Stochastic Seasonal Planning of DG-Based Smart Grid and Energy Hub by Considering Demand Response Program and Environmental Impacts

This paper presents a stochastic optimization program for multi-objective cost and environmental pollution optimization in a network over a one-year time horizon. In this context, the system operator, in addition to planning equipment utilization, mitigates the effects of existing fluctuations in the uncertain input parameters by employing demand response programs. Random functions are used to model the oscillatory behavior of wind turbine speed. Furthermore, planning is performed for different seasons of the year to examine the sensitivity of the obtained response to weather conditions. To simulate the proposed model, a mixed-integer linear programming (MILP) approach is employed, and the GAMS software is used to solve it. Considering uncertainty in wind turbine generation, the proposed model is applied to a test microgrid consisting of multiple energy carriers. Simulation results demonstrate the impact of demand response programs while increasing the cost of planning due to the consideration of uncertainty in the system.