Evaluation of Reliability in Risk-Constrained Scheduling of Autonomous Microgrids with Demand Response and Renewable Resources

Uncertainties in renewable energy resources and electricity demand have introduced new challenges to energy and reserve scheduling of microgrids, particularly in autonomous mode. In this study, a risk-constrained stochastic framework is presented to maximise the expected profit of a microgrid operator under uncertainties of renewable resources, demand load and electricity price. In the proposed model, the trade-off between maximising the operator's expected profit and the risk of getting low profits in undesired scenarios is modelled by using the conditional value-at-risk (CVaR) method. The influence of consumers' participation in demand response (DR) programs and their emergency load shedding for different values of lost load (VOLL) are then investigated on the expected profit of the operator, CVaR, expected energy not served and scheduled reserves of the microgrid. Moreover, the impacts of different VOLL and risk aversion parameters are illustrated on the system reliability. Extensive simulation results are also presented to illustrate the impact of risk aversion on system security issues with and without DR. Numerical results demonstrate the advantages of customers' participation in the DR program on the expected profit of the microgrid operator and the reliability indices.