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This paper presents a method to determine the optimal location, energy capacity, and power rating of distributed battery energy storage systems at multiple voltage levels to accomplish grid control and reserve provision. We model operational scenarios at a one-hour resolution, where deviations of stochastic loads and renewable generation (modeled through scenarios) from a day-ahead unit commitment and violations of grid constraints are compensated by either dispatchable power plants (conventional reserves) or injections from battery energy storage systems. By plugging-in costs of conventional reserves and capital costs of converter power ratings and energy storage capacity, the model is able to derive requirements for storage deployment that achieve the technical-economical optimum of the problem. The method leverages an efficient linearized formulation of the grid constraints of both the HV (High Voltage) and MV (Medium Voltage) grids while still retaining fundamental modeling aspects of the power system (such as transmission losses, effect of reactive power, OLTC at the MV/HV interface, unideal efficiency of battery energy storage systems) and models of conventional generator. A proof-of-concept by simulations is provided with the IEEE 9-bus system coupled with the CIGRE benchmark system for MV grids, realistic costs of power reserves, active power rating and energy capacity of batteries, and load and renewable generation profile from real measurements.
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 e
We consider some crucial problems related to the secure and reliable operation of power systems with high renewable penetrations: how much reserve should we procure, how should reserve resources distribute among different locations, and how should we
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Decentralized renewable energy systems can be low-carbon power sources, and promoters of local economies. It is often argued that decentralized generation also helps reducing transmission costs, as generation is closer to the load, thus utilizing the
The rapid deployment of distributed energy resources (DERs) in distribution networks has brought challenges to balance the system and stabilize frequency. DERs have the ability to provide frequency regulation; however, existing dynamic frequency simu