Abstract
The uncertainty of wind farm power and load both have a certain impact on the economic dispatch of the power system. First, this study deals with the fuzzy processing of power prediction error and load forecasting error of wind farms based on fuzzy random theory. On this basis, a multi-objective fuzzy stochastic dispatch model of a power system with flexible load is established under the carbon trading mechanism. And, the nonlinear cost of flexible load response and the cost of carbon emission compensation is introduced to the multi-objective function of the model. In addition, the fuzzy chance constraint of the spinning reserve is added to the constraint conditions. By introducing the variable, the fuzzy random dispatch model is transformed into a clear equivalent model. Finally, the discrete bacterial colony chemotaxis algorithm is used to process the model, and the optimal solution to the multi-objective function is obtained by a compromise strategy based on a small degree of satisfaction. In the simulation, a classic IEEE10 system and a wind farm are taken as examples. The results show that compared with the other three traditional dispatch models, the total power generation cost is reduced by US$13 670, US$5610 and US$86 010, respectively using the model proposed in this article.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.