WIND POWER CONSUMPTION METHOD OF VIRTUAL POWER PLANT WITH CONSIDERATION OF COMPREHENSIVE DEMAND RESPONSES OF ELECTRICAL LOADS AND HEAT LOADS

Abstract

The present invention discloses a wind power consumption method of a virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads, which comprises: establishing a wind turbine output model, so as to obtain a wind power prediction curve; establishing heat load demand models before/after demand responses and heat supply equipment output models before/after the demand responses, so as to obtain the abandoned wind quantities per moment before/after the demand responses and the total abandoned wind quantities before/after the demand responses; judging that whether consumption is promoted or not according to the total abandoned wind quantities before/after the demand responses; and establishing a storage battery capacity model and judging the charging/discharging state and the charging/discharging capacity of a storage battery.

Description

CROSS REFERENCES TO RELATED APPLICATIONS

The present application claims foreign priority of Chinese Patent Application No. 202110296018.0, filed on Mar. 19, 2021 in the China National Intellectual Property Administration, the disclosures of all of which are hereby incorporated by reference.

TECHNICAL FIELD

The present invention belongs to field of consumption of abandoned wind, and particularly relates to a wind power consumption method of a virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads.

BACKGROUND OF THE PRESENT INVENTION

Clean energy is greatly developed due to environmental protection and renewability thereof, but at the same time, a lot of problems are caused, wherein due to the characteristics of randomness and volatility of wind power, a power grid is impacted by wind power integration; and the energy utilization rate is lower. Therefore, a wind power consumption method is studied, which has great significance for reducing abandoned wind.

Comprehensive energy scattered in a region is gathered and controlled by a virtual power plant through an advanced communication technology, so that a power generation and distribution system with excellent controllability is formed, and an effective way is provided for wind power consumption. Due to the continuous growth of various types of loads represented by electrical loads and heat loads in the power generation and distribution system, the operation of the virtual power plant needs to be coordinated and optimized. As controllable loads participate in demand responses, the economy of the system can be improved; the energy consumption capacity of the virtual power plant can also be improved; and the problem of local consumption of abandoned wind is alleviated. Therefore, it is necessary to consider comprehensive demand responses of various loads, such as comprehensive demand responses of the electrical loads and the heat loads, in order to effectively promote the wind power consumption of the virtual power plant.

SUMMARY OF PRESENT INVENTION

The present invention aims to provide a wind power consumption method of a virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads for the operation cost of the virtual power plant.

The technical solution adopted by the present invention comprises the following steps:

(1) establishing a wind turbine output model, so as to obtain a wind power prediction curve by the wind turbine output model;

(2) establishing a heat load demand model before demand responses and a heat supply equipment output model before the demand responses, so as to obtain the demand of the heat loads before the demand responses according to the heat load demand model before the demand responses; taking the heat supply equipment output model before the demand responses as an electrical boiler output model before the demand responses in the virtual power plant and calculating the wind power quantity consumed by heat supply equipment before the demand responses according to the electrical boiler output model before the demand responses and the demand of the heat loads before the demand responses; and calculating the abandoned wind quantity per moment before the demand responses and the total abandoned wind quantity before the demand responses according to the wind power prediction curve, the known demand of the electrical loads before the demand responses and the known wind power quantity consumed by the heat supply equipment before the demand responses;

(3) establishing a heat load demand model after the demand responses and a heat supply equipment output model after the demand responses, so as to obtain the demand of the heat loads after the demand responses according to the heat load demand model after the demand responses; and taking the heat supply equipment output model after the demand responses as an electrical boiler output model after the demand responses in the virtual power plant and calculating the wind power quantity consumed by the heat supply equipment after the demand responses according to the electrical boiler output model after the demand responses and the demand of the heat loads after the demand responses;

