Confronting the Duck Curve Problem Using Dynamic Economic Emission Dispatch with CAES

Abstract

The high requirement for electrical energy, Photovoltaic (PV) installation price and environmental issues have led to PV installations' recent worldwide growth. The large PV penetration changes the daily load demands curve, especially on a sunny day, making a massive gap between load demands in the day and the night. This load demand curve shapes the duck curve both in the generation and the load demand side. In a duck curve, thermal generators' fuel costs and emissions are increased because their operation is not optimal, decreasing efficiency. In this study, compressed air energy storage (CAES) is added to the system for load demand balancing. The optimal dynamic economic emission dispatch (DEED) is performed to determine the best pattern of CAES operation and the optimal output of thermal generators to satisfy the 24-hour load demand for minimizing the fuel costs and emissions of the thermal generators simultaneously. The quadratic constrained programming is applied in this paper as the optimization tool for the DEED problem, and it is determined by using the CPLEX solver. Furthermore, the proposed model's feasibility is illustrated using different cases based on the IEEE 30-bus system. As a result, according to the comprehensive operational flexibility analyses, the proposed system is capable to handles the fast ramp of the duck curve, proved by no flexibility deficit in the planning periods. Finally, the thermal generators' fuel costs and emissions are also minimized. The total fuel cost was saved around $1180/day in case 1, $1970/day in case 2, and $3630/day in case 3, while the quantity of emissions was reduced by around 96.449 tons/day in case 1, 198.786 tons/day in case 2, and 351.193 tons/day for case 3.