Control and economics of power systems with renewables

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Non-generator resources (NGRs) like energy storage and demand response are conceptual solutions to the intermittency of renewable energy sources. NGRs have great potential to enhance the electric power system's efficiency and reliability, but will also add considerable new complexity through scale, uncertainty, and economics. Indeed, a demand response program may contain upwards of 10^5 loads, each subject to uncertainty from modeling inaccuracies, limited communications, and random factors like human behavior and weather. NGRs in general have starkly different characteristics than conventional generators, such as faster ramping capabilities, hard energy capacity constraints, and consequently dynamic states of charge. These factors mean that NGRs cannot be treated like conventional generation resources. In particular, power system operators must (i) use large load aggregations as though they were individual NGRs, and (ii) pay NGRs with regard to their unique physical characteristics so as to encourage proper participation in current markets and future investments. Indeed, the persistence of electricity market abuses like the 2001 California electricity crisis and the more recent JP Morgan trading scandal signifies the importance of sound economic mechanisms based on physical models. This research program will address these challenges by developing fundamental algorithmic and economic frameworks for effectively utilizing NGRs. New methodologies for managing uncertain load populations will be built on online learning theory and load aggregation techniques based on polytope theory. For instance, multi-armed bandit index policies will be derived for simultaneously utilizing and improving estimated models of loads. Since NGRs will be significant sources of power system regulation, markets must account for both the dynamics of NGRs and the power system. Toward this end, tools from optimal control and dynamic game theory will be employed to design contracts and pricing mechanisms that are based on physical models of NGRs and power system regulation, and to identify potential vulnerabilities to gaming and market abuse. The research will produce a broad set of tools for optimizing NGR utilization in technical and economic dimensions, in turn facilitating the integration of renewable energy sources into the existing power infrastructure. The resulting benefits will include (i) new theoretical insights and research directions in power system operation and economics, (ii) training of highly qualified personnel for careers in Canadian power industry and academia, and (iii) reduced environmental impacts.