Charge Allocation in Hybrid Electrical Energy Storage Systems

A hybrid electrical energy storage (HEES) system consists of multiple banks of heterogeneous electrical energy storage (EES) elements placed between a power source and some load devices and providing charge storage and retrieval functions. For an HEES system to perform its desired functions of 1) reducing electricity costs by storing electricity obtained from the power grid at off-peak times when its price is lower, for use at peak times instead of electricity that must be bought then at higher prices, and 2) alleviating problems, such as excessive power fluctuation and undependable power supply, which are associated with the use of large amounts of renewable energy on the grid, appropriate charge management policies must be developed in order to efficiently store and retrieve electrical energy while attaining performance metrics that are close to the respective best values across the constituent EES banks in the HEES system. This paper is the first to formally describe the global charge allocation problem in HEES systems, namely, distributing a specified level of incoming power to a subset of destination EES banks so that maximum charge allocation efficiency is achieved. The problem is formulated as a mixed integer nonlinear program with the objective function set to the global charge allocation efficiency and the constraints capturing key requirements and features of the system such as the energy conservation law, power conversion losses in the chargers, the rate capacity, and self-discharge effects in the EES elements. A rigorous algorithm is provided to obtain near-optimal charge allocation efficiency under a daily charge allocation schedule. A photovoltaic array is used as an example of the power source for the charge allocation process and a heuristic is provided to predict the solar radiation level with a high accuracy. Simulation results using this photovoltaic cell array and a representative HEES system demonstrate up to 25% gain in the charge allocation efficiency by employing the proposed algorithm.