(4) calculating the demand of the electrical loads after the demand responses; calculating the abandoned wind quantity per moment after the demand responses and the total abandoned wind quantity after the demand responses according to the wind power prediction curve, the demand of the electrical loads after the demand responses and the wind power quantity consumed by the heat supply equipment after the demand responses; then calculating the difference value between the total abandoned wind quantity before the demand responses and the total abandoned wind quantity after the demand responses; if the difference value is more than 0, judging that the wind power consumption is promoted; and if the difference value is less than 0, judging that the wind power consumption is not promoted; and

(5) establishing a storage battery capacity model; judging that a storage battery is in a charging state or in a discharging state and judging the charging/discharging capacity according to the storage battery capacity model and the abandoned wind quantity per moment after the demand responses; when the abandoned wind quantity per moment after the demand responses is more than 0, charging the storage battery; and when the abandoned wind quantity per moment after the demand responses is less than 0, discharging the storage battery to assist a wind turbine to supply power.

In the step (1), the wind turbine output model is:

$g_{\mathrm{WPP}}\left(t\right)=\{\begin{array}{cc}0,& v_t\le v_{in}\\ \frac{v_t-v_{in}}{v_R-v_{in}}g,& v_{in}\le v_t\le v_R\\ g,& v_R\le v_t\le v_{\mathrm{out}}\\ 0,& v_t\ge v_{\mathrm{out}}\end{array}$

wherein in the formula, g represents the rated power of the wind turbine; v_in represents the cut-in wind speed of the wind turbine; v_R represents the rated wind speed of the wind turbine; v_out represents the cut-out wind speed of the wind turbine; v_t represents the real-time wind speed of the wind turbine at the moment t; t represents the moment t; and g_WPP (t) represents the actual output of the wind turbine at the moment t; and

the actual output of the wind turbine meets the following constraint condition:

g _WPP ^min ≤g _WPP(t)≤g_WPP^max

wherein in the formula, g_WPP^min represents the lower limit of power of the wind turbine; and g_WPP^max represents the upper limit of power of the wind turbine.

In the step (2), the heat load demand model before the demand responses is:

$Q_{\mathrm{heart}}^1\left(t\right)=\sum _{t=1}^{24}\left(C_{\mathrm{air}}{\rho }_{\mathrm{air}}\mathrm{NSH}+\partial \mathrm{KA}\right)\left(T_{\mathrm{PMV}}^1-T_{\mathrm{out}}\left(t\right)\right)-Q_{\mathrm{inc}}-Q_{\mathrm{inh}},$

wherein in the formula, Q_heart1^(t) represents the demand of the heat loads before the demand responses; ∂ represents the modified temperature difference factor of an envelope enclosure; K represents the heat transfer coefficient of the envelope enclosure; A represents the area of the envelope enclosure; T_out (t) represents the outdoor temperature at the moment t; Car represents the specific heat capacity of air; ρ_air represents the air density; N represents the air change rate; S represents the area of a building; H represents the indoor height of the building; Q_ine represents the calorific value of electrical equipment; Q_inh represents the calorific value of a human body; and T_PMV¹ represents the set indoor temperature before the demand responses;

the set indoor temperature T_PMV¹ before the demand responses is calculated by the following formula:

$T_{\mathrm{PMV}}^1=T_S-\frac{M\left(2.43-{\lambda }_{\mathrm{PMV}}^1\right)\left(I_{\mathrm{cl}}+0.1\right)}{3.76};$

in the formula, T_S represents the human skin temperature in a normal temperature state; M represents the human energy metabolism rate; λ_PMV¹ represents the initial PMV (Predicted Mean Vote) index; Ii represents the dress heat resistance; and when in calculation, λ_PMV¹ is set as 0, and the set indoor temperature T_PMV¹ before the demand responses is obtained, so as to obtain the demand Q_heart¹(t) an of the heat loads before the demand responses according to the heat load demand model before the demand responses; and

the PMV index refers to the average scale prediction for thermal sensation; the PMV index is divided into seven levels: λ_PMV represents the optimum temperature state accepted by the human body at the moment 0; λ_PMV+1, λ_PMV+2 and λ_PMV+3 respectively represent slightly warm, warm and hot; and λ_PMV−1, λ_PMV−2 and λ_PMV−3 respectively represent slightly cool, cool and cold. The scope (−0.5−0.5) of the PMV index is the scope accepted by the human body according to the ISO-7730 standard code.

