Dynamic Optimal Power Flow Based on a Spatio-Temporal Wind Speed Forecast Model

With large wind energy penetration to power grid, power system operation has become more complex due to the intermittency of wind. For an efficient operation of wind energy, accurate wind speed forecast is in urgent need. Here, a statistical wind speed forecast model is proposed which considers the spatial and temporal correlations in wind speed and wind direction among geographically dispersed wind farms. Then the forecast model was incorporated in the one-day ahead dynamic optimal power flow for power system operation. Dynamic optimal power flow is a highly non-linear and non-convex with large control variable optimization problem. Modern heuristic optimization techniques have proven their efficiency and robustness to such problem, so this work focuses on a novel heuristic method, artificial bee colony. The original artificial bee colony was modified in this work for dynamic optimization. The forecast model has been verified by comparing with actual wind speed. Several case studies are implemented on a modified IEEE 30-bus system to verify the performances.