Co-optimization of Battery Energy Storage System Incorporated with Dynamic Thermal Line Rating and Demand Response /

Abstract

Due to the increase in population and demand for electricity, traditional power systems may not be able to fulfill the electricity demand. Moreover, the increased use of conventional generators results in high emissions of greenhouse gases. One strategy for reducing carbon footprints is the incorporation of renewable energy sources into power networks. Due to the fixed capacities of transmission lines in traditional power systems, the integration of wind power in a network must be curtailed to minimize network congestion during high load levels. This will ultimately lead to higher dispatch costs, because of using more expensive generators to make up for the loss of wind integrations. Additionally, the integration of renewable energy in power systems is one of the challenging issues due to its fluctuating nature. Battery energy storage systems are installed in the existing network to mitigate output fluctuations, store the extra wind energy during off-peak demand periods, and discharge the stored energy when wind production is not adequate. It is essential to make existing power systems more flexible to deal with ever-increasing demand. Dynamic line rating is used to make the system more flexible by enhancing existing line capacities, thus reducing network congestion. Demand response is another flexible option that is advantageous for both utilities as well as customers from an economic point of view. It allows consumers to shift their electricity usage from peak periods to off-peak hours. In this paper, wind energy is optimally integrated into the IEEE RTS-24 bus system by linearized formulation of DC-OPF, and MILP is adopted for problem assessment in MATLAB. This study combines all the above-mentioned cost-effective technologies to evaluate their collaborative effect on the power system’s wind curtailment, load curtailment, and generator dispatch cost. Results indicate that the combination of these three technologies can improve the operational cost of the power system more than either stand-alone technology or a combination of two technologies.