CN107069773B - Load smooth control method based on demand side resource unified state model - Google Patents
Load smooth control method based on demand side resource unified state model Download PDFInfo
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Abstract
The invention discloses a load smooth control method based on a demand side resource uniform state model. The proposed unified state model can describe the response characteristics of different types of demand side resources by using a unified mathematical expression; deducing a control matrix to realize real-time management and control on the output power of the resource at the demand side on the basis of considering the response sequence of the resource at the demand side; on the basis of considering the user energy comfort level, the proposed control strategy can realize the full absorption and absorption of renewable energy sources, ensure that the SOC of the electric automobile before going out meets the user requirements, and ensure that the indoor temperature of the temperature control load meets the user comfort level requirements; the control of the invention can obviously reduce the power fluctuation of the load, and the power fluctuation rate of the load is kept below a preset value of 10 percent.
Description
Technical Field
The invention relates to a power transmission network planning method, in particular to a load smooth control method based on a demand side resource unified state model.
Background
In recent years, renewable energy sources such as wind energy and solar energy have attracted more and more attention worldwide by virtue of their renewable green color and environmental protection [1 ]. However, renewable energy Distributed Generation (DG) is characterized by random intermittency, thus introducing a great deal of uncertainty in the operation of the distribution grid. Causing the fluctuation of the load power of the power distribution network, and being worthy of attention, the serious change [2] of the load power of the power distribution network can obviously affect the stable operation of the power distribution network to generate profound influence [2] so as to limit the utilization, absorption and absorption of renewable energy sources [3 ].
The traditional generator is a common means for stabilizing the fluctuation of the load power of the power distribution network, and one of the traditional control strategies for smoothing the load curve of the power distribution network is to plan the traditional generator. However, the response speed of such a conventional generator is not enough to follow the output power variation of the DG distributed grid, and causes problems in that the generator is poor in operation economy and the generation efficiency is lowered [4 ]. Another approach to address this problem is to respond to load power fluctuations in the distribution grid by using an Energy Storage System (ESS), such as batteries, flywheel, etc. [5] [6] [5,6 ]. (ii) a With the energy storage system, the energy storage system ESS can be used to improve the reduction of the influence [7] [8] on the distribution of the distribution network voltage caused by the stochastic output of the distributed power sources in the distribution network. Reduction documents 7 and 8 the ESS was studied in order to reduce peak load [9] [10] peak loads in the distribution grid. (ii) a By dynamically adjusting the charging power output, the ESS energy storage system can effectively cope with and stabilize the power fluctuation [11], [12] of the power distribution network with the DG caused by the distributed power supply; . However, the adoption of large-scale ESS application energy storage systems would be uneconomical and impractical to significantly reduce the economics of renewable energy access.
With the rapid development of smart grids, there is also a growing interest in the flexibility of demand response becoming an important means of assisting the operation of power distribution networks. . The ability of different types of demand side resources to have a large total response potential is considerable [13, ] [14 ]. Taking the distributed power supply [15], the electric vehicle [16] and the temperature control load [17] as examples, under an effective control means, the resources can be proved to be effective demand side resources such as the distributed power supply [15], the Electric Vehicle (EV) [16] and the constant Temperature Control Load (TCL) [17] which demand response effective resources, and can serve as an ESS in a power distribution network, thereby assisting the safe and stable operation of the power grid. Thus, some demand side resources can provide various types of assistance to the power distribution grid. Considering the response capability of the electric automobile and the thermostatic control temperature control load, the resources can only slow down the influence of the power fluctuation of the renewable energy source on the voltage of the power distribution network; by controlling the charging and discharging process of the electric automobile, the electric automobile can effectively reduce the voltage fluctuation of the power distribution network with the distributed power supply and simultaneously coordinate the charging load of the electric automobile in real time on the basis of minimizing the power loss of the power distribution network [18 ] [19 ]. Electric vehicles rely on their rapid responsiveness to smooth load curves and load distribution that can be remodeled as an energy storage device and reduce load peaks to alleviate peak loads [20, ] [21 ]. (ii) a Temperature-controlled load thermostatically controlled loads, such as heat pumps, represented by heat pumps, can mitigate power fluctuations in a power distribution network with distributed power sources [22, ] [23] that stabilize power fluctuations caused by renewable energy sources in the power distribution network.
