Cloud Electricity Storage for Multi-Service Battery Operation: Case of RTE

Problem definition: We study a cloud storage operator that provides shared storage service for electricity end-users using the residual part of a multi-service grid-scale battery primarily used for high-priority grid services. We design an optimal product with regard to pricing and customer portfolio. Academic/practical relevance: A framework and solution approach for assessing and operating such multi-service battery operations with stochastic services and different priority levels is an open problem. Methodology: We model the problem as a two-stage stochastic optimization between high-priority stochastic grid services and low-priority cloud storage for stochastic end-users. We also propose operational metrics of multiplexing gain and probability of blocking to assess the operation of the multi-service multi-user battery. To address the computational challenge of solving the stochastic optimization with a large number of end-users, we propose effective capacity as a convex approximation that allows an analytical solution. We then provide an empirical analysis based on real grid congestion data from RTE France and a large dataset of end-users' electricity consumption in California. Results: Our empirical analysis shows (i) our proposed effective capacity is a close approximation, (ii) battery operation and profit are sensitive to the cost of external resources, number of end-users, and the leasing price of the battery, and (iii) with only a slight discount of the leasing price (~1%), the profit of the third party from a stochastic residual battery can be the same as that from a deterministic one. Managerial implications: Cloud storage as a low-priority service can profitably exist alongside other high-priority battery services, making integration of more storage in the grid economically viable and allowing larger intermittent renewables, a key path towards reduced carbon emissions.