Source network load storage multi-element ubiquitous optimization scheduling method for clean energy consumption

Abstract

The invention discloses a source network load storage multivariate ubiquitous optimization scheduling method for clean energy consumption. The method comprises the following steps: S1, determining a target function of a day-ahead low-carbon power generation scheduling model; s2, setting constraint conditions of the day-ahead low-carbon power generation dispatching model; s3, converting the low-carbon power generation dispatching optimization model into a single-target optimization model; s4, establishing a quantitative model of the carbon emission external cost; s5, establishing a risk assessment model, determining the operation risk indexes of the power system, calculating the weight omega E of each index by using an entropy method, calculating the weight omega A by combining an analytic hierarchy process, obtaining the final weight omega, and solving the safety comprehensive risk value of the power system in each time period; and S6, calculating a weight coefficient in the objective function based on a linear weighting method of a zero-sum game, and substituting the weight coefficient back into the original dual-objective optimization model to obtain an optimal power generation plan. According to the scheme, the carbon emission can be greatly reduced, and the method has guiding significance for establishing a lower-energy-consumption strong smart power grid.

Description

technical field [0001] The invention belongs to the field of optimal dispatching of electric power systems, and relates to a multiple ubiquitous optimal dispatching method of source, network, load and storage for clean energy consumption. Background technique [0002] Facing the increasingly severe pressure of abnormal climate change, human beings need to slow down the occurrence of extreme weather phenomena by controlling greenhouse gas emissions. Facing the prospect of future fossil energy depletion, it is necessary to vigorously develop renewable energy and increase Utilization efficiency, reducing human consumption and dependence on fossil energy, these two factors require the existing scheduling model to fully consider the issue of carbon emissions. At the same time, power generation scheduling must meet the basic requirements for safe operation of the power system, and at the same time reduce economic costs as much as possible to achieve low-carbon, safe, and economica...

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Problems solved by technology

[0004] The thermal power and new energy unit game and the day-ahead optimal dispatching model considering carbon emission reduction constraints are a mixed integer quadratic programming problem with complex calculations, a large number of constraints, and strong nonlinearity. It is not only difficult to solve directly , takes a long time, and may also face the problem of non-convergence. How to speed up the solution speed under the premise of ensuring a certain accuracy for the day-ahead scheduling model based on multi-objective optimization is the key point and difficulty that the future power system needs to solve

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