The Study Of Dynamic Economic Dispatch And Reactive Power Optimization Based On Chance Constrained Programming

With the energy crisis and environmental issues becoming increasingly prominent, wind and solar energy and other renewable energy which are low carbon, clean, green, advantages, have been widespread attracted by state and society to obtain sustainable development, and therefore large-scale integrate the grid and gradually replace conventional energy sources. However, affected by the natural weather conditions and other reasons, renewable energy has a significant output volatility, volatility and intermittent, increasing the power system of uncertain factors that affects the security, reliably and economically of the power system and makes the power system’s control, dispatch and optimization of the active and reactive power facing the inevitable challenges. Therefore, that power system formulate dispatch and control strategy on basis of model uncertainty in an effective and reasonable method to ensure the safe and reliable operation of the grid and achieve economic conditions has important theoretical and practical engineering value.In the above context, from the perspective of the entire global coordinated and integrated power system based on chance constrained programming, safe and economic operation of power generation system with renewable energy resource is studied, the dynamic economic dispatch and reactive power optimization problem is focus on the paper. Main work and innovations are described as follows:(1)A multi-objective fuzzy chance constrained dynamic economic dispatch model considering energy saving and emission reduction is researched for energy saving and emission reduction benefits and uncertainty of renewable power sources to the power system. The fuzzy characteristics of the error are analyzed according to different prediction and the distribution parameters, and thus the fuzzy membership function of the intermittent power output and load is obtained. Then, different fuzzy measures chance constraints are formed for different system constraints considering fuzzy theory, this paper establishes a multi-objective fuzzy chance constrained dynamic economic dispatch model considering operating expenses and CO2 and SO2 emissions. To solve the model, chance constraints are turned into their clear equivalent forms using clear equivalent to avoid the huge workload of solving the simulation model, multi-objective is transformed into single-objective optimization through product fuzzy decision of multi-objective decision making theory to obtain the Pareto optimal solution, and an improved firefly algorithm making use of chaos optimization strategy is used to improve accuracy and convergence rate. The feasibility and effectiveness of the proposed model and algorithm are verified by the analysis of the case.(2)The mathematical model of dynamic economic dispatch to optimize the output of the generator and the spinning reserve simultaneously is established to the multiple uncertainties of power system. The power system with renewable energy have multiple uncertainties of renewable energy output, load and unit forced outage, leading to take the spinning reserve capacity decision into account when dynamic economic dispatch and increase the difficulty of problem solving undoubtedly. Given this problem, on basis of the fuzzy variable representing the renewable power source output and load and discrete random variable representing the forced outage rate of thermal power units, using the random and fuzzy chance constrained, the mathematical model of dynamic economic dispatch to optimize the output of the generator and the spinning reserve simultaneously is established, and the improved clear equivalent forms is used to deal with chance constrained. The model fully considers the cost differences of spinning reserve costs of units and economic benefits produced by the spinning reserve, the minimum difference of power reserve cost and spare economic benefits is added to the objective function of dynamic economic dispatch, to achieve system can maximize the overall economic benefits on basis of spinning reserve decision model. The feasibility and effectiveness of the proposed model are verified by 10 generation power systems.(3) For great impact to the reactive power optimization of renewable energy generation output and load, a fuzzy chance constrained reactive multi-objective power optimization model including multi-fuzzy parameters is established. Trapezoidal fuzzy parameters are used to express renewable energy powers output and load, the traditional deterministic optimal reactive power model is improved combining credibility theory and the minimizing fuzzy chance constrained programming,and a fuzzy chance constrained reactive multi-objective power optimization model is obtained. In the solution, the fuzzy objective function and chance constraints credibility are solved credibility fuzzy power flow on basis of incremental, and the multi-objective optimization is converted to a single-objective optimization using target membership functions and interactive satisfaction to get original Pareto optimal solutions of single-objective optimization, and the bat algorithm is also used to solve the model. Numerical results show that the multi-objective fuzzy chance constrained reactive power optimization model and algorithm is able to reflect uncertainty on power system reactive power optimization.(4) The distribution network fuzzy reactive power optimization model considering renewable power sources distributed generators (DGs) reactive power control capacity and fuzzy feature is proposed.The reactive power control capacity of PV station and wind turbine driven doubly-fed induction generator is analyzed through the operating characteristics of the inverter, and as its optimization variables, the active loss and node voltage deviation minimization are chosen as the objective function. A improved fuzzy power by flow incremental method and fuzzy set theory is proposed for solving the objective function and constraints credibility. The improved bat algorithm using chaos optimization strategy is proposed for solving the model to improve accuracy and convergence rate. The proposed model is verified by IEEE 33-bus system, to which the distributed PV generation and wind power generation are simultaneously added, and an optimal scheme possessing the meaning of fuzzy statistics is achieved, and the results show the efficiency of the model and algorithm.In summary, the energy saving and emission reduction and spinning reserve decisions of dynamic economic dispatch and reactive power optimization and the other active and reactive optimization of power system is researched and explored in the paper for the power system with large-scale renewable energy generation, and the corresponding models and algorithms based on chance constrained programming are proposed. Of course, there are many practical engineering problems requiring further study in this study in order to enrich, develop and improve on the combination of theory and practice.