Dynamic Economic Dispatch with Integration of Compressed Air Energy Storage Considering Large Penetration of Photovoltaic Generation Systems

The large penetration of Photovoltaic (PV) systems is reshaping the load demands curve. PV makes the load demand gaps very large, lower during the day, and higher at night. It creates a duck curve, which affects significantly the power system operation. In a duck curve, thermal generators' efficiency has decreased because their operations have not been optimal, thereby increasing fuel costs. Therefore, this research proposes Compressed Air Energy Storage (CAES) as energy storage for balancing the load demand. CAES saves the surplus power from the system and releases the saved power when the system needs it. The optimal Dynamic Economic Dispatch (DED) is carried out on CAES and thermal generators to determine optimal CAES operation and thermal generators output to meet the 24 hours load demand for saving thermal generators' fuel cost. Furthermore, the Quadratic Constrained Programming (QCP) on the DED is solved using the CPLEX solver. It has been applied to solve the 24-hour dispatch periods operation of IEEE 30 and IEEE 118-bus test system in order to verify the proposed system's effectiveness.