[ reference documents ]
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Disclosure of Invention
The existing current research results mainly aim at the participation of a specific type of demand side resource in system response, and documents make good contribution to the improvement of the power quality of a power distribution network of a single type of demand side resource. However, each type of demand-side resource has its own response characteristics and capability points. Therefore, it is of great importance to establish a unified mathematical model to describe the characteristics of different types of demand side resources and improve the response capability of the demand side resources, and the model can effectively mine the response capability of the demand side resource cluster. Meanwhile, the model can consider the response sequence of the demand side resource, in this way, all available power output control which is beneficial to realizing the demand side resource can be accurately controlled, and the response sequence is also considered when the unified model is established.
In order to solve the technical problem, the invention provides a load smooth control method based on a uniform state model of demand side resources, which comprises the following steps:
step one, establishing a uniform state model of demand side resources:
dividing the time of one day into M time intervals by taking a distributed power supply, an electric automobile and a temperature control load as demand side resources, wherein each interval time is delta t, namely M multiplied by delta t is 24 h;
the superscript i is used to refer to the resource type, and the distributed power supply, the electric vehicle and the temperature control load are represented by G, V and L (i belongs to { G, V, L }), respectively; the subscript j is used for indicating the number of a specific demand side resource in the distributed power supply G, the electric automobile V and the temperature control load L;
1-1) establishing a distributed power state model as follows:
in the formula (1), the reaction mixture is,the maximum output power provided by the distributed power supply j in a real-time state at the moment t;
the state model of the distributed power supply is as follows:
in the formula (2), the reaction mixture is,the accumulated quantity of the output electric energy of the distributed power supply j in a real-time state;the output power of the distributed power supply j in a real-time state is within the upper limit and the lower limit respectivelyAndis distributedThe accumulated amount of electric energy generated by the power supply j at rated output power is calculated according to the formula (3):
1-2) establishing an electric automobile state model, comprising the following steps:
in the formula (4), the reaction mixture is,in order to start the charging time,in order to start the time of the trip,andrated charge and discharge powers, respectively;in order to be the maximum output power,is a positive value;in order to achieve the minimum output power,is a negative value;
in the formula (5), the reaction mixture is,the real-time SOC value of the electric vehicle j is obtained;the electric vehicle j is charged at the rated power up to the upper limit of the SOC,discharging the electric vehicle j at rated power until reaching the lower limit of the SOC; when the electric automobile is charged, the SOC value rises to the SOC value required by the userIf so, stopping charging;
when the electric automobile is connected with the power distribution network, the j state model of the electric automobile is as follows:
in the formula (6), the reaction mixture is,for real-time power output of electric vehicle jFor the corrected j battery capacity of the electric vehicle,comprises the following steps:
in the formula (7), the reaction mixture is,the actual battery capacity of the electric automobile;andrespectively the charging efficiency and the discharging efficiency of the electric vehicle,is the output power;
1-3) establishing a temperature control load state model
in the formula (8), the reaction mixture is,rated power consumption;in order to obtain a lower limit of the output power,is a negative value;in order to achieve the upper limit of the output power,the value is 0;
normalized indoor temperature of temperature controlled load jAnd outdoor temperatureIs represented as follows:
the state model of the temperature-controlled load is as follows:
in the formulae (9) and (10),is the temperature of the room in question,andrespectively the upper and lower limits of the temperature control threshold,is the temperature of the outside of the room,andupper and lower limits of the indoor temperature, respectively; in thatDuring the time period, the temperature control load is in an on state and the indoor temperature risesIn the time period, the heat source equipment is in a turn-off state, and the indoor temperature is reduced; for temperature-controlled loads in the on state, the temperature isRange-off, temperature in the case of temperature-controlled loads in the off stateOpening when the range is reached;
is normalized outdoor temperature, ajIs equal toWherein R isjAnd CjRespectively a thermal resistor and a capacitor;to output power, when the temperature controlled load is in an on state,the temperature controlled load in the off state,
