  This paper proposes a nondominated sorting genetic algorithm II (NSGA-II)
based approach to determine optimal or near-optimal sizing and siting of
multi-purpose (e.g., voltage regulation and loss minimization),
community-based, utility-scale shared energy storage in distribution systems
with high penetration of solar photovoltaic energy systems. Small-scale
behind-the-meter (BTM) batteries are expensive, not fully utilized, and their
net value is difficult to generalize and to control for grid services. On the
other hand, utility-scale shared energy storage (USSES) systems have the
potential to provide primary (e.g., demand-side management, deferral of system
upgrade, and demand charge reduction) as well as secondary (e.g., frequency
regulation, resource adequacy, and energy arbitrage) grid services. Under the
existing cost structure, storage deployed only for primary purpose cannot
justify the economic benefit to owners. However, the delivery of storage for
primary service utilizes only 1-50\% of total battery lifetime capacity. In the
proposed approach, for each candidate set of locations and sizes, the
contribution of USSES systems to grid voltage deviation and power loss are
evaluated and diverse Pareto-optimal front is created. USSES systems are
dispersed through a new chromosome representation approach. From the list of
Pareto-optimal front, distribution system planners will have the opportunity to
select appropriate locations based on desired objectives. The proposed approach
is demonstrated on the IEEE 123-node distribution test feeder with
utility-scale PV and USSES systems.
