Optimal Scheduling of Energy Storage for Energy Shifting and Ancillary Services to the Grid

The increase in renewable energy penetration into Ontario’s electricity market has altered the overall behaviour of the energy market, with negative electricity prices even starting to appear. Negative prices represent a greater supply than the market demands, mostly appearing at night and during off-peak periods. Energy storage can be deployed in Ontario for peak shaving and energy shifting from off-peak to peak periods to address the above-mentioned issues. This is also the concern of many other system operators across the world. This thesis is mainly focused on developing optimization-based models for scheduling of energy storage units. At first, a real-time optimal scheduling algorithm is developed seeking to maximize the storage revenue by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices. The electricity price modulation is proposed as an approach to competitively offer incentive by the utility regulator to storage to fill the gap between current and a stable rate of return. Subsequently, the application of large-scale storage for congestion relief in transmission systems as an ancillary service to the grid is investigated. An algorithm is proposed for the following objectives: (i) to generate revenue primarily by exploiting electricity price arbitrage opportunities and (ii) to optimally prepare the storage to maximize its contribution to transmission congestion relief. In addition, an algorithm is proposed to enable independently operated, locally controlled storage to accept dispatch instructions issued by Independent System Operators (ISOs). Storage in this case is referred to as dispatchable storage. While the operation of locally controlled storage is optimally scheduled at the owner’s end, using the proposed algorithm, storage is fully dispatchable at the ISO’s end. Finally, a model is proposed and analyzed to aggregate storage benefits for a largescale load. The complete model for optimal operation of storage-based electrical loads considering both the capital and operating expenditures of storage is developed. The applications of the proposed algorithms and models are examined using real-world market data adopted from Ontario’s electricity market and actual load information from a large-scale institutional electricity consumer in Ontario.