TY - JOUR
T1 - Maximization of Wind Energy Utilization through Corrective Scheduling and FACTS Deployment
AU - Kapetanaki, Alexandra
AU - Levi, Victor
AU - Buhari, Muhammad
PY - 2017
Y1 - 2017
N2 - The paper proposes a probabilistic methodology for minimizing wind spillage and maximizing capacity of the deployed wind generation, whilst improving system reliability. Capacities of the connected wind units are initially determined by using a method developed by the industry. A probabilistic approach is applied for the day-ahead planning to find maximum deployable wind sources so that the prescribed wind spillage is not exceeded. This is done using the optimum power flow, where wind spillages are prioritised with the probabilistic ‘cost coefficients’. Further improvement of wind energy utilization is achieved by installing FACTS devices and making use of real-time thermal ratings (RTTR). Two ranking lists are developed to prioritize location of SVCs and TCSCs, and they are then combined into a unified method for best FACTS placement. The entire methodology is realized in two sequential Monte Carlo procedures, and the probabilistic results are compared with the state enumeration ones. Results show improved wind utilization, network reliability and economic aspects.
AB - The paper proposes a probabilistic methodology for minimizing wind spillage and maximizing capacity of the deployed wind generation, whilst improving system reliability. Capacities of the connected wind units are initially determined by using a method developed by the industry. A probabilistic approach is applied for the day-ahead planning to find maximum deployable wind sources so that the prescribed wind spillage is not exceeded. This is done using the optimum power flow, where wind spillages are prioritised with the probabilistic ‘cost coefficients’. Further improvement of wind energy utilization is achieved by installing FACTS devices and making use of real-time thermal ratings (RTTR). Two ranking lists are developed to prioritize location of SVCs and TCSCs, and they are then combined into a unified method for best FACTS placement. The entire methodology is realized in two sequential Monte Carlo procedures, and the probabilistic results are compared with the state enumeration ones. Results show improved wind utilization, network reliability and economic aspects.
U2 - 10.1109/TPWRS.2017.2662802
DO - 10.1109/TPWRS.2017.2662802
M3 - Article
SN - 0885-8950
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
ER -