Electricity arbitrage for mobile energy storage in marginal pricing mechanism via bi-level programming

• An investment framework for electricity arbitrage for mobile energy storage. • Mobile energy storage model with temporal and spatial constraints. • Co-optimization of energy and reserve markets in distribution systems. • Market revenue settlement on the marginal pricing mechanism. • Conditional value-at-risk-based revenue risk metrics for mobile energy storage. The rapid growth of renewable energy is integrated into the distribution system. The creation of both new market mechanisms and investment models has critical effects on the economics and security of the distribution market. Mobile energy storage has been used to increase the resilience of distribution grids due to their advantages in mobility and flexibility, which offer electricity arbitrage options for merchant investments. This paper presents a bi-level optimization framework based on location marginal pricing settlement of mobile energy storage financial rights revenue in active distribution systems. In the developed framework, the upper-level problem determines the optimal capacity, routing, and dispatching of mobile energy storage to maximize revenue in the liberalized electricity market. The lower-level problem performs the joint optimization of energy and reserve market clearing as well as renewable energy capacity optimization based on the alternating current optimal power flow model. The non-convexity of the line flow and location marginal pricing is linearized via second-order cone relaxation and Karush-Kuhn-Tucker. The bi-level programming is reformatted as mathematical programming with equilibrium constraints. Further, the revenue risk due to renewable energy uncertainty is measured via conditional value-at-risk. Finally, the effectiveness of the optimization framework and solution method is verified using the modified IEEE-33 test system. The results show that mobile energy storage promotes renewable energy and reduces distribution network costs by 2.3%.