the electrical boiler output model before the demand responses is:

Q ¹ _EB(t)=g¹_EB(t)·η_EB,

wherein in the formula, Q¹_EB(t) represents the power of heat supply of an electrical boiler before the demand responses at the moment t; g¹_EB(t) represents the wind power quantity consumed by the work of the electrical boiler before the demand responses at the moment t; and η_EB represents the electricity to heat conversion efficiency;

the actual output of the electrical boiler before the demand responses meets the following constraint condition:

Q ^1min _EB ≤Q ¹ _EB(t)≤Q^1max_EB,

wherein in the formula, Q^1min_EB represents the lower limit of power of the electrical boiler before the demand responses; Q^1max_EB represents the upper limit of power of the electrical boiler before the demand responses; and Q¹_EB(t) represents the actual output of the electrical boiler before the demand responses at the moment t; and

the heat supply equipment before the demand responses only comprises the electrical boiler before the demand responses, so the numerical value of Q¹_EB(t) is equal to that of Q_heart¹(t), i.e., Q¹_EB(t)=Q_heart¹(t); and the power of heat supply of output of the electrical boiler before the demand responses at the moment t is obtained according to the demand Q_heart¹(t) of the heat loads before the demand responses, so as to obtain the wind power quantity g¹_EB(t) consumed by the heat supply equipment before the demand responses according to the electrical boiler output model before the demand responses.

In the step (2), the abandoned wind quantity per moment before the demand responses and the total abandoned wind quantity before the demand responses are respectively obtained by the following formulas:

$g_W^1\left(t\right)=g_{\mathrm{WPP}}\left(t\right)-g_E^1\left(t\right)-g_{\mathrm{EB}}^1\left(t\right)g_W^1=\sum _{t=1}^{24}{g}_W^1\left(t\right)$

wherein in the formulas, g_W¹ represents the total abandoned wind quantity before the demand responses; g_W¹(t) represents the abandoned wind quantity before the demand responses at the moment t; g_E¹(t) represents the known demand of the electrical loads before the demand responses at the moment t; and g_EB¹(t) represents the wind power quantity consumed initially by the heat supply equipment.

In the step (3), the heat load demand model after the demand responses is:

$Q_{\mathrm{heart}}^2\left(t\right)=\sum _{t=1}^{24}\left(C_{\mathrm{air}}{\rho }_{\mathrm{air}}\mathrm{NSH}+\partial \mathrm{KA}\right)\left(T_{\mathrm{PMV}}^2-T_{\mathrm{out}}\left(t\right)\right)-Q_{\mathrm{inc}}-Q_{\mathrm{inh}},$

wherein in the formula, Q_heart²(t) represents the demand of the heat loads after the demand responses; T_PMV² represents the set indoor temperature after the demand responses; ∂ represents the modified temperature difference factor of the envelope enclosure; K represents the heat transfer coefficient of the envelope enclosure; A represents the area of the envelope enclosure; T_out (t) represents the outdoor temperature at the moment t; C_air represents the specific heat capacity of air; ρ_air represents the air density; N represents the air change rate; S represents the area of a building; H represents the indoor height of the building; Q_ine represents the calorific value of the electrical equipment; and Q_inh represents the calorific value of the human body; and

the set indoor temperature T_PMV² after the demand responses is calculated by the following formula:

$T_{\mathrm{PMV}}^2=T_S-\frac{M\left(2.43-{\lambda }_{\mathrm{PMV}}^2\right)\left(I_{\mathrm{cl}}+0.1\right)}{3.76},$

wherein in the formula, T_S represents the human skin temperature in a normal temperature state; M represents the human energy metabolism rate; λ_PMV² represents the initial PMV index; I_c1 represents the dress heat resistance; and when in calculation, λ_PMV² is set as 0, and the set indoor temperature T_PMV² after the demand responses is obtained, so as to obtain the demand Q_heart²(t) of the heat loads after the demand responses according to the heat load demand model after the demand responses.

