LAUSR

We study the optimal operation of energy storage owned by a consumer who has intermittent renewable generation and faces time-varying (random) electricity prices and different types of ac/dc loads. We formulate the optimal storage operation problem as a finite-horizon dynamic program, with an objective of minimizing the expected energy cost. The incorporation of different types of ac/dc energy sources and appliances complicates the sequential decision making problem on storage operation. We provide a complete characterization on an optimal threshold policy, and implement the characterized optimal policy in realistic settings with random renewable generation and electricity prices. Numerical results demonstrate that the optimal dynamic programming (DP) solution saves 5%–12% of the total cost resulting from conventional DP solutions (that ignore the difference in ac/dc conversion efficiencies). Further, the value of storage (the consumer’s net benefit obtained by optimally operating the storage) increases with renewable generation. For example, as the (average) solar generation increases from 40% to 100% of the average (total) demand, the value of a 32 kWh (80 kWh) storage increases from 2.0% to 5.4% (7.2% to 14.9%, respectively) of the maximum energy cost.