1-4) establishing a unified state model, including
The numbers of the distributed power supply, the electric automobile and the temperature control load are respectively NG、NV、NLAnd satisfy NG+NV+NL=N;
According to the distributed power supply state model, the electric vehicle state model and the temperature control load state model respectively expressed by the above equations (2), (6) and (10), the demand side resource state model is expressed by equation (11):
wherein:
on the basis of equation (11), the demand-side resource unified state model is shown as equation (18):
x(t+Δt)=x(t)+P(t)δ(t) (18)
in equation (18), the column vector x (t) is the real-time status of the demand-side resource, and the element satisfiesThe diagonal matrix p (t) is the real-time output power matrix of the demand-side resource,diagonal element satisfiesThe column vector δ (t) is defined as the modified time interval;
step two, smooth control of a load curve:
and evaluating the load fluctuation condition of the power distribution network by using the power fluctuation rate, wherein the load fluctuation condition is expressed by formulas (19) and (20):
in the formulae (19) and (20), the function fTUsed for calculating the power fluctuation rate of the load in the time period T; function(s)Andused for calculating the maximum value and the minimum value of the load in the time period T;is the rated value of the load;andload maximum and minimum;a real-time load value;
the method for realizing the smooth control of the load curve comprises the following steps:
the first step is as follows: determining a target power for load smoothing
By rtRepresenting the real-time power fluctuation rate, e.g.Formula (21):
in equations (22), (23) and (24), the upper limit of the load real-time power fluctuation rateAnd lower limitAs shown in equation (25):
in the formula (25), the reaction mixture,is the power fluctuation ratio rTThe limit of (2);the target variation power for load smoothing is shown as equation (26);
the second step is that: determining responsiveness of different demand side resources
To implement a load curve smoothing strategy based on a unified state model, the matrix P (t) is decomposed into the product of two matricesI.e. real time output powerByInstead of, i.e. using
In the formula (27), the reaction mixture is,are diagonal matrix, diagonal elementsThe upper limit of the output power of the demand side resource j; the diagonal matrix B is an output power control matrix, and diagonal elementsA control variable used to increase or decrease the output power of the demand-side resource j;
the formula (18) is rewritten as follows:
the ability to increase output power is:
the ability to reduce output power is:
in the formulas (29) and (30), matrixIs the maximum value of the controllable variable, the matrixBIs the minimum value of the controllable variable; l is0Is an N × 1 dimensional matrix with elements all 1; pup(t) is a matrix of dimension N × 1, the non-negative elements of the mth row indicating the ability of the mth resource to increase output power; pdn(t) is an N × 1 dimensional matrix, and the non-positive value element in the mth row represents the capability of the mth resource to reduce the output power;
define lower triangular matrixAnd lower triangular arrayB *Respectively evaluating the capacity of increasing output power and the capacity of reducing output power of the resource at the demand side, and setting a lower triangular arrayAnd lower triangular arrayB *The element in (1) is shown as formula (31):
the following are written over equations (29) and (30):
in the formula (32), Pup*(t) is an Nx 1 dimensional matrix, and the non-negative value element of the mth row represents the capability of increasing the output power of 1-m resources; pdu*(t) is also an N × 1 dimensional matrix, the non-positive value elements of the m-th row represent the ability of 1-m resources to reduce output power;
the third step: determining an actual control matrix B*
B*=B (34)
the output power of the demand-side resource is represented by equation (36):
the updated state model of the demand-side resource is represented by equation (37):
compared with the prior art, the invention has the beneficial effects that:
(1) by utilizing a load curve smooth control strategy, the power fluctuation of the load is obviously reduced, and the power fluctuation rate is kept below a preset value of 10 percent;
(2) the proposed unified state model can describe the response characteristics of different types of demand side resources by using a unified mathematical expression;
(3) deducing a control matrix to realize real-time management and control on the output power of the resource at the demand side on the basis of considering the response sequence of the resource at the demand side;
(4) on the basis of considering the user energy comfort level, the provided control strategy can realize the sufficient absorption of renewable energy, ensure that the SOC before the electric automobile goes out meets the user requirement, and ensure that the indoor temperature at which the temperature control load is positioned meets the comfort level requirement of the user.
