| With the increasingly prominent issues of global fossil energy depletion and ecological crisis,renewable green new energy has been vigorously explored and utilized,and a large number of distributed new energy has been integrated into the distribution network.However,the inherent intermittency and volatility of new energy make its large-scale grid connection a challenge to the operation and scheduling of traditional distribution station area power grid.Therefore,the construction of intelligent distribution station area power grid has become the mainstream trend.At the same time,with the continuous improvement of energy storage,the rise of terminal intelligent equipment and the popularity of electric vehicles,the load side also shows flexible characteristics to participate in the station area scheduling.The flexibility and adjustability of the flexible load itself is beneficial for smoothing the power fluctuations of renewable energy,achieving peak shifting and valley filling,and improving the safe and economic operation of the station area system.This thesis considers conducting research on the optimization scheduling strategy of distribution station area with flexible load participation under the premise of photovoltaic grid connection.The main content is as follows:The basic characteristics of the source,load,and storage units in the distribution station area are introduced.The power generation side includes the operating characteristics of photovoltaic power generation units and the charging and discharging characteristics of battery energy storage.The load side divides the generalized flexible load into reducible load,translatable load,and transferable load based on different scheduling response characteristics,and takes reducible air conditioning load and transferable electric vehicle load as typical representatives.Based on their participation in scheduling,schedulable capacity,and operational characteristics,scheduling model is established to lay a theoretical foundation for subsequent research.An economic optimization scheduling model for distribution station area with flexible source loads is established.Considering the optimization model of the station area with the goal of minimizing comprehensive operating costs,including power purchase costs,grid loss costs,operation and maintenance costs of photovoltaic and energy storage,scheduling costs that can reduce air conditioning loads,scheduling costs of energy storage,and charging costs of electric vehicles,the power balance,charging and discharging power of energy storage units,node voltage,etc.are constrained,and utilizing the principle of improved adaptive particle swarm optimization,the optimization model is successfully solved,based on the improved IEEE 33 node system,conduct numerical simulation and set three schemes for comparative analysis.The results validate the rationality and effectiveness of the proposed model and improved optimization algorithm.Considering the uncertainty of photovoltaic output,it will have a profound impact on the reliability of scheduling results.Firstly,a cardinality uncertainty set is used to describe the uncertainty of photovoltaic output,while still considering the minimum comprehensive operating cost of the station area.A two-stage robust optimization scheduling model for the station area is proposed.Then,Then,the model is decoupled and transformed into alternating main and sub problems using column and constraint generation algorithms.During the transformation process,the dual principle and linearization processing are used to transform the model into a deterministic solvable optimization problem,and the second-order cone relaxation technique is introduced to convex relax the constraint conditions.Finally,the model is solved using the YALMIP simulation platform in MATLAB and the commercial solver CPLEX efficient solver.The simulation results show that the proposed two-stage robust optimization scheduling method exhibits good robustness performance for uncertain photovoltaic output. |
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