CN112990541A - Power peak clipping decision method based on family comprehensive energy demand response - Google Patents

Abstract

A power peak clipping decision method based on family comprehensive energy demand response comprises the following steps: 1) simplifying the comprehensive energy system according to the household energy characteristics according to the actual condition of the comprehensive energy for the household users; 2) modeling energy demand response for family synthesis; 3) solving a family comprehensive demand response model; 4) and (3) application and decision of the family comprehensive demand response method. The invention provides a power peak clipping decision method based on household comprehensive energy demand response, which is a decision method for performing optimization by taking adjustment incentive of electricity price as a means based on energy consumption peak clipping regulation by starting from energy consumption characteristics of household users and considering economic expenditure of household energy and comfort of the household users according to daily load historical data of the comprehensive energy of the household users. The method aims at peak clipping of electric power at present, can be further popularized and applied to time-phased accurate peak-clipping and valley-filling, and can even reserve margin for new energy consumption in advance.

Description

Power peak clipping decision method based on family comprehensive energy demand response

Technical Field

The invention relates to the field of comprehensive energy systems and operation and research, in particular to a power peak clipping decision method based on household comprehensive energy demand response.

Background

With the advancement of the country in the aspect of the comprehensive energy system, the related research of the comprehensive energy application technology is becoming mature. The comprehensive energy system comprises multiple energy forms of electricity, heat, gas and the like at a supplier, a plurality of channel energy paths are arranged at a transmission part, and the coordination and utilization of the multiple energy forms are also arranged at a load end, so that the complementary advantages among the different energy forms are realized, for example, the electric energy has fast response but is difficult to store, the heat energy has thermal inertia and slow response, but the storage technology is mature. On the other hand, the cost is higher when the electric energy is converted into the heat energy in the same unit, and the cost is lower when the gas is converted into the heat energy.

In an integrated energy system, the energy supply includes various forms of energy, such as wind, light, coal, and natural gas, which are commonly used at present, and these primary energy sources need to be converted for utilization, as shown in fig. 1. Wind energy is converted into electric energy through a wind turbine, light energy is converted into electric energy through a photovoltaic system, coal is converted into electric energy through a thermal power generating unit, and natural gas is converted into heat energy and electric energy through a gas turbine. On the load side, the consumer is often loaded with electrical loads, thermal loads and gas loads. In the comprehensive energy system, the complementary characteristics among different energy forms are emphasized, and the energy storage device can be inserted in each link of the comprehensive energy system. In the primary energy, coal and natural gas are easy to store, after the energy utilization link, heat energy and natural gas are easy to store in large capacity, and various energy sources have different storage forms and characteristics on the user side.

In the comprehensive energy system, a user does not increase or reduce the use of electric energy singly any more in a period of time, but can cooperate with the response by converting the energy type, and the purpose of peak clipping of the electric load can be achieved, but the life convenience and the comfort of the user are not greatly influenced. There are some documents that have been studied in the related art. For example, consider the comprehensive demand response in a smart energy cell, and create a smart energy cell (Huzel, land Jun, Huangrui, etc. the demand response is considered and the demand response is considered for the smart energy cell thermoelectric coupling system energy utilization optimization method. And the optimization scheduling of the industrial park (Chenyu, Wangxin, Pan Shou, etc., the optimization scheduling of the industrial park considering the flexibility of users and the thermal inertia, research and development and application, the automation of a power system [ J ], 2020,44 (18): 1-10). Also, in consideration of user comfort, a mathematical modeling method for studying user response behavior through economic analysis (strong shima, wangsan, zhangyue, etc., modeling of regional electric heating load characteristics taking account of user response behavior differences, power system automation [ J ], 2019,43 (7): 67-73).

For southern household users, the problem of warm air supply in winter does not exist, and the main energy inlet of the household is mainly divided into a power grid and a natural gas pipeline, so that the energy demand model of the household can be simplified, and the peak clipping regulation and control are convenient to carry out.

In the prior art, there is also a peak clipping method, and chinese patent document CN 106950840a describes a hierarchical distributed coordination control method for a comprehensive energy system facing power grid peak clipping, which divides the energy system into an upper control system and a lower control system, and includes the following steps: 1) the lower control system performs self-tendency optimization control on the user; 2) the upper control system collects power information of the gateway and judges whether the integral peak value of the energy system meets the actual requirement or not; 3) directly adjusting the energy storage output and the generator output in the upper park; 4) the upper control system judges whether the power of the gateway is out of limit again; 5) the upper control system issues instructions to the lower adjustable users, and the interactive users reasonably adjust the loads of the interactive users; 6) the upper control system continuously judges whether the power of the gateway is out of limit; 7) and the upper layer garden control system issues an instruction to the lower layer interruptible user, and the interactive user reasonably interrupts the load of the interactive user. The problem that multiple energy sources are mutually coupled and difficult to coordinate and complement can be solved, peak clipping and valley filling are achieved, and friendly interaction with a power grid is achieved.