Drawings
FIG. 1 is a single distributed power operating area;
FIG. 2 is a single electric vehicle operating area;
FIG. 3 is a single temperature controlled load operating zone;
FIG. 4 is a response sequence for an increase in output power;
FIG. 5 is a response sequence for a decrease in output power;
FIG. 6 is a load power without consideration of a load curve smoothing control strategy;
FIG. 7 is a load power for a smooth control strategy taking into account the load curve;
FIG. 8 is a graph of power fluctuation rate of a load under no control and control;
FIG. 9 is the output power of a distributed power supply under no control and control;
FIG. 10 is an output power of an electric vehicle under temperature control and control;
FIG. 11 is the output power of a temperature controlled load without control and under control;
FIG. 12(a) and FIG. 12(b) are SOC of the electric vehicle without control and under control, respectively;
fig. 13(a) and 13(b) are the indoor temperatures at which the temperature-controlled load is placed under no control and under control, respectively.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments.
The invention provides a load smooth control method based on a uniform state model of demand side resources, which comprises the following steps:
step one, establishing a uniform state model of the demand side resource. The present invention is directed mainly to demand-side resources represented by distributed power supplies, electric vehicles, and temperature-controlled loads. The time of day is divided into M time intervals, each interval having a time Δ t, i.e., M × Δ t is 24. In the invention, a superscript i is used for indicating a resource type, and a distributed power supply, an electric automobile and a temperature control load are respectively represented by G, V and L (i belongs to { G, V, L }); the subscript j is used to indicate the number of a particular demand side resource in G, V, L. The method comprises the following steps:
1-3) establishing a distributed power state model as follows:
the single distributed power source operation area is shown in fig. 1.
The upper and lower limits of the output power of the distributed power supply j are shown in the formula (1).
In the formula (I), the compound is shown in the specification,is the maximum output power provided by the distributed power source j at time t.
The state model of the distributed power supply is shown as equation (2).
In the formula (I), the compound is shown in the specification,outputting the accumulated amount of the electric energy for the distributed power supply j;is the output power of the distributed power supply j, and the upper and lower limit ranges are respectivelyAndis the accumulated amount of electric energy generated by the distributed power source j at the rated output power, and can be calculated according to equation (3).
To establish a state model of a distributed power supply, a control center needs to acquire a real-time statePower outputMaximum power outputAnd rated output powerThe information of (1).
1-4) establishing an electric automobile state model, which comprises the following steps:
when the electric automobile goes out, the electric automobile has no influence on a power distribution network; when the power distribution network is accessed, the electric automobile can realize bidirectional power flow control with the power distribution network, and the working area of a single electric automobile is shown in fig. 2.
Upper and lower limits of j power output of electric automobileAndas shown in equation (4), wherein the initial charging time isThe time of starting trip is
In the formula (I), the compound is shown in the specification,andrated charge-discharge power;is the maximum output power, is a positive value;is the minimum output power and is negative.
For the electric automobile access distribution network, the electric automobile operation area (shaded part in fig. 2) is limited by the output power and the SOC state. Point A, B, C, D, E is used to determine the boundary of the operating region, whose upper boundary is defined by A-B-C, and electric vehicle j is charged at rated power from A to B until SOC reaches its upper limitUnder itThe boundary is determined by A-D-E-F, and the electric vehicle j is discharged at rated power from A to D until the SOC reaches the lower limitIn order to ensure that the electric automobile can meet the SOC requirement of a user before going outThe electric vehicle j is forcibly charged at the rated power from E to F.
