introduction of these mechanisms, with price impacts largely dependent on policy settings -- suggesting judicious calibration of these schemes can yield given price outcomes. Despite the determinative role prices play with respect to a scheme's economic impost, there is little in the extant literature that establishes a connection between wholesale prices and scheme parameterisation decisions -- a topic explored in several chapters of this thesis. Calibration frameworks are developed to assist in identifying initial policy settings, and also inform how parameters may be updated as the underlying state of the system changes. Similarities between these two schemes are also explored, along with the way in which their mechanics can be combined. A new hybrid scheme is formulated that uses elements of both mechanisms to establish a clear and persistent carbon price, while also allowing net liabilities faced by generators to be clearly communicated. Under this mechanism, the scheme is allowed to run at a surplus or deficit depending on how it is parameterised. The opportunities presented by this new approach are explored, and a connection between scheme revenue and policy parameter settings is established. Using this relationship, a model predictive controller is designed to manage fluctuations in scheme revenue, obviating the need for a permit market, and defining a rules-based mechanism by which to update policy parameters. Case studies examining these calibration protocols are evaluated using a dataset describing Australia's National Electricity Market, developed specifically for this thesis. This is the first open grid geospatial model of Australia's largest electricity network, compiling publicly available information from government agencies and the market operator. These data allow the thesis to be placed within the context of an ongoing debate regarding the future direction of climate and energy policy within Australia, and also provides a more realistic test system through which to evaluate the calibration frameworks developed. While the case studies presented focus on the National Electricity Market, these protocols have universal application, giving policymakers an expanded and more flexible toolkit that may assist in overcoming the political and economic barriers carbon pricing initiatives often face.