| Combined cooling heating and power microgrid(CCHP microgrid for short)is an energy supply system with energy storage,distributed energy and multiple loads for comprehensive utilization of cooling and heating.It has the advantages of clean and efficient,multi-energy combined supply,and plays an important role in the consumption of renewable energy sources.With the high proportion of renewable energy connected to the microgrid and the uncertainty of user demand,the traditional CCHP microgrid operation mode has not met the actual requirements.Based on this,this paper establishes a multi-scenario CCHP micro-grid multi-time scale stochastic optimal scheduling model,which gives full play to the advantages of CCHP system in a random environment,and enables the system to realize economic operation under the condition of high robustness.The main contents of this paper are as follows:Aiming at the problems of high cost and low resource utilization of CCHP microgrid scheduling under traditional operation mode,this paper proposes a multi-strategy improved sparrow search algorithm(MISSA)to solve the scheduling strategy.The global development and local exploration ability of the sparrow search algorithm are balanced by a variety of strategies such as the initialization of the population with a good point set,the vertical and horizontal crossing strategy,the Cauchy perturbation strategy and the introduction of an adaptive step factor.The time complexity is analyzed to verify the rationality of the improved algorithm;Compared with MISSA and other algorithms,the reliability of the multi-strategy improved sparrow search algorithm is verified;Taking the typical winter day as an example,the advantages of the improved algorithm are verified by different operation strategies.In view of the strong randomness of renewable energy and multiple loads,this paper proposes a scene reduction method combining improved k-means algorithm and backward reduction.In order to ensure that the reduced scene can reflect the characteristics of renewable energy and multiple loads,this paper determines the clustering number of k-means algorithm through elbow method to avoid subjective factors affecting the characteristics of the scene set;The concept of density and the principle of maximum and minimum ensure that the reduced scenario will not be too concentrated and can reflect the characteristics of renewable energy and multiple loads.The effect of scene reduction is evaluated by the sum of squares(SSE),Davies-Bouldin index(DBI)and contour coefficient.Finally,this paper establishes a multi-scenario CCHP microgrid multi-time scale stochastic optimal scheduling model.In the day-ahead stochastic optimal scheduling,the power balance equation of uncertain variables under the opportunity constraint is established,and the unbalance quantity is introduced to relax the power balance equation into an inequality,so that the inequality satisfies the opportunity constraint at a certain level of confidence.To ensure the reliability of the system,a chance-constrained reserve capacity model is established.Taking the expected cost under multiple scenarios as the objective function,the day-ahead stochastic optimal scheduling scheme is obtained.In the intra-day revised scheduling plan,rolling scheduling is carried out based on ultrashort-term forecast data,and power leveling is completed by using batteries,distributed energy and large power grids.In order to ensure the stable operation of CCHP microgrid,the output adjustment of each power supply is taken as the objective function 1;In order to improve the economy of intraday correction scheduling,the intraday correction cost is taken as the objective function 2,and the multi-objective is converted into a single objective by geometric weighting method.Finally,the effectiveness of the CCHP microgrid multi-time scale stochastic optimization strategy based on multi-scenarios is verified by an example analysis.Figure [61] Table [21] Reference [92]... |
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