Wind Farm Diversification and Its Impact on Power System Reliability

Abstract

As wind exploitation gains prominence in the power industry, the extensive use of this intermittent source of power may heavily rely on our ability to select the best combination of wind farming sites that yields maximal reliability of power systems at minimal cost. This research proposes a general method to minimize the wind park global power output variance by optimally distributing a predetermined number of wind turbines over a preselected number of potential wind farming sites for which the wind patterns are statistically known. The objective is to demonstrate the benefits of diversification for the reliability of wind-sustained systems through the search for steadier overall power outputs. Three years of wind data from the recent NREL/3TIER study in the western US provides the statistics for evaluating each site for their mean power output, variance and correlation with each other so that the best allocations can be determined. Some traditional reliability indices such as the LOLP are computed by using sequential Monte Carlo simulations to emulate the behavior of a power system uniquely composed of wind turbines and a load modeled from the 1996 IEEE RTS. It is shown that configurations featuring minimal global power output variances generally prove the most reliable for moderate load cases, provided the sites are not significantly correlated with the modeled load. Under these conditions, the choice of uncorrelated/negatively correlated sites is favored. The correlations between the optimized global wind power outputs and the modeled load are studied as well.