The electrical boiler output model after the demand responses is:

Q ² _EB(t)=g²_EB(t)·η_EB,

wherein in the formula, Q²_EB(t) represents the power of heat supply of the electrical boiler after the demand responses at the moment t; g²_EB(t) represents the wind power quantity consumed by the work of the electrical boiler after the demand responses at the moment t; and η_EB represents the electricity to heat conversion efficiency;

the actual output of the electrical boiler after the demand responses meets the following constraint condition:

Q ^2min _EB ≤Q ² _EB(t)≤Q^2max_EB

wherein in the formula, Q^2min_EB represents the lower limit of power of the electrical boiler after the demand responses; Q^2max_EB represents the upper limit of power of the electrical boiler after the demand responses; and Q²_EB(t) represents the actual output of the electrical boiler after the demand responses at the moment t; and

the heat supply equipment after the demand responses only comprises the electrical boiler after the demand responses, so the numerical value of Q²_EB(t) is equal to that of Q_heart²(t), i.e., Q²_EB (t)=Q_heart²(t); and the power of heat supply of output of the electrical boiler after the demand responses at the moment t is obtained according to the demand Q_heart²(t) of the heat loads after the demand responses, so as to obtain the wind power quantity g²_EB(t) (consumed by the heat supply equipment after the demand responses according to the electrical boiler output model after the demand responses.

In the step (4), the demand of the electrical loads after the demand responses is obtained specifically by adopting the following manners:

firstly, the variation of the electrical loads per moment after the demand responses is calculated by the following formulas:

$\Delta g_{\mathrm{on}}\left(t\right)=e_{\mathrm{on}}\times g_{\mathrm{on}}\left(t\right)\times \frac{\Delta P_{\mathrm{on}}\left(t\right)}{P_{\mathrm{on}}\left(t\right)},t\in T_{\mathrm{on}}\Delta g_{\min d}\left(t\right)=e_{\min d}\times g_{\min d}\left(t\right)\times \frac{\Delta P_{\min d}\left(t\right)}{P_{\min d}\left(t\right)},t\in T_{\mathrm{mind}}\Delta g_{\mathrm{off}}\left(t\right)=e_{\mathrm{off}}\times g_{\mathrm{off}}\left(t\right)\times \frac{\Delta P_{\mathrm{off}}\left(t\right)}{P_{\mathrm{off}}\left(t\right)},t\in T_{\mathrm{off}}$

wherein in the formulas, Δg_on(t), Δg_mind(t) and Δg_off(t) represent the variations of the electrical loads at the peak period of power consumption, the flat period of power consumption and the valley period of power consumption after the demand responses; g_on(t), g_mind(t) and g_off(t) represent the electrical loads at the peak period of power consumption, the flat period of power consumption and the valley period of power consumption before the demand responses; P_on(t), P_mind(t) and P_off(t) represent the energy consumption at the peak period of power consumption, the flat period of power consumption and the valley period of power consumption before the demand responses; ΔP_on(t), ΔP_mind(t) and ΔP_off(t) represent the variations of energy consumption at the peak period of power consumption, the flat period of power consumption and the valley period of power consumption after the demand responses; e_on, e_mind and e_off represent the elastic coefficients of energy consumption at the peak period of power consumption, the flat period of power consumption and the valley period of power consumption; and T_on represents the peak period of energy consumption, T_mind represents the flat period of energy consumption, and T_off represents the valley period of energy consumption; and

then, the demand g_E²(t) of the electrical loads per moment after the demand responses is obtained by the variations of the electrical loads per moment after the demand responses plus the known demand g_E¹(t) of the electrical loads per moment before the demand responses.

