KEYWORDS: Wind energy, System integration, Power supplies, Safety, Photovoltaics, Thermoelectric materials, Data modeling, Thermal modeling, Statistical analysis, Analytical research
The rapid development of nuclear power energy has effectively alleviated the social power demand. However, the sensitive characteristics of nuclear power plant operation disturbances have a certain impact on the grid load. In order to improve the peak-shaving capability of nuclear power integration into the power system, a peak-shaving optimization method is proposed on the basis of full consideration of low-carbon constraints. First of all, this article introduces the principle of low-carbon restraint and establishes an evaluation framework for energy conservation and economic operation. Secondly, the peak shaving optimization problem is formally described, the sum of comprehensive costs is minimized as the objective function of optimal dispatching, and the corresponding constraints are set. In addition to considering the operation cost, the safety output characteristics of nuclear power units during peak shaving are considered, and multiple constraints are established. Finally, the peak shaving capacity of power system is determined, and the peak shaving optimization strategy of nuclear power access power system is formulated. The example results show that after the application of this method, the output of nuclear power unit is improved, the peak shaving accuracy and time-consuming are better than the traditional method, and the cost is effectively reduced, which shows that this method has high application value.
The electric power of nuclear power unit is mainly limited by the seawater temperature of external factors. When the seawater temperature rises, in order to avoid the thermal power and the opening of high-pressure regulating valve exceeding the limit, the unit operator must reduce the set value of electric power accordingly so as to affect the output of the unit. The internal operation parameters of the unit, such as main steam pressure, are more affected by the primary circuit, which is relatively stable and rarely fluctuated. To solve this problem, a regression model based on Stochastic Forest algorithm is established for the relationship between seawater temperature and electric power settings on the opening and thermal power of high pressure regulating valve. The predicted value of seawater temperature at a certain time and the set value of electric power gradually increasing from the smaller value are input into the random forest regression model so that the opening and thermal power of the high-pressure regulating valve output by the model at that time just do not exceed the limits of the operation regulations of the power station. The maximum electric power setting value that makes the opening of the high-pressure regulating valve and the thermal power just not exceed the limit is taken as the optimal electric power setting value at that time. Experiments show that the effect of this algorithm is more prominent than the traditional calculation methods, and the accuracy of the actual value of high-pressure regulating valve opening and thermal power meets the requirements. The research content of this paper promotes the application of smart turbine technology in the field of nuclear power, and has reference significance for the construction of nuclear power smart plant.
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