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With the advent of an era of the high fossil energy cost and growing environment consciousness, wind power is gaining great favor over other traditional energy sources. Large scale usage of wind energy can significantly reduce the pollutions and carbon emission otherwise caused by fossil fuel. In many cases, with tax incentive, investment in wind energy can also reduce the operational cost of generating companies. One difficulty of integrating large scale wind power is related to the uncertainty in wind power. Unlike hydro energy which is also renewable and intermittent, wind power output is hard to predict precisely due to the indeterminacy in wind speed. The uncertainty not only causes difficulty in scheduling, but also system stability and security concerns in operation. This work proposed a short-term(24 hours) optimal economical dispatch model and developed a risk evaluation method for the short-term operation of power systems with high wind penetration, considering the wind variability. We use the Particle Swarm Optimization(PSO) algorithm with constraints to solve the dispatch problem above. The Value at Risk(VaR) and Utility function(UF) are used to evaluate the risk and make a optimal tradeoff between the profit and risk for the system operators. The algorithms are tested on the standard IEEE 30-bus power system to validate the applicability.