Risk-aware sizing and transactive control of building portfolios with thermal energy storage

With the increasing numbers of distributed energy resources are being installed at more distributed locations, it is challenging to operate the electric grid systems efficiently against the demand and supply fluctuations. Moreover, extreme conditions could result in high expenditure and grid unreliability. To address this issue, this work focused on developing a risk-averse stochastic optimal dispatch model for building portfolios with thermal energy storage using conditional value at risk to avoid expected expensive financial loss at the tail of cost distribution. Two simulation case studies were performed to assess the performance of the risk-averse controller depending on the TES sizing and quantify the value of the proposed framework compared to the deterministic approach. The results demonstrated that the risk-averse controller could benefit from larger TES sizing as storing excess energy for the emergent realizations. Overall, 42.4% of cost savings was achieved by applying the risk-averse control strategy.