Is the normalized SOC value of the electric vehicle EVj, as shown in equation (5). When the electric automobile is connected with the power distribution network, the state model of the electric automobile is shown in the formula (6).
In the formula (I), the compound is shown in the specification,the real-time SOC value of the electric vehicle j is obtained.
In the formula (I), the compound is shown in the specification,for real-time power output of electric vehicle jThe corrected battery capacity of the electric vehicle is shown as the formula (7).
In the formula (I), the compound is shown in the specification,the actual capacity of the battery of the electric automobile;andrespectively charge and discharge efficiency.
To build a state model of an electric vehicle, the Aggregator needs to obtain real-time statesOutput powerRated charge and discharge powerAndbattery capacity of electric vehicleCharge and discharge efficiencyAndtravel timeSOC value of user's demandUpper and lower bounds of SOCAndthe information of (1).
1-3) establishing a temperature control load state model
The temperature-controlled load has good heat storage characteristics, and taking the heat pump to increase the indoor temperature as an example, the operation area of the single temperature-controlled load is shown in fig. 3.
Upper and lower limits of output power of temperature controlled load j ((And) As shown in formula (8).
In the formula (I), the compound is shown in the specification,rated power consumption;is the lower limit of the output power and is a negative value;the upper limit of the output power is 0.
As shown in figure 3 of the drawings,andrespectively, the upper and lower limits of the indoor temperature. In thatDuring the time period, the heat pump is in the 'on' state and the indoor temperature increases. In thatDuring the time period, the heat pump is in the 'off' stateAnd the indoor temperature is lowered. To reduce the number of switching operations, the temperature is in the 'on' state for temperature controlled loadsThe range may be turned off. For a heat pump in the 'off' state, the temperature isThe range may be on.
To normalize indoor and outdoor temperaturesAnd) Indoor and outdoor temperature after normalization of temperature control load jAndas shown in formula (9). The state model of the temperature-controlled load is shown in equation (10).
In the formula (I), the compound is shown in the specification,is the normalized outdoor temperature; a isjIs equal toWherein R isjAnd CjRespectively a thermal resistor and a capacitor;for output power, when in the 'on' state isIn the 'off' state is
To establish a state model of the temperature controlled load, the control center needs to obtain real-time stateOutput powerRated power consumptionThermal resistor and capacitor RjAnd CjUpper and lower limits of indoor temperatureAndupper and lower temperature control threshold limitsAndand outdoor temperatureAnd so on.
1-4) establishing a unified state model, including
The numbers of the distributed power supply, the electric automobile and the temperature control load are respectively NG、NV、NLAnd satisfy NG+NV+NLN. According to the state model equations (3), (6) and (10) of the three resources, after different unificationsThe demand-side resource status model of (2) is shown in equation (11), wherein the parameter meanings are shown in equations (12) - (17).
Based on the state model given by equation (11), the demand-side resource uniform state model is shown as (18).
x(t+Δt)=x(t)+P(t)δ(t) (18)
Wherein, the column vector x (t) is the real-time status of the demand-side resource, and the element satisfiesThe diagonal matrix P (t) is a real-time output power matrix of the resource at the demand side, and the diagonal elements meetThe column vector δ (t) is defined as the modified time interval.
And step two, applying a load curve smoothing control strategy.
And evaluating the load fluctuation condition of the power distribution network by using the power fluctuation rate, as shown in formulas (19) and (20).
In the formula, function fTUsed for calculating the power fluctuation rate of the load in the time period T; function(s)Andused for calculating the maximum value and the minimum value of the load in the time period T;is the rated value of the load;andload maximum and minimum;is a real-time load value.
On the basis of the unified state model, the load curve smoothing control strategy proposed by the present invention is described next.
The first step is as follows: determining a target power for load smoothing
By rtRepresents the real-time power fluctuation rate, as shown in (21).
in the formula, the upper and lower limits of the real-time power fluctuation rate of the loadAndas shown in equation (25).
