Research On Operation Strategy And Random Optimization Scheduling Of Combined Cooling, Heating And Power

Based on the principle of energy cascade utilization, CCHP (Combined Cooling Heating and Power) system has its own advantages when supply a variety of secondary energy, it has a high efficiency in comprehensive utilization of energy with less pollution, which makes it has wide application prospects in effectively relieving the energy crisis and promoting the sustainable development of energy. The balance of energy involves coordination and dispatching of the refrigeration, heating and power supply as well as other kinds of power unit;Therefore, reasonable measuring the internal energy flow function, calculating the optimal operation strategy, and analyzing the best way of photovoltaic, wind and other renewable energy to access to CCHP system are of great practical significance for the development and application of the CCHP system as well as the efficient use of renewable energy. The thesis comprehensively overviewed the CCHP system, including its operation strategy, economic environmental optimization scheduling, and a brief introduction of the research status of stochastic optimization method. An in-depth research also has been done about the physical significance and the applicable scope of some random factors processing method, such as chance-constrained programming, Value at Risk and Conditions of risk value method, superquantile method, etc. The mainly research work of the thesis are as follows. (1) Based on the existing stochastic optimization method of the research, in view of the conditional value at risk approach in solving the inconformity with the physical significance which occurs in the process of solving power system efficiency objective function. Put forward the Conditional Value-at-benefit based on probability (CVaB) to solve stochastic optimization model. And the corresponding mathematical reasoning and proof is given. At a given confidence level, the optimal efficiency value that the optimization goal could achieve is VaB (Value-at-benefit based on probability), CVaB reflected the benefit expectation value under the condition that the objective function less than VaB. CVaB embarks from the actual situation and is a better way to provide optimum decision-making information for conservative decision makers, and enriches the optimization decision method. (2) CCHP system of cold, heat, electricity load changes and balance have different characteristics and regularity, although the real-time load changes, due to the periodic balance characteristic of the heating and cooling, but electric power real-time balance, the scheduling can implement operation strategy of Thermal Load Dominant Mode(TLDM) and Electric Load Dominant Mode(ELDM). Considering the energy flow characteristics of energy balance after wind electricity access the CCHP system, the thesis describes energy flow function under the running strategy of TLDM and ELDM, economic environmental optimization scheduling model is established by energy flow function. The objective function of the model include the fuel cost of each power unit, the electricity purchasing cost between the interaction of CCHP system and city grid and the environmental cost of pollution emissions. The simulation results shows that the proposed energy flow function under different operation strategy and economic environmental scheduling optimization model can realize the effect of reducing pollution emissions and achieve sustainable use of the energy efficiency under the premise of the CCHP system’s promoting the economic benefit.(3) In order to improve the utilizations of wind energy and reduce its influence of randomness on CCHP system, the thesis puts forward the wind powered participated in CCHP system in heating and power supply manner heating mode and power mode. To get the needed mode control decision-making information, wind energy mode control system is established and analyzed. In view of the two power modes, respectively established the objective function of optimization model which include the cost of fuel and electricity purchasing cost of system operation cost. Considering wind power output prediction deviation, superquantile method is used to depict the random objective function, and then the corresponding stochastic optimization model is established. Simulations of the economic benefits of wind power system under different power modes are analyzed, and studied the influence of different confidence level on system operation cost. Results provide a basis for the choice of wind energy mode; the research provides new ideas for high-efficient and logical utilization of renewable energy under the background of the smart grid.