[email protected] Large-Scale Energy Storage Deployment in Ontario Utilizing Time-of-Use and Wholesale Electricity Prices: An Economic Analysis

In the Ontario power system, almost all coal power plants have been recently closed. The major power generation in Ontario is currently provided by nuclear power plants (base-load generation). Additionally, wind generation typically is maximum at night, a time period when the demand is minimum. This raises the question whether energy storage systems (ESSs) should be deployed in Ontario to shift the excess energy from the nighttime to peak hours during the day (if and when there is surplus power in the system). In today’s competitive electricity markets, policy makers and regulators are encouraging private investors to build, own, and operate large-scale energy storage plants as merchant operators. In such a case, the main objective of an ESS owner would be to generate profit by exploiting energy price arbitrage opportunities. An optimal dispatching algorithm is required to command an ESS to maximize the profitability of the investment. In this paper, a real-time optimal dispatching (RTOD) algorithm is developed by formulating a mixed integer linear programming problem to determine the ESS charging and discharging power setpoints in the Ontario electricity market. The RTOD algorithm aims to utilize the same Compressed-air ESS technology optimally sized for two models as follows: 1) the model using wholesale electricity market prices and 2) the model using contract-based electricity prices. Compressed-air has been chosen due to its lower capital expenditure and its ability to be positively influenced by the availability of waste heat. In the first case, the hourly Ontario energy prices and pre-dispatch prices, issued by the Ontario independent electricity system operator, are employed to optimally dispatch the ESS where the ESS seeks to generate revenue by exploiting arbitrage opportunities in the day-ahead wholesale market. In the second case, the time-of-use (TOU) electricity prices, as an example of contract-based electricity prices, are used to optimally dispatch the ESS where the ESS seeks to generate revenue by exploiting arbitrage opportunities available in TOU rates. The economic benefits of both cases are presented and compared. The simulation results reveal that while both TOU and wholesale electricity rates do not make any ESS investments economically viable, the profitability of the investment in ESSs operating in the wholesale market is considerably higher as compared to the TOU rates.