In the formula (I), the compound is shown in the specification,is the power fluctuation ratio rTThe limit of (2).
The second step is that: determining responsiveness of different demand side resources
To implement a load curve smoothing strategy based on a unified state model, the matrix P (t) is decomposed into the product of two matricesI.e. real time output powerByInstead of, i.e. using
In the formula (I), the compound is shown in the specification,are diagonal matrix, diagonal elementsThe upper limit of the output power of the demand side resource j; the diagonal matrix B is an output power control matrix, and diagonal elementsIs a control variable used to increase or decrease the output power of the demand-side resource j.
The modified unified state model is then shown in equation (28).
The response sequence of the demand-side resource is determined by the arrangement sequence in the unified state model and is continuously updated with the time. For example, exchange the order of responses for the m and n rows of demand-side resources: 1) exchanging elements of the m-th row and the n-th row for column matrices x (t) and δ (t); 2) for diagonal matrices B andthe diagonal elements of the m-th and n-th rows are swapped.
As shown in fig. 4, when the output power is increased, the order of response of the demand-side resource is: distributed power (increased output), electric car (load shedding) and temperature controlled load (shutdown device), electric car (discharge), uncontrollable resource (reached upper limit of output power).
As shown in fig. 5, when the output power is reduced, the order of response of the demand-side resource is: electric cars (reduced discharge), electric cars (increased charge) and temperature controlled loads (turned on devices), distributed power supplies (reduced output), uncontrollable resources (reached lower output power limit).
On the basis of the unified state model, the capability of increasing the output power is shown as a formula (29), and the capability of reducing the output power is shown as a formula (30). Pup(t) is a matrix of dimension N × 1, and the non-negative value elements of the mth row indicate the ability of the mth resource to increase the output power. Pdn(t) is an N x 1 dimensional matrix, and the non-positive value elements in the mth row indicate the ability of the mth resource to reduce output power.
In the form of matrixThe diagonal element of (a) is the controllable variable maximum; l is0Is an N × 1 dimensional matrix with elements all 1.
In the form of matrixBIs the controllable variable minimum.
To further illustrate the responsiveness of demand-side resources, a lower triangular matrix is definedAndB *to evaluate the ability of the demand side resources to increase and decrease output power,andB *the element in (A) is represented by formula (31).
After the improvement, the ability to increase and decrease output power is shown as equation (32).
In the formula, Pup*(t) is an Nx 1 dimensional matrix, and the non-negative value element of the mth row represents the capability of increasing the output power of 1-m resources; pdn*(t) is also an N x 1 dimensional matrix, with the non-positive value elements in the m-th row indicating the ability of 1-m resources to reduce output power.
The third step: determining an actual control matrix B*
B*=B (34)
Therefore, the output power of the demand-side resource can be obtained by equation (36), and the updated state model of the demand-side resource is shown by equation (37).
Example simulation and result analysis
In this embodiment, an IEEE-33 node distribution network is taken as an example [24]The effectiveness of the proposed load curve smoothing strategy based on the demand side resource unified state model is verified. Each load node has 10-40 users [25 ]]And assuming that each home is equipped with a rooftop photovoltaic, the rooftop area is [60,100 ]]And the photovoltaic power density is 100W/m2Data reference UKGDS [26 ] for photovoltaic power generation and user load]。
The number of electric vehicles per user is 1.86 [27], the rated charge-discharge power of the electric vehicle is 7kW [28], and other parameters such as battery capacity, charge-discharge efficiency, charge and go time, user demand SOC, maximum and minimum value of SOC, and the like are cited in reference [29 ].
It is assumed that each user has a heat pump. The rated power consumption of the heat pump is 6kW [30], and other parameters such as outdoor temperature, upper and lower limits of indoor temperature, thermal resistance and capacitance are referred to in reference [17 ].
3-1) load curve smoothing control effect
When the load curve smoothing strategy is not considered, the output powers of the distributed power supply, the electric automobile, the temperature control load, the uncontrollable load and the total load are shown in fig. 6, and the power fluctuation of the total load is mainly caused by the randomness of the output power of the distributed power supply.