In the step (4), the abandoned wind quantity per moment after the demand responses and the total abandoned wind quantity after the demand responses are respectively obtained by the following formulas:

$g_W^2\left(t\right)=g_{\mathrm{WPP}}\left(t\right)-g_E^2\left(t\right)-g_{\mathrm{EB}}^2\left(t\right)g_W^2=\sum _{t=1}^{24}{g}_W^2\left(t\right)$

wherein in the formulas, g_W² represents the total abandoned wind quantity after the demand responses; g_W²(t) (represents the abandoned wind quantity after the demand responses at the moment t; g_E²(t) represents the demand of the electrical loads after the demand responses at the moment t; and g_EB²(t) represents the quantity of electricity consumed by heat supply of the electrical boiler after the demand responses at the moment t. The step (5) specifically is:

The storage battery capacity model is:

S _SOC(t)=S_soc(t−1)+S_ch(t)−S_dis(t))

S _ch(t)=g_ch(t)η_ch

S _dis(t)=g_dis(t)η_dis

wherein in the formulas, S_SOC (t) represents the capacitance of the storage battery at the moment t; S_soc (t−1) represents the capacitance of the storage battery at the moment (t−1); S_ch (t) represents the charging capacity of the storage battery at the moment t; S_dis (t) represents the discharging capacity of the storage battery at the moment t; g_ch (t) represents the charging power of the storage battery at the moment t; η_ch represents the charging efficiency of the storage battery; g_dis (t) represents the discharging power of the storage battery at the moment t; and η_dis represents the discharging efficiency of the storage battery;

the capacity of the storage battery meets the following constraint condition:

S _SOC ^min ≤S _SOC(t)≤S_SOC^max

wherein in the formula, S_SOC^min represents the minimum charging capacity of the storage battery, and the S_SOC^max represents the maximum charging capacity of the storage battery;

the output constraint of the storage battery meets the following constraint condition:

g _ch ^min ≤g _ch(t)≤g_ch^max

g _dis ^min ≤g _dis(T)≤g_dis^max

wherein in the formulas, g_ch^min represents the minimum charging power of the storage battery; g_ch^max represents the maximum charging power of the storage battery; g_dis^min represents the minimum discharging power of the storage battery; and g_dh^max represents the maximum discharging power of the storage battery;

when the value of the actual output g_WPP(t) of the wind turbine at the moment t is less than the sum of the value of the wind power quantity g²_EB(t) consumed by the heat supply equipment after the demand responses at the moment t and the value of the demand of the electrical loads after the demand responses at the moment t, the value of the obtained abandoned wind quantity g²_EB(t) g_W²(t) after the demand responses at the moment t is less than 0; and when the value of the actual output g_WPP(t) of the wind turbine at the moment t is more than or equal to the sum of the value of the wind power quantity E consumed by the heat supply equipment after the demand responses at the moment t and the value of the demand g_E²(t) of the electrical loads after the demand responses at the moment t, the value of the obtained abandoned wind quantity g_W²(t) after the demand responses at the moment t is more than or equal to 0; and

when the value of the abandoned wind quantity g_W²(t) after the demand responses at the moment t is less than 0, the storage battery is configured to discharge to assist the wind turbine to supply power; when the value of the abandoned wind quantity g_W²(t) after the demand responses at the moment t is more than or equal to 0, the storage battery is configured to be charged; the charging quantity S_ch (t) is equal to the abandoned wind quantity g_W²(t) after the demand responses at the moment t, i.e., g_W²(t)=S_ch(t); and the discharging quantity S_dis (t) is equal to the absolute value of the abandoned wind quantity g_W²(t) after the demand responses at the moment t, i.e., |g_W²(t)|=S_dis(t).

