Stochastic optimal power flow formulation to achieve emissions objectives with energy storage

With increasing environmental awareness, strategies that include energy storage and emissions constraints or costs in the dispatch algorithm have been proposed. However, the problem is challenging because the real-time ancillary service dispatch signal is stochastic. The objective of this paper is to develop an optimal power flow formulation with energy storage that ensures emissions objectives are met. To achieve this, we propose a stochastic formulation which includes (i) uncertainties in reserve actions; (ii) re-dispatch reserves to manage state of charge of energy storage; (iii) an emissions constraint. We investigate methods to solve this problem via chance constraints. We also use this new formulation to study costs/emissions trade-offs associated with energy storage integration. We find that energy storage may not always be the economically and environmentally preferable option for providing reserves; factors that affect the dispatch results include demand level, supply-demand mismatch characteristics, energy storage round trip efficiency, and cost of re-dispatch reserves.