Therefore, a load curve smoothing control strategy is required to be adopted to smooth the power fluctuation of the load, in this embodiment, assuming that the limit of the power fluctuation rate per 15 minutes is 10%, the total load, the target power of the total load and the total load after control are as shown in fig. 7, and it can be seen that the power fluctuation condition of the load is obviously reduced. However, in the period from 8:00 to 15:00, the actual load value cannot accurately follow the smoothed load target value, and sometimes the actual load value is lower than the smoothed load target value, which are caused by the response capability of the demand-side resource whose output power increases reaching the limit.
The load power fluctuation rate under uncontrolled and controlled conditions is shown in fig. 8, and the power fluctuation rate of the load is kept below 10% after the control strategy is adopted.
3-2) demand side resource response characteristics
The output power of the uncontrolled and controlled distributed power supply is shown in fig. 9, the controlled distributed power supply output can well track the uncontrolled distributed power supply output, and the main reason is that in the load curve smooth control strategy, the distributed power supply is the first means for increasing the output power and the last means for reducing the output power, so that the absorption and absorption of renewable energy can be effectively promoted.
The output power of the electric automobile under the uncontrolled and controlled conditions is shown in fig. 10, and the fluctuation of the output power of the electric automobile is large in a period from 8:00 to 15:00, and the main reason is that the electric automobile changes the connection state (charging, idling and discharging) with a power distribution network. To increase the output power, the electric vehicle being charged will stop charging or even discharge to the grid, so there is a time when the total output power of the electric vehicle is greater than zero. And the traveling habits of the electric automobiles of residents have certain similarity, so that the charging load of the electric automobiles has a peak value.
Output power of uncontrolled and controlled temperature controlled loads as shown in fig. 11, the controlled temperature controlled load output power can almost follow the uncontrolled output power before 5:00, mainly because the power fluctuation of the load during this time is small. After 5:00, the output power of the temperature-controlled load after control cannot follow the output power under no control, mainly because the temperature-controlled load participates in the control of stabilizing the fluctuation of the load power. The output power of the temperature-controlled load after control is close to 0 in the period from 15:00 to 17:00, mainly because almost all the temperature-controlled loads are in the off state in response to the power fluctuation. However, in the period from 18:00 to 19:00, the output power of the temperature-controlled load after control peaks, mainly because the temperature-controlled load in the off state is gradually turned on due to the continuous drop of the indoor temperature.
To further illustrate the response characteristics of the electric vehicle in the control strategy, the SOC state of the electric vehicle accessing the power grid under no control and under control is shown in fig. 12, while the SOC state in the trip overcharge is not given when the electric vehicle is traveling. In the period from 08:00 to 15:00, most electric automobiles are in a trip state and cannot respond to power fluctuation of loads; in the period from 15:00 to 20:00, most electric automobiles finish traveling and start charging. Under the condition that a load curve smooth control strategy is not considered, the charging process is not influenced, the change process of the SOC state of the electric automobile is obviously different after the control, the line of the rising trend indicates that the electric automobile is being charged, the line of the falling trend indicates that the electric automobile is being discharged, and the line of the horizontal trend indicates that the electric automobile is only connected to a power distribution network and the output power is zero (idle state). In the load curve smoothing control strategy, the electric automobile responds to load fluctuation by changing the access state of the electric automobile
To further illustrate the response characteristics of a temperature controlled load in a control strategy, the room temperature at which the temperature controlled load is subjected to both uncontrolled and controlled conditions is shown in FIG. 13. The line of the rising trend indicates that the room temperature rises and the temperature control load is in the on state, and the line of the falling trend indicates that the room temperature falls and the temperature control load is in the off state. As can be seen from FIG. 13(a), the room temperature was varied regularly between 19 ℃ and 23 ℃ without control; as can be seen from fig. 13(b), the indoor temperature change process under control is significantly different. To increase the output power, the temperature controlled load with higher room temperature and in the on state will be preferentially selected to participate in the load smoothing control, while the output power of the temperature controlled load in fig. 11 is close to 0 in the period from 15:00 to 17:00, and as can be seen from fig. 13(b), the reason why the temperature controlled load response capability is limited in this period is further illustrated.