The working principle of the storage battery is: under the conditions that the wind power is sufficient, and abandoned wind is generated, the abandoned wind quantity is stored; when the wind power is insufficient to provide the required electrical loads, the storage battery is configured to discharge to assist the wind turbine to supply power.

The virtual power plant of the present invention comprises the electrical boiler, the storage battery and the wind turbine.

The present invention has the beneficial effects that:

According to the method, power utilization and heat utilization can be reasonably guided, the energy utilization rate is improved, and the operation cost of the virtual power plant is lowered; the method has the reference value for wind power consumption of the virtual power plant with the consideration that the comprehensive demand responses are implemented on various loads, and the scientific basis is provided for more efficiently improving the energy utilization rate; and an effective way is provided for lowering the operation cost of a power generation and distribution system, such as the virtual power plant, and the like.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of wind power consumption of a virtual power plant of the present invention;

FIG. 2 is a diagram of a demand curve of electrical loads and heat loads in an embodiment of the present invention;

FIG. 3 is a diagram of the condition of wind power consumption in a scenario 1 of the embodiment of the present invention;

FIG. 4 is a diagram of a demand change curve after demand responses of the electrical loads in the embodiment of the present invention;

FIG. 5 is a diagram of a demand change curve after demand responses of the heat loads in the embodiment of the present invention; and

FIG. 6 is a diagram of the condition of wind power consumption in a scenario 2 of the embodiment of the present invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present invention is further described in details hereinafter through combination with the drawings and specific embodiments.

In the implementation of the present invention, the present invention is implemented according to the specific steps in the contents of the description and the contents of the claims, and the specific step process is not described here.

The embodiments of the present invention are described as follows:

In the embodiments, a virtual power plant which comprises a wind turbine, a storage battery and an electrical boiler is taken as an example. The output condition of the wind turbine is shown in FIG. 2. The initial capacity of the storage battery is 0 kWh. A demand curve of electrical loads and heat loads is shown in FIG. 3. The uniform energy consumption cost before demand responses is 0.5/kWh; after peak-valley energy consumption is adopted, the peak period of energy consumption is 11:00-15:00 and 19:00-21:00; the cost at the peak period of energy consumption is 0.8/kWh; and the corresponding elastic coefficient e_on of energy consumption is −0.07. The flat period of energy consumption is 08:00-10:00, 16:00-18:00 and 22:00-23:00; the cost at the flat period of energy consumption is 0.4/kWh; and the corresponding elastic coefficient e_mind of energy consumption is 0.05. The valley period of energy consumption is 24:00-07:00; the cost at the valley period of energy consumption is 0.2/kWh; and the corresponding elastic coefficient e_off of energy consumption is 0.08. In the embodiments, two scenarios are considered. In the first scenario, energy storage equipment is not considered, and the demand responses are not implemented on the electrical loads and the heat loads. In the second scenario, the energy storage equipment is considered, and comprehensive demand responses are implemented on the electrical loads and the heat loads. In the embodiment, the abandoned wind quantities of the virtual power plant in the two scenarios are respectively calculated and are compared with each other.

The virtual power plant in the embodiment is mainly used for wind power consumption for the power utilization of users and the electricity to heat conversion of the electrical boiler. In the scenario 2, the demand of the electrical loads after the demand responses is obtained according to the elastic cost coefficients of the electrical loads at different periods. It can be seen from FIG. 4 that peak load shifting of the electrical loads is realized by the demand responses. At the demand peak period of the heat loads, incentive demand responses are implemented by lowering the set indoor temperature T_PMV, and the compensation cost for the demand responses of the virtual power plant is considered to be minimum. In the embodiment, the incentive demand responses of the heat loads are implemented at the common peak period (19:00-23:00) of the electrical loads and the heat loads. It can be seen from FIG. 5 that the curtailment of the heat loads is realized by the demand responses; meanwhile, when the abandoned wind quantity is larger, the storage battery is configured to store energy, so as to promote wind power consumption. Through comparison on the conditions of wind power consumption in the two scenarios, as shown in Tab. 1, it is found that the abandoned wind quantity in the scenario 2 is reduced, and the consumption capacity is higher.