However, most of the current research on the comprehensive energy system focuses on the overall economic cost optimization and the consumption of new energy, and some research users have demand response, but the research aims to achieve economic cost and new energy consumption, and the energy consumption characteristics of the household users are rarely considered.

Disclosure of Invention

The invention aims to solve the technical problem of providing a power peak clipping decision method based on household comprehensive energy demand response, which is a decision method optimized by taking the economic expenditure of household energy and the comfort level of household users as the consideration from the energy consumption characteristics of the household users and aiming at electric energy peak clipping regulation, and further can be popularized and applied to time-sharing accurate peak and valley regulation and even can leave a margin for new energy consumption in advance.

In order to solve the technical problems, the technical scheme adopted by the invention is as follows:

a power peak clipping decision method based on family comprehensive energy demand response comprises the following steps:

step one, simplifying a multi-energy system according to the household energy using characteristics according to the actual condition of the comprehensive energy using of the household user;

step two, modeling for energy demand response for family synthesis;

thirdly, solving a family comprehensive demand response model;

and step four, application and decision of the family comprehensive demand response method.

In the first step, according to the characteristics of the household energy, the multiple energy forms of the comprehensive energy system of the household user are simplified into the terminal energy use form and the energy path entrance of the household user, the energy path entrance is divided into a power grid and a natural gas pipeline, and the household energy load is regulated into an electric load and a heat load.

In the second step, the model adjusting condition is set to be that the total cost of the family for energy expenditure cannot be increased before and after the family user executes the response scheme, and the total use cost is F-F₁+F₂In which F is₁For the cost of electric energy, F₂For gas costs, prior to response scenarios, the home energy cost is expressed as:

wherein F_qCost of energy for home use before implementing a demand response, F_q1For implementing the pre-demand response electric energy costs, F_q2For the natural cost before the implementation of demand response, W is the electricity consumption, the unit degree, J is the electricity price,unit/degree, V is the volume of natural gas, unit meter³K is natural gas price, unit/meter³P is power consumption, unit kW, Q is gas consumption per hour, t is time, 24 hours a day;

after the response scenario is made, the household energy cost is expressed as:

according to the setting conditions of model adjustment, the following conditions are provided:

F_q≥F_h

the heat energy consumption in the comfort model is used for replacing the environmental temperature and humidity, namely the total heat energy consumption is unchanged.

P_{t_q_r}Part of the electric energy, mu, being converted into heat energy before demand response₁For conversion of electric energy into heat energy efficiency, mu₂For gas to heat efficiency, P_{t_h_r}The electric energy part is converted into heat energy after the demand response;

setting the decision target to be peak clipping X%, the difference between the power load after response and the power load before response (1-X%) is the smallest, that is

Wherein beta is a peak clipping target and is calculated by percentage.

In the third step, based on the objective function and the constraint conditions established in the second step, the simplification is carried out by combining the actual situation, and the linear programming optimization solution is carried out to reduce the peak power price j_tFor decision variables, add boundary conditions:

Q_{t_h}≥0

j_t≥J

0≤P_{t_h_r}≤P_{t_q_r}

0≤P_{t_q_r}≤P_{t_q}。

in the fourth step, based on the analysis results solved in the second step and the third step, the price adjustment range can be obtained:

so as to obtain the sensitivity of price amplitude and peak clipping amplitude, in the application, the value of plan peak clipping is multiplied by the sensitivity, and the price adjustment amplitude is obtained:

and substituting the accumulated data of the daily load historical data of the family comprehensive energy into the model solving process, repeating the first step, the second step, the third step and the fourth step to obtain a variable load-price sensitivity value, and continuously correcting the result.

In the third step, the decision target is 10% peak clipping.

According to the power peak clipping decision method based on the family comprehensive energy demand response, the family comprehensive energy demand response analysis is carried out according to the comprehensive energy daily load historical data of the family user, and when an energy department needs to carry out peak regulation balance or reserve a load margin to carry out new energy consumption, the purpose of load adjustment can be accurately achieved through the change of electricity price.

Drawings

The invention is further illustrated by the following examples in conjunction with the accompanying drawings:

FIG. 1 is a block diagram of an integrated energy system to which the present invention is directed;

FIG. 2 is a simplified diagram of a comprehensive energy source for a household to which the present invention is applicable;

fig. 3 is a characteristic diagram of the comprehensive energy use situation of the family in the embodiment.

