Integrating wind and solar power into the grid requires dispatching various types of reserve generation to compensate for the randomness of renewable power. The dispatch is usually determined by a system operator (SO) or an aggregator who `firms' variable energy by bundling it with conventional power. The optimal dispatch is formulated as the solution to a stochastic control problem and shown to have a closed form that can be quickly computed. Different objectives and risk constraints can be included in the formulation and trade-offs can be evaluated. In particular one can quantify the influence of sequential forecasts on the total integration cost and the choice of dispatched generation. When the forecast error is Gaussian, the optimal dispatch policy can be precomputed.

%B 2012 American Control Conference (ACC) %I IEEE %C Montreal, QC %P 4417 - 4422 %8 06/2012 %@ 978-1-4577-1095-7 %R 10.1109/ACC.2012.6315239 %0 Conference Paper %B 2012 45th Hawaii International Conference on System Sciences (HICSS) %D 2012 %T Selling Random Wind %A Eilyan Bitar %A Kameshwar Poolla %A Pramod P. Khargonekar %A Ram Rajagopal %A Pravin Varaiya %A Felix Wu %K CERTS %K electricity markets %K reliability %K reliability and markets %K renewables integration %K RM11-006 %XWind power is inherently random, but we are used to 100 percent reliable or 'firm' electricity, so reserves are used to convert random wind power into firm electricity. The cost of these reserves is frequently a hidden subsidy to wind power producers. We propose an alternative: package random wind power into electricity with different levels of reliability and sell them at different prices. This variable-reliability market is more efficient than the current firm-electricity market, and may require lower subsidy. However, we have to think of electricity differently. We also explore interesting differences between the variable-reliability and related real-time markets.

%B 2012 45th Hawaii International Conference on System Sciences (HICSS) %I IEEE %C Maui, HI, USA %P 1931 - 1937 %8 01/2012 %@ 978-1-4577-1925-7 %R 10.1109/HICSS.2012.523