TABLE 1
Table of conditions of wind power consumption
of a virtual power plant in two scenarios
	Scenario 1	Scenario 2
	Wind power generation/kW	4886	4886
	Electrical load/kW	2177	2184.3
	Output of electrical boiler/kW	2656.66	2653.89
	Output of storage battery/kW	0	12.76
	Abandoned wind quantity/kW	52.34	35.05

Therefore, the comprehensive responses of the electrical loads and the heat loads are considered in the present invention, the capacity of wind power consumption of the virtual power plant is effectively improved; the reference is provided for a research that the comprehensive demand responses are implemented on various loads; and an effective way is provided for promoting wind power consumption of a power generation and distribution system, such as the virtual power plant and the like and relieving the problem of wind abandonment.

Finally, it should be noted that the above example is only used for describing the technical solution of the present invention, rather than the limit to technical solution of the present invention. Although the present invention is described with reference to the above example, those skilled in the art should understand that a specific implementation manner of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement made without departing from the spirit and the scope of the present invention shall be covered in the scope of the claims of the present invention.

Claims

1. A wind power consumption method of a virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads, comprising the following steps: (1) establishing a wind turbine output model, so as to obtain a wind power prediction curve by the wind turbine output model;(2) establishing a heat load demand model before demand responses and a heat supply equipment output model before the demand responses, so as to obtain the demand of the heat loads before the demand responses according to the heat load demand model before the demand responses; taking the heat supply equipment output model before the demand responses as an electrical boiler output model before the demand responses in the virtual power plant and calculating the wind power quantity consumed by heat supply equipment before the demand responses according to the electrical boiler output model before the demand responses and the demand of the heat loads before the demand responses; and calculating the abandoned wind quantity per moment before the demand responses and the total abandoned wind quantity before the demand responses according to the wind power prediction curve, the demand of the electrical loads before the demand responses and the wind power quantity consumed by the heat supply equipment before the demand responses, wherein the virtual power plant comprises the electrical boiler, a storage battery and a wind turbine;(3) establishing a heat load demand model after the demand responses and a heat supply equipment output model after the demand responses, so as to obtain the demand of the heat loads after the demand responses according to the heat load demand model after the demand responses; and taking the heat supply equipment output model after the demand responses as an electrical boiler output model after the demand responses in the virtual power plant and calculating the wind power quantity consumed by the heat supply equipment after the demand responses according to the electrical boiler output model after the demand responses and the demand of the heat loads after the demand responses;(4) calculating the demand of the electrical loads after the demand responses; calculating the abandoned wind quantity per moment after the demand responses and the total abandoned wind quantity after the demand responses according to the wind power prediction curve, the demand of the electrical loads after the demand responses and the wind power quantity consumed by the heat supply equipment after the demand responses; then calculating a difference value between the total abandoned wind quantity before the demand responses and the total abandoned wind quantity after the demand responses; if the difference value is more than 0, judging that the wind power consumption is promoted; and if the difference value is less than 0, judging that the wind power consumption is not promoted; and(5) establishing a storage battery capacity model; and judging the charging/discharging state and the charging/discharging capacity of the storage battery according to the storage battery capacity model and the abandoned wind quantity per moment after the demand responses.

2. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein in the step (1), the wind turbine output model is:

3. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein in the step (2), the heat load demand model before the demand responses is:

4. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 3, wherein the heat supply equipment before the demand responses only comprises the electrical boiler before the demand responses, so the numerical value of Q1EB(t) is equal to that of Qheart1(t); and the output of the electrical boiler before the demand responses at the moment t is obtained according to the demand Qheart1(t) of the heat loads before the demand responses, so as to obtain the wind power quantity g1EB(t) consumed by the heat supply equipment before the demand responses according to the electrical boiler output model before the demand responses.

5. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein in the step (2), the abandoned wind quantity per moment before the demand responses and the total abandoned wind quantity before the demand responses are respectively obtained by the following formulas:

6. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein in the step (3), the heat load demand model after the demand responses is:

7. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 6, wherein the heat supply equipment after the demand responses only comprises the electrical boiler after the demand responses, so the numerical value of Q2EB(t) is equal to that of Qheart2(t); and the output of the electrical boiler after the demand responses at the moment t is obtained according to the demand Qheart2(t) of the heat loads after the demand responses, so as to obtain the wind power quantity g2EB(t) consumed by the heat supply equipment after the demand responses according to the electrical boiler output model after the demand responses.

8. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein in the step (4), the demand of the electrical loads after the demand responses is obtained specifically by adopting the following manners: firstly, the variation of the electrical loads per moment after the demand responses is calculated by the following formulas:

9. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein in the step (4), the abandoned wind quantity per moment after the demand responses and the total abandoned wind quantity after the demand responses are respectively obtained by the following formulas:

10. The wind power consumption method of the virtual power plant with consideration of comprehensive demand responses of electrical loads and heat loads according to claim 1, wherein the step (5) specifically is: the storage battery capacity model is: Ssoc(t)=Ssoc(t−1)+(Sch(t)−Sdis(t))Sch(t)=gch(t)ηch Sdis(t)=gdis(t)ηdis wherein in the formulas, SSOCmin (t) represents the capacitance of the storage battery at the moment t; Ssoc (t−1) represents the capacitance of the storage battery at the moment (t−1); Sch (t) represents the charging capacity of the storage battery at the moment t; Sdis (t) represents the discharging capacity of the storage battery at the moment t; gch (t) represents the charging power of the storage battery at the moment t; ηch represents the charging efficiency of the storage battery; gdis (t) represents the discharging power of the storage battery at the moment t; and ηdis represents the discharging efficiency of the storage battery;the capacity of the storage battery meets the following constraint condition: SSOCmin≤SSOC(t)≤SSOCmax wherein in the formula, SSOCmin represents the minimum charging capacity of the storage battery, and the SSOCmax represents the maximum charging capacity of the storage battery;the output constraint of the storage battery meets the following constraint condition: gchmin≤gch(t)≤gchmax,gdismin≤gdis(t)≤gdismax wherein in the formulas, gchmin represents the minimum charging power of the storage battery; gchmax represents the maximum charging power of the storage battery; gdismin represents the minimum discharging power of the storage battery; and gdismax represents the maximum discharging power of the storage battery;when the value of the actual output gWPP (t) of the wind turbine at the moment t is less than the sum of the value of the wind power quantity g2EB(t) consumed by the heat supply equipment after the demand responses at the moment t and the value of the demand gE2(t) of the electrical loads after the demand responses at the moment t, the value of the obtained abandoned wind quantity gW2(t) after the demand responses at the moment t is less than 0; and when the value of the actual output gWPP (t) of the wind turbine at the moment t is more than or equal to the sum of the value of the wind power quantity g2EB(t) consumed by the heat supply equipment after the demand responses at the moment t and the value of the demand gE2(t) of the electrical loads after the demand responses at the moment t, the value of the obtained abandoned wind quantity gW2(t) after the demand responses at the moment t is more than or equal to 0; andwhen the value of the abandoned wind quantity gW2(t) after the demand responses at the moment t is less than 0, the storage battery is configured to discharge to assist the wind turbine to supply power; when the value of the abandoned wind quantity gW2(t) after the demand responses at the moment t is more than or equal to 0, the storage battery is configured to be charged; the charging quantity Sch (t) is equal to the abandoned wind quantity gW2(t) after the demand responses at the moment t; and the discharging quantity Sdis (t) is equal to the absolute value of the abandoned wind quantity gW2(t) after the demand responses at the moment t.