No abstract

In this paper, the impact of uncertainties in loads, renewable generation, market price signals, and event occurrence time on the feasible islanding and survivability of microgrids is analyzed. A data-driven approach is proposed for estimating the maximum deviation level of uncertain parameters dynamically based on historical data. Similarly, fragility curves are utilized for determining the preparation time for the potential events based on the estimated event occurrence time and physical constraints of the microgrid components. In addition, a resilience-oriented demand response program is proposed for enhancing the utilization of renewables and other available resources for reducing the load shedding during the emergency period. Finally, a resilience index is proposed for quantifying the benefits of the proposed method for the resilienceoriented operation of microgrids. In normal mode, the impact of event occurrence time and uncertainty level is analyzed via an adaptive robust optimization method. In emergency mode, 10 000 Monte Carlo scenarios of all the uncertain parameters are generated, and their impact on the operation cost, amount of load shed, and the range of the proposed resilience index are analyzed for each case.

Variables ∆e Error between the normalized frequency,ω, and the normalized DC voltage,V dc δ(b, t, c) Voltage angle of AC bus b at time t for contingency c δ(p, t, c) Voltage angle of AC bus p at time t for contingency c δ bp (t, c) Voltage angle difference between buses b, p at time t for contingency ĉ ω Normalized value of frequency ω V dc Normalized value of DC voltage ω Measured value of frequency ω at at time t C P V Capital cost of PV arrays C W T Capital cost of WT ES AC (b, t, c) Energy content in AC storage in bus b at the end of the current time step for contingency c P ex (b, t, c) Active power exchange between considered bus b and other buses at time t for contingency c P AC (g, t, c) Active power generation of AC generator g at time t for contingency c P ic (t, c) Active power flow through the interlinking converter at time t for contingency c P l AC (b, t, c) Active AC load at bus b at time t for contingency c P ls AC (b, t, c) Involuntary loss of active AC load at bus b at time t for contingency c P os AC (b, t, c) AC overslack for active power at bus b at time t for contingency c Q ex (b, t, c) Reactive power exchange between considered bus b and other buses at time t for contingency c Q AC (g, t, c) Reactive power generation of AC generator g at time t for contingency c Q ic (t, c) Reactive power flow through the interlinking converter at time t for contingency c Q l AC (b, t, c) Reactive AC load at bus b at time t for contingency c Q ls AC (b, t, c) Involuntary loss of reactive AC load at bus b at time t for contingency c Q os AC (b, t, c) AC overslack for reactive power at bus b at time t for contingency c S c AC (b, t, c) AC Storage charging into bus b at time t for contingency c S d AC (b, t, c) AC Storage discharging from bus b at time t for contingency c S AC (i, t, c) Apparent power of AC branch i at time t for contingency c V AC (b, t, c) Voltage at AC bus b at time t for contingency c V AC (p, t, c) Voltage at AC bus p at time t for contingency c V dc Measured value of DC voltage at time t

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This paper is concerned with the design of an autonomous hybrid alternating current/direct current (AC/DC) microgrid for a community system, located on an island without the possibility of grid connection. It is comprised of photovoltaic (PV) arrays and a diesel generator, AC loads, and battery energy storage devices for ensuring uninterruptible power supply during prolonged periods of low sunshine. A multi-objective, non-derivative optimisation is considered in this residential application; the primary objective is the system cost minimisation, while it is also required that no load shedding is allowed. Additionally, the CO 2 emissions are calculated to demonstrate the environmental benefit the proposed system offers. The commercial software, HOMER Pro, is utilised to identify the least-cost design among hundreds of options and simultaneously satisfy the secondary objective. A sensitivity analysis is also performed to evaluate design robustness against the uncertainty pertaining to fuel prices and PV generation. Finally, an assessment of the capabilities of the utilised optimisation platform is conducted, and a theoretical discussion sheds some light on the proposal for an enhanced design tool addressing the identified issues.