Storage-Reserve Sizing With Qualified Reliability for Connected High Renewable Penetration Micro-Grid

Abstract

The major challenge in high renewable penetration microgrid is the power mismatch between stochastic renewables and demand. Energy storage and reserve purchase are main techniques in reducing that. Storage sizing problem is widely investigated in literatures without reserve capacity co-optimizing. And due to innate no loss-of-load assumption, a large proportion of capacity is used to handle inessential energy deficiency with small probability. In this paper, storage-reserve sizing problem with qualified reliability is raised to integrate reserve sizing and loss-of-load probability (LOLP) index into existing storage sizing problem. Two-stage probabilistic model is established to minimize total cost with optimizing storage capacity during first-stage and reserve strategy during second-stage. Since the time-consuming Monte Carlo simulation and stage iteration are usually required in problem solving, Markovian steady-state sizing method is proposed to improve efficiency. Probability constraint is tested by mathematical quantile. And two-stage model is transformed to single-stage one attributed to analytical solution of second-stage. Meanwhile obtained relationship among storage capacity, reserve capacity, and LOLP index can help designers balance between capacity and reliability. Numerical test shows: needed capacity is significantly reduced with little sacrifice of reliability; storage–reserve combination is economical, since they are probabilistically complementary; proposed solution method is fast and accurate.