Electric heating load double-layer optimization scheduling method under multiple time scales

Abstract

The invention relates to the technical field of electric heating load optimization scheduling methods, in particular to an electric heating load double-layer optimization scheduling method under multiple time scales, which comprises the following steps of: firstly, classifying electric heating loads, establishing a historical data feature set model of multiple feature indexes under multiple time scales for controllable electric heating loads, and designing an index algorithm; and processing and designing a double-layer ordered power utilization scheduling model for predicting the dynamic demand of the electric heating load through a GRNN prediction model. According to the method, the accuracy and flexibility of power grid dispatching electric heating load prediction are improved, a double-layer dispatching strategy of a power grid layer and a user layer is achieved, and therefore orderly control over electric heating users is achieved under the condition that the satisfaction degree and comfort degree of the users are guaranteed, the reasonable electric heating time-of-use electricity price is designed. Therefore, the load rate and the operation stability of the power system undervarious heating load impacts are better improved, energy conservation and emission reduction are promoted, and benefit maximization of a power grid and users is realized.

Description

technical field

[0001] The invention relates to the technical field of an electric heating load optimization scheduling method, and relates to a double-layer optimal scheduling method for an electric heating load under multiple time scales. Background technique

[0002] my country is in the stage of accelerated industrialization and urbanization, especially in some areas where the winter is long and the demand for heating continues to grow rapidly, and the heating methods in remote areas mainly rely on old methods such as burning coal and firewood. Due to the long transportation distance, Due to the shortage of coal resources and other reasons, the heating cost is relatively high. In some areas, gas heating is used. Although it has the advantages of high energy utilization rate, high power supply reliability, small network loss, and low environmental pollution, it has high requirements for early architectural design and has problems such as safety hazards. On the contrary, t...

Examples

Embodiment 1

[0030] Embodiment 1: as figure 1 As shown, the double-layer optimal scheduling method of electric heating load under multiple time scales includes the following steps:

[0031] Step 1: Analyze the electric heating load, divide the load into coal-to-electricity users (as uncontrollable loads) and sporadic expansion and new installation users (as controllable loads), and formulate different scheduling strategies for the two types of loads.

[0032] Then, for the controllable load, a historical data feature set model with multiple characteristic indicators under multiple time scales is built. The model indicators are load characteristics under multiple time scales, including load power sequence, load maximum and minimum values, load trend information, load fluctuation Information and loads drastically change information. Use P to denote the multi-time scale historical load series, and use R p (t) represents the load trend information, with V p (t) and S p (t) respectively rep...

Embodiment 2

[0045] Embodiment 2: The double-layer optimal scheduling method for electric heating loads under multiple time scales includes the following steps:

[0046] step 1,

[0047] Step 1.1 firstly analyze the electric heating load. Since the present invention needs to realize the double-layer dispatching of loads, integrating the active switching of loads of the power grid and the user's independent adjustment of heating time according to the time-of-use electricity price, it is first necessary to extract the controllable loads and uncontrollable loads in the heating loads, Facilitate unified management of load.

[0048] The electric heating load is classified. The electric heating load mainly includes coal-to-electricity users and sporadic industry expansion and new installation users. In view of the current situation that sporadic industry expansion and new installation users have a high controllable load capacity, the present invention regards coal-to-electricity users as uncont...

Embodiment example

[0102]Taking electric heating in southern Xinjiang as an example to carry out the load as an example, as of March 2020, a total of 352,500 electric energy meters have been installed for electric heating in the three prefectures of southern Xinjiang, of which 306,700 households have been installed in coal-to-electricity projects, and 45,800 households have been installed in sporadic industries. Among them, coal-to-electricity transformation is mainly based on distributed carbon crystal (fiber), graphene, and heating cables, and sporadic industry expansion is mainly based on centralized electric (storage) heat boilers and heat pump heating. For coal-to-electricity users, among the 306,700 coal-to-electricity users in southern Xinjiang, only 8% of them continue to use electricity. Calculated according to the access capacity of 4,000 VA per household, the total controllable load capacity is only 98,000 KVA , and considering that the users of this type of load are all rural resident...

technical field

[0001] The invention relates to the technical field of an electric heating load optimization scheduling method, and relates to a double-layer optimal scheduling method for an electric heating load under multiple time scales. Background technique

[0002] my country is in the stage of accelerated industrialization and urbanization, especially in some areas where the winter is long and the demand for heating continues to grow rapidly, and the heating methods in remote areas mainly rely on old methods such as burning coal and firewood. Due to the long transportation distance, Due to the shortage of coal resources and other reasons, the heating cost is relatively high. In some areas, gas heating is used. Although it has the advantages of high energy utilization rate, high power supply reliability, small network loss, and low environmental pollution, it has high requirements for early architectural design and has problems such as safety hazards. On the contrary, t...

Examples

Embodiment 1

[0030] Embodiment 1: as figure 1 As shown, the double-layer optimal scheduling method of electric heating load under multiple time scales includes the following steps:

[0031] Step 1: Analyze the electric heating load, divide the load into coal-to-electricity users (as uncontrollable loads) and sporadic expansion and new installation users (as controllable loads), and formulate different scheduling strategies for the two types of loads.

[0032] Then, for the controllable load, a historical data feature set model with multiple characteristic indicators under multiple time scales is built. The model indicators are load characteristics under multiple time scales, including load power sequence, load maximum and minimum values, load trend information, load fluctuation Information and loads drastically change information. Use P to denote the multi-time scale historical load series, and use R p (t) represents the load trend information, with V p (t) and S p (t) respectively rep...

Embodiment 2

[0045] Embodiment 2: The double-layer optimal scheduling method for electric heating loads under multiple time scales includes the following steps:

[0046] step 1,

[0047] Step 1.1 firstly analyze the electric heating load. Since the present invention needs to realize the double-layer dispatching of loads, integrating the active switching of loads of the power grid and the user's independent adjustment of heating time according to the time-of-use electricity price, it is first necessary to extract the controllable loads and uncontrollable loads in the heating loads, Facilitate unified management of load.

[0048] The electric heating load is classified. The electric heating load mainly includes coal-to-electricity users and sporadic industry expansion and new installation users. In view of the current situation that sporadic industry expansion and new installation users have a high controllable load capacity, the present invention regards coal-to-electricity users as uncont...

Embodiment example

[0102]Taking electric heating in southern Xinjiang as an example to carry out the load as an example, as of March 2020, a total of 352,500 electric energy meters have been installed for electric heating in the three prefectures of southern Xinjiang, of which 306,700 households have been installed in coal-to-electricity projects, and 45,800 households have been installed in sporadic industries. Among them, coal-to-electricity transformation is mainly based on distributed carbon crystal (fiber), graphene, and heating cables, and sporadic industry expansion is mainly based on centralized electric (storage) heat boilers and heat pump heating. For coal-to-electricity users, among the 306,700 coal-to-electricity users in southern Xinjiang, only 8% of them continue to use electricity. Calculated according to the access capacity of 4,000 VA per household, the total controllable load capacity is only 98,000 KVA , and considering that the users of this type of load are all rural resident...

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