Intelligent community demand response scheduling method and system

A technology of intelligent community and demand response, applied in the field of power grid

Pending Publication Date: 2019-05-10
STATE GRID JIANGSU ELECTRIC POWER CO ELECTRIC POWER RES INST +4
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Problems solved by technology

However, there are few methods on how to comprehensively utilize the complementary characteristics of multi-energy, de

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  • Intelligent community demand response scheduling method and system
  • Intelligent community demand response scheduling method and system
  • Intelligent community demand response scheduling method and system

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specific Embodiment

[0111] In this embodiment, an intelligent community is taken as an example, and the effectiveness of the method is verified by comparing the charging and discharging curves of energy storage and electric vehicles before and after.

[0112] A demand response scheduling method for an intelligent community, comprising the following steps:

[0113] (1) Determine the intelligent community optimization evaluation index according to the load type of the user in the intelligent community scene, and the intelligent community optimization evaluation index includes the electric vehicle charging and discharging power and the energy storage system charging and discharging real-time power;

[0114] The community in the embodiment is equipped with 10 charging piles, and the rated power of each charging pile is 10kW; the rated voltage of the vehicle-mounted lithium battery is 250V, and the rated capacity is 100A·h. The application scenario of electric vehicles is set to arrive at the parking ...

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Abstract

The invention provides an intelligent community demand response scheduling method and system, and the method comprises the steps: employing the minimum total operation cost of a system and the minimumexchange electric quantity of a power grid as a target function, building an optimal scheduling model comprising photovoltaic, energy storage and electric vehicles, and carrying out the solving through employing a multi-population collaborative purification genetic algorithm, and obtaining an optimization result. The method comprises the following steps: firstly, analyzing main components of theintelligent cell, and researching the operation characteristics of the intelligent cell; For the coordinated optimization scheduling problem of the daily load demand response of intelligent power cells containing multiple energy resources, the residential intelligent power mode including distributed energy such as electric vehicles and energy storage is taken as the research object. The minimum total operation cost of a system and the minimum exchange electric quantity of a power grid are taken as objective functions, the constraint conditions of schedulable loads, electric vehicles, distributed energy storage and the like are considered, a multi-population collaborative purification genetic algorithm is used for solving, an optimization result is obtained, peak clipping and valley fillingare achieved, and finally the effectiveness of an optimization model and a solving strategy is analyzed by means of examples.

Description

technical field [0001] The invention belongs to the technical field of power grids, and relates to a demand response scheduling strategy for an intelligent community based on a multi-population co-evolutionary genetic algorithm. Background technique [0002] With the development of supporting technologies such as intelligent collection, sensing, and control, the large-scale application of intelligent communities becomes possible. In 2017, the "Intelligent Community Demonstration Project", one of the supporting projects of the national key research and development plan "Urban User and Power Grid Supply-Demand Friendly Interactive System", carried out large-scale promotion. At present, 6 intelligent communities have been completed in Wujin, Changzhou and Jinji Lake, Suzhou. , mainly for the construction of resident user interaction capabilities, the construction of photovoltaic storage in public areas of communities, and electric vehicles. As a key component of smart communit...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06Q10/04G06N3/00
Inventor 陆子刚卢树峰黄奇峰郑爱霞何胜陈振宇杨斌阮文骏史忠伟
Owner STATE GRID JIANGSU ELECTRIC POWER CO ELECTRIC POWER RES INST
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