Wind power plant extended photovoltaic multi-objective optimization method by considering boost main transformer capacity
A technology of multi-objective optimization and main transformer capacity, applied in the field of multi-objective optimization of wind farm expansion photovoltaic, can solve the problems of not considering the utilization level of electrical equipment in power plants, low utilization rate of electrical equipment, limiting engineering economy and practicability, etc. Achieve the effect of high engineering practical application value, low execution environment and maintenance requirements, and strong versatility
Inactive Publication Date: 2019-12-20
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +1
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Problems solved by technology
In addition, in most of the current research and design, the utilization level of the main electrical equipment of the power plant is not considered, resulting in a low utilization rate of the electrical equipment such as the step-up main transformer of the power generation system, which limits the economics and practicability of the project
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[0093] The present invention takes the photovoltaic power generation capacity expansion project of an existing wind farm in a certain area of Shandong Province as an example, and the optimized Pareto front-ends obtained under the two scenarios of not expanding the boosted main transformer and expanding a 50MVA boosted main transformer are respectively as follows figure 2 and image 3 shown. Assuming that the project investor requires the utilization rate of the booster main transformer to reach 35%, the waste rate of clean energy not to exceed 2%, and the lower the volatility, the better, then choose not to expand the booster main transformer and expand 32.2 hectares of photovoltaics as the final solution, As shown in Table 1.
[0094] Table 1 Final engineering scheme
[0095]
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The invention discloses a wind power plant extended photovoltaic multi-objective optimization method by considering boost main transformer capacity, which improves an independent wind-solar meteorological model, considers the correlation between wind speed and solar radiation intensity changes, and converts meteorological data into power generation output data. A multi-objective optimization modelby taking the field area and the boost main transformer capacity as constraint conditions is constructed, and a multi-objective optimization model by taking the maximum boost main transformer utilization rate, the minimum power variable coefficient and the minimum clean energy waste rate as objective functions is constructed; and, long-term meteorological data of a researched area is obtained through simulation by taking hours as a time scale based on a Monte Carlo method, a Pareto optimal solution set is solved by adopting a multi-target particle swarm algorithm, and the influence of expansion of the boost main transformer capacity on a final scheme is considered.
Description
technical field [0001] The invention relates to the field of new energy power generation, in particular to a multi-objective optimization method for wind farm expansion photovoltaics considering the capacity of booster main transformers. Background technique [0002] In recent years, wind power and photovoltaics have developed rapidly, and their installed capacity and penetration rate in the grid have reached a relatively high level. As intermittent energy sources, wind power and photovoltaics are potentially random and volatile, which limits the ability of the grid to accommodate wind and wind power generation and reduces the economics of power generation system operation. At the same time, wind power and photovoltaics have a natural complementarity in terms of time. During the day, the output of wind power is small, while the output of photovoltaics is large, and the opposite is true at night; in rainy weather, the output of wind power is large, and the output of photovolt...
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IPC IPC(8): H02J3/00H02J3/38H02J3/46G06F17/50
CPCH02J3/00H02J3/46Y02E10/76
Inventor 杨冬房俏张志轩麻常辉邢鲁华陈博马欢赵康周宁李山蒋哲李文博刘文学
Owner ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY
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