Considering day-ahead hourly electricity price and multiple demand responses to promote wind power acceptance level
A demand response and wind power acceptance technology, applied in data processing applications, instruments, forecasting, etc., can solve problems such as lack of flexibility in load adjustment
Active Publication Date: 2021-01-29
STATE GRID FUJIAN ELECTRIC POWER CO LTD
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Problems solved by technology
In the peak and valley electricity price, the electricity price is divided into three periods of peak, flat and valley, which is inflexible to the adjustment of load; in the real-time electricity price, the electricity price fluctuates with the change of the market, which has a great influence on the adjustment of the user's own electricity consumption plan
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[0072] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.
[0073] A method of the present invention that considers the day-ahead hourly electricity price and various demand responses to promote the acceptance level of wind power, in the case of large-scale wind power access, considers the influence of the day-ahead hourly electricity price on the price-type demand response users and the incentive-type demand response users, and establishes A day-ahead hourly electricity price optimization under the condition of wind power uncertainty and a two-level planning model including wind power power system dispatching considering incentive demand response; using Latin hypercube sampling to generate a large number of wind power scenarios, using the synchronous back-substitution method to reduce the scenarios, through The quantum particle swarm algorithm solves the model; under the constraint conditions, the...
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The invention relates to a method for promoting wind power acceptance level considering the day-ahead hourly electricity price and multiple demand responses. In the case of large-scale wind power access, the influence of the day-ahead hourly electricity price on price-type demand response users and incentive-type demand response users are considered, and the establishment A day-ahead hourly electricity price optimization under the condition of wind power uncertainty and a two-level planning model including wind power power system dispatching considering incentive demand response; using Latin hypercube sampling to generate a large number of wind power scenarios, using the synchronous back-substitution method to reduce the scenarios, through The quantum particle swarm algorithm solves the model; under the constraint conditions, the optimal day-ahead hourly electricity price, optimal wind power acceptance, optimal thermal power unit dispatching output, and optimal incentive demand response call volume are obtained. The method of the invention can guide users to cut peaks and fill valleys, effectively promote the acceptance of wind power, reduce the cost of thermal power generation and increase the benefits of users.
Description
technical field [0001] The invention relates to the field of power market analysis, in particular to a method for promoting wind power acceptance level considering day-ahead hourly electricity price and various demand responses. Background technique [0002] Wind power is currently the fastest growing and most widely used new energy. However, new energy power generation generally has randomness and volatility. In addition, wind power also has typical anti-peak characteristics. At present, the main factors restricting wind power consumption in my country are system peak-shaving capacity and power grid transmission capacity. The fundamental reasons affecting system peak-shaving capacity are the aggravation of load peak-valley difference and insufficient capacity of system peak-shaving units after large-scale access of wind power. [0003] Demand response projects generally classify loads into price-based load response, incentive-based load response, and loads that are not con...
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IPC IPC(8): G06N3/00
CPCG06Q10/04G06Q10/06315G06Q30/0283G06Q50/06Y04S50/14
Inventor 方日升刘文彬王其瑜王良缘王颖帆杨首晖江岳文温步瀛林建新张艺渊
Owner STATE GRID FUJIAN ELECTRIC POWER CO LTD