Detailed Description

The technical scheme of the invention is explained in detail in the following by combining the drawings and the embodiment.

As shown in fig. 1-2, a power peak clipping decision method based on home integrated energy demand response includes the following steps:

step one, simplifying a multi-energy system according to the household energy using characteristics according to the actual condition of the comprehensive energy using of the household user;

step two, modeling for energy demand response for family synthesis;

thirdly, solving a family comprehensive demand response model;

and step four, application and decision of the family comprehensive demand response method.

In the first step, according to the characteristics of household energy, multiple energy forms of the comprehensive energy system are simplified into a terminal energy use form and an energy path inlet of a household user, and in general household users in the south, because the central heating of families in the south is less, the method does not consider that heat energy is directly input into the household, the energy path inlets are two groups, a power grid and a natural gas pipeline are arranged, and the household energy load is also regulated into an electric load and a heat load, as shown in fig. 2.

In the second step, the total cost of the family for energy expenditure cannot be increased or even reduced in consideration of the comprehensive energy response of the family user, otherwise, the family user cannot respond to the scheme of the relevant energy department;

the total use cost is F ═ F₁+F₂In which F is₁For the cost of electric energy, F₂The cost of natural gas;

before the energy department makes a response scenario, the domestic energy cost is expressed as:

wherein F_qCost of energy for home use before implementing a demand response, F_q1For implementing the pre-demand response electric energy costs, F_q2For the natural cost before the demand response is implemented, W is the electricity consumption, unit degree, J is the electricity price, unit/degree, and V is the natural gas volumeUnit meter³K is natural gas price, unit/meter³P is power consumption, unit kW, Q is gas consumption per hour, t is time, 24 hours a day;

after the energy department proposes the response scheme, the household energy cost is expressed as:

the premise that the home user can demand response is that the energy consumption cost cannot be exceeded, otherwise, no response is made:

F_q≥F_h

family comfort level is the subjective impression of family life, receives external environment and self subjective consciousness's influence, and International Standard Organization (ISO) has proposed the thermal comfort model of ISO 7730, but the comfort level is not merely temperature and humidity, has proposed a simplified comfort level model here, comes the fuzzy alternative environment humiture with the consumption of heat energy, and the total amount of the instant heating power consumption is unchangeable:

P_{t_q_r}part of the electric energy, mu, being converted into heat energy before demand response₁For conversion of electric energy into heat energy efficiency, mu₂For gas to heat efficiency, P_{t_h_r}The electric energy part is converted into heat energy after the demand response;

the family demand response with the decision target of peak shaving is optimal as much as possible, if the decision target is 10% of peak shaving, the difference between the electric load after response and the electric load before response is minimum, namely the difference is 90% of the electric load before response

Beta is the peak clipping target and is calculated as a percentage.

In the third step, the method is based on the method established in the second stepSimplifying an objective function and a constraint condition by combining with an actual situation, and then solving by linear programming optimization, wherein a decision variable is a peak clipping power price j_tIn the process of solving the mathematical model, the iterated local optimal solution does not conform to actual logic, and the situations that the electricity price is negative or the gas consumption of natural gas is negative occur.

Q_{t_h}≥0

j_t≥J

0≤P_{t_h_r}≤P_{t_q_r}

0≤P_{t_q_r}≤P_{t_q}

In the fourth step, based on the analysis results obtained in the second and third steps, the price adjustment range can be obtained, that is, the price adjustment range is obtained

Therefore, the sensitivity of the price amplitude and the peak-shaving amplitude is obtained, and in application, the value of the planned peak shaving is multiplied by the sensitivity, so that the price adjusting amplitude can be obtained.

And repeating the first step, the second step, the third step and the fourth step along with the updating of the daily load historical data of the household comprehensive energy to obtain a variable load-price sensitivity value, and continuously correcting the result to ensure that the sensitivity is closer to reality, so that the adjustment is more accurate and is closer to a peak regulation target during later peak regulation. When the energy department needs to carry out peak regulation balance or reserve a load margin to carry out new energy consumption, the purpose of load adjustment can be accurately achieved through the change of electricity price.

In the third step, the decision target is 10% peak clipping, and when the decision target is 10%, the energy adjustment of the home user can be well performed while the peak clipping is performed.

