代写coursework Topics in Control: Stochastic Programming in Power Systems

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1. A system has three identical CCGT generators with 120MW each and a wind farm with 200MW capacity. The failure rate of CCGT is 3%, while the forecasting error of wind generation follows a normal distribution with zero mean and standard deviation of 20MW. In the system condition that all three CCGTs are online and wind farm is forecasted to produce 150MW, calculate the probability that 400MW/350MW/300MW of demand cannot be met. (Note: the failure of generators and wind forecasting error are independent processes)

2. Assume the wind power forecasting error is driven by a Gaussian AR(1) process with hourly timestep:
Error (k) = 1.2*Error (k-1) + 8*(k), (k) follows N(0,1) i.i.d
2.1 Please define a four-stage scenario tree for wind forecasting errors with five branches emanating from the root node, with quantiles 0.01, 0.1, 0.5, 0.9 and 0.99. Each node represents the wind forecasting error state over a 1-hour time interval.
2.2 Please define a four-stage scenario tree for wind forecasting errors with five branches emanating from the root node with quantiles 0.01, 0.1, 0.5, 0.9 and the top and bottom nodes in the second stage further branches into five scenarios at stage 3 with the same quantile structure.

Please draw the scenario tree and calculate the nodal wind forecasting error and probability代写.

3. Assume a system has three generator (G1, G2 andG3) and a wind farm (W1). The following table gives the technical characteristics of generators:

The cost of wind power production is 0 €/MWh, and its installed capacity is 75MW.
A four-hour time period (t0, t1, t2 and t3) is considered. The load in hours t0, t1, t2, and t3 is 215MW, 200 MW, 250 MW and 220 MW, respectively. The involuntarily load curtailment cost is €100/MWh. The wind farm is forecasted to produce 36MW, 43MW, 48MW and 35MW in hour t0, t1, t2 and t3. The wind forecasting error is assumed to follow the scenarios tree developed in question 2.1.

Please formulate a stochastic programming problem to find the optimal generation scheduling under forecasting error. Any coding environment can be used in this question.