Auxiliary services are vital for the operation of a substation. If a contingency affects the distribution feeder that provides energy for the auxiliary services, it could lead to the unavailability of the substation’s service. Therefore, backup systems such as diesel generators are used. Another alternative is the adoption of a microgrid with batteries and photovoltaic generation to supply substation auxiliary services during a contingency. Nevertheless, high battery costs and the intermittence of photovoltaic generation requires a careful analysis so the microgrid capacity is defined in a compromise between the investment and the unavailability reduction of auxiliary services. This paper proposes a method for the capacity sizing of a microgrid with batteries, photovoltaic generation, and bidirectional inverters to supply auxiliary services in substations under a contingency. A set of alternatives is assessed through exhaustive search and Monte Carlo simulations to cater for uncertainties of contingencies and variation of solar irradiation. An unavailability index is proposed to measure the contribution of the integrated hybrid microgrid to reduce the time that the substation is not in operation. Simulations carried out showed that the proposed method identifies the microgrid capacity with the lowest investment that satisfies a goal for the unavailability of the substation service.

Battery systems bring technical and economic advantages to electrical distribution systems (EDSs), as they conveniently store the surplus of cheap renewable generation for use at a more convenient time and contribute to peak shaving. Due to the high cost of batteries, technical and economic studies are needed to evaluate their correct allocation within the EDS. To contribute to this analysis, this paper proposes a stochastic mathematical model for the optimal battery allocation (OBA), which can be guided by the optimization of two different economic metrics: net present value (NPV) and internal rate of return (IRR). The effects of the OBA in the EDS are evaluated considering the stochastic variation of photovoltaic generation and load. Tests with the 33-node IEEE test system indicate that OBA results in voltage profile improvement (~1% at peak time), peak reduction (31.17%), increased photovoltaic hosting capacity (18.8%), and cost reduction (3.06%). Furthermore, it was found that the IRR metric leads to a different solution compared to the traditional NPV optimization due to its inherent consideration of the relation between cash flow and investment. Thus, both NPV and IRR-based allocation alternatives can be used by the decision maker to improve economic and technical operation of the EDS.

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