The following are illustrated by specific examples:

according to the comprehensive energy use situation of the ordinary family, an arithmetic environment is established according to the diagram shown in FIG. 3, the electricity price of the residents of the ordinary family is set to be 0.6 yuan/degree, and the gas price is set to be 3 yuan/cubic meter.

p_tq＝[3 2 3 2 3 1 2 3 5 6 8 7 8 9 8 5 6 5 7 10 11 10 8 3]；

q_tq＝[0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.15 0.1 0.1 0.1 0.15 0.15 0.1 0.1 0.1 0.1 0.15 0.15 0.2 0.15 0.1 0.1 0.1]；

p_tqr＝[0.1 0.1 0.1 0.1 0.1 0.15 0.15 0.1 0.1 0.1 0.15 0.15 0.1 0.1 0.1 0.1 0.15 0.15 0.2 0.2 0.15 0.15 0.1 0.1]；

According to the objective function and the constraint condition, solving:

j＝[0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6329 0.6329 0.6329 0.6 0.6]；

p_th＝[3 2 3 2 3 1 2 3 5 6 8 7 8 9 8 5 6 5 7 9.3000 9.3000 9.3000 8 3]

ε＝0.548

this is a price sensitivity with a peak clipping target of 10% in the evening prime period, and according to such a method, sensitivities with peak clipping targets of other values can be established, and also sensitivity response values for other peak periods can be established, as shown in table 1 below.

Table 1 peak clipping target correspondence table.

Claims (6)

1. A power peak clipping decision method based on family comprehensive energy demand response is characterized by comprising the following steps:

step one, simplifying a multi-energy system according to the household energy using characteristics according to the actual condition of the comprehensive energy using of the household user;

step two, modeling for energy demand response for family synthesis;

thirdly, solving a family comprehensive demand response model;

and step four, application and decision of the family comprehensive demand response method.

2. The electric power peak clipping decision method based on the family comprehensive energy demand response as claimed in claim 1, characterized in that in the first step, according to the family energy characteristics, the multiple energy forms of the comprehensive energy system of the family user are classified into the terminal energy use form and the energy path entrance of the family user, the energy path entrance is divided into a power grid and a natural gas pipeline, and the family energy load is classified into an electric load and a heat load.

3. The method as claimed in claim 2, wherein in the second step, the model adjusting condition is set to be that the total cost of the household for energy expenditure cannot be increased before and after the household user executes the response scheme, and the total use cost is F-F₁+F₂In which F is₁For the cost of electric energy, F₂For gas costs, prior to response scenarios, the home energy cost is expressed as:

wherein F_qCost of energy for home use before implementing a demand response, F_q1For implementing the pre-demand response electric energy costs, F_q2In order to implement natural cost of the weather before demand response, W is power consumption, unit degree, J is electricity price, unit/degree, V is natural gas volume, unit meter³K is natural gas price, unit/meter³P is power consumption, unit kW, Q is gas consumption per hour, t is time, 24 hours a day;

after the response scenario is made, the household energy cost is expressed as:

according to the setting conditions of model adjustment, the following conditions are provided:

F_q≥F_h

the heat energy consumption in the comfort model is used for replacing the environmental temperature and humidity, namely the total heat energy consumption is unchanged.

P_{t_q_r}Part of the electric energy, mu, being converted into heat energy before demand response₁For conversion of electric energy into heat energy efficiency, mu₂For gas to heat efficiency, P_{t_h_r}The electric energy part is converted into heat energy after the demand response;

setting the decision target to be peak clipping X%, the difference between the power load after response and the power load before response (1-X%) is the smallest, that is

Wherein beta is a peak clipping target and is calculated by percentage.

4. The power peak clipping decision method based on family comprehensive energy demand response according to claim 3, characterized in that in the third step, based on the objective function and constraint conditions established in the second step, the simplification is performed in combination with the actual situation, and the linear programming optimization solution is performed to clip the peak power price j_tFor decision variables, add boundary conditions:

Q_{t_h}≥0

j_t≥J

0≤P_{t_h_r}≤P_{t_q_r}

0≤P_{t_q_r}≤P_{t_q}。

5. the electric power peak clipping decision method based on family comprehensive energy demand response of claim 4, characterized in that in the fourth step, based on the analysis results solved in the second step and the third step, the price adjustment range can be obtained:

so as to obtain the sensitivity of price amplitude and peak clipping amplitude, in the application, the value of plan peak clipping is multiplied by the sensitivity, and the price adjustment amplitude is obtained:

and substituting the accumulated data of the daily load historical data of the family comprehensive energy into the model solving process, repeating the first step, the second step, the third step and the fourth step to obtain a variable load-price sensitivity value, and continuously correcting the result.

6. The electric power peak clipping decision method based on family comprehensive energy demand response as claimed in claim 3, characterized in that in the third step, the decision goal is peak clipping by 10%.

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