Ice melting coordination optimization method considering ice melting mode and system scheduling operation
A technology for scheduling operation, coordination and optimization, applied in computing, DNA computer, data processing applications, etc., can solve problems such as DC ice melting limitation and equipment configuration
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Embodiment 1
[0140] Embodiment 1: IEEEERTS-79 system is used as embodiment test system
[0141] Such as figure 2 As shown, the load reduction penalty fee is set to 1000$ / MWh. In this embodiment, a total of 6 lines are set to be covered with ice, as shown in Table 1. Among them, 4 lines are equipped with DC ice-melting devices, and the DC ice-melting method is used for deicing, and 2 lines are not equipped with DC ice-melting devices, and the ice is melted in the operation mode. The number of DC ice melting operation teams is 3 groups. The ambient temperature of rime covered with ice is -7°C, and the mass concentration of liquid water in the atmosphere is 0.25g / m 3 , the effective wind speed is 3m / s, and the median volume diameter of the droplets is 50μm. Set the outer diameter of the bare conductor of the transmission line to 21.88mm. Set the icing period to 48h, and the complete DC deicing operation usually takes 8h, and the deicing in the set operation mode also needs to be complet...
Embodiment 2
[0148] The electrical and meteorological parameters of the embodiment are brought into the collaborative optimization model, and the minimum operating cost and the minimum icing extreme value of the line are used as the dual objective function of the optimization model. The maximum number of iterations is set to 200 generations, the population size of each generation is 300, and the NSGA-II algorithm is used to solve the problem. Obtain the embodiment Pareto optimal solution set, this solution set contains three solutions, i.e. Case1-Case3, each ice-melting scheduling scheme is as follows Figure 4 shown.
Embodiment 3
[0150] The objective function and comprehensive cost corresponding to each ice-melting scheduling scheme are shown in Table 3 and Table 4, and the line ice thickness change curve is as follows: Figure 5 shown. It can be seen from Table 3 that these three solutions belong to the non-dominated relationship, among them, Case1 has the smallest extreme value of ice thickness but the highest comprehensive cost, Case3 has the smallest comprehensive cost but the largest ice thickness extreme value, and Case2 has the smallest comprehensive cost and the highest ice thickness extreme value. The values are all between Case1 and Case3. The optimal solution decision in Pareto solution set is shown in Table 5. Case2 balances the comprehensive cost and the extreme value of icing, and is the optimal decision of the ice-melting coordination optimization model that takes into account the ice-melting mode and system scheduling operation.
[0151] In summary, the minimum operating cost of the...
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