Intelligent home optimized operation method suitable for electric automobile and energy storage device

Abstract

The invention discloses an intelligent home optimized operation method suitable for an electric automobile and an energy storage device; the intelligent home optimized operation method comprises the following steps: (1) an intelligent home optimized operation object function is established; (2) constraint conditions for optimized operation are designated, and a GAMS solving model is adopted. The beneficial effects of the electric automobile and energy storage device-based intelligent home optimized operation method that are when electricity price uncertainty is considered, optimized home operation conforms with actual decision making processes; the intelligent home optimized operation method is applicable to abundant objects, and economic value of intelligent use of electricity can be fully tapped.

Description

technical field [0001] The invention relates to the technical field of intelligent power utilization in a smart grid of a power system, in particular to a smart home optimization operation method considering electric vehicles and energy storage equipment. Background technique [0002] With the continuous development and progress of the social economy, the proportion of residential electricity consumption in the total electricity consumption of the whole society is increasing. Under the background of vigorously developing the smart grid, the smart electricity consumption of residents is an important part of the implementation of demand response strategies on the residential side. It is an important manifestation that it has great potential in reducing the compound peak-to-valley difference, reducing the capacity of standby units, and absorbing the output of renewable energy. Since the concept of smart home was proposed in the 1990s, domestic and foreign scholars have carried o...

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Problems solved by technology

In the prior art, under the background of time-of-use electricity price, according to the characteristics of different operating rules of each household appliance, the household appliance load is classified, and an optimization model with the goal of minimizing the user's electric energy cost and minimizing the peak-to-valley difference is established. In the model The working mode of electric vehicles and energy storage batteries is single. Compared with the real-time electricity price environment, its optimization potential has not been fully utilized; through the introduction of electricity price priority, demand response control rules and pre-scheduling mechanisms to realize the operation control of some household equipment, The purpose of reducing the overall cost of users and alleviating the grid load is obtained, but the effect is not obvious, and new energy and electric vehicles have not been considered; under the premise of meeting the requirements of the given power consumption of demand response and the comfort level of users, according to The real-time dynamic priority of the controlled load executes the power consumption decision, which reduces the power consumption cost while improving the grid load curve and reducing the peak-to-valley difference; Charge and discharge control, to achieve the purpose of reducing the total cost of electricity, but the optimal control of electric vehicle charge and discharge and self-owned power generation equipment that have the potential to reduce peak loads are not considered; the establishment of a mixed integer model for smart homes considers electric vehicles and All operating modes of the energy storage battery, but ignore the user's maximum power limit, which may increase the load peak-to-valley difference

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