According to the invention, on the basis of a unified state model, a load curve smooth control strategy is utilized, the load power fluctuation of the power distribution network is obviously reduced, and meanwhile, the energy utilization comfort level of a user is ensured in the process of controlling the output power of the resource at the demand side.
While the present invention has been described with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments, which are intended to be illustrative rather than restrictive, and many modifications may be made by those skilled in the art without departing from the spirit of the present invention within the scope of the appended claims.
Claims (1)
1. A load smooth control method based on a demand side resource unified state model comprises the following steps:
step one, establishing a uniform state model of demand side resources:
dividing the time of one day into M time intervals by taking a distributed power supply, an electric automobile and a temperature control load as demand side resources, wherein each interval time is delta t, namely M multiplied by delta t is 24 h;
the superscript i is used for indicating the resource type, i belongs to { G, V, L }, G, V and L respectively represent a distributed power supply, an electric automobile and a temperature control load; the subscript j is used for indicating the number of a specific demand side resource in the distributed power supply G, the electric automobile V and the temperature control load L;
1-1) establishing a distributed power state model as follows:
distributed electricityUpper limit of output power of source jAnd lower limitThe following were used:
in the formula (1), the reaction mixture is,the maximum output power provided by the distributed power supply j in a real-time state at the moment t;
the state model of the distributed power supply is as follows:
in the formula (2), the reaction mixture is,is the accumulated amount of output power of the distributed power supply j in a real-time state, wherein, the output power of the distributed power supply j in a real-time state is within the upper limit and the lower limit respectivelyAnd the accumulated quantity of the electric energy generated by the distributed power supply j with rated output power is calculated according to the formula (3):
1-2) establishing an electric automobile state model, comprising the following steps:
in the formula (4), the reaction mixture is,in order to start the charging time,in order to start the time of the trip,andrated charge and discharge powers, respectively;in order to be the maximum output power,is a positive value;in order to achieve the minimum output power,is a negative value;
in the formula (5), the reaction mixture is,the real-time SOC value of the electric vehicle j is obtained;the electric vehicle j is charged at the rated power up to the upper limit of the SOC,discharging the electric vehicle j at rated power until reaching the lower limit of the SOC; when the electric automobile is charged, the SOC value rises to the SOC value required by the userIf so, stopping charging;
when the electric automobile is connected with the power distribution network, the j state model of the electric automobile is as follows:
in the formula (6), the reaction mixture is,for the real-time power output of the electric vehicle j, for the corrected j battery capacity of the electric vehicle,comprises the following steps:
in the formula (7), the reaction mixture is,the actual battery capacity of the electric automobile;andrespectively the charging efficiency and the discharging efficiency of the electric vehicle,is the output power;
1-3) establishing a temperature control load state model
in the formula (8), the reaction mixture is,rated power consumption;in order to obtain a lower limit of the output power,is a negative value;in order to achieve the upper limit of the output power,the value is 0;
normalized indoor temperature of temperature controlled load jAnd outdoor temperatureAs shown below, wherein,
the state model of the temperature-controlled load is as follows:
in the formulae (9) and (10),is the temperature of the room in question,andrespectively the upper and lower limits of the temperature control threshold,is the temperature of the outside of the room,andupper and lower limits of the indoor temperature, respectively; in thatDuring the time period, the temperature control load is in an on state and the indoor temperature risesIn the time period, the heat source equipment is in a turn-off state, and the indoor temperature is reduced; for temperature-controlled loads in the on state, the temperature isRange-off, temperature in the case of temperature-controlled loads in the off stateOpening when the range is reached;
is normalized outdoor temperature, ajIs equal toWherein R isjAnd CjRespectively a thermal resistor and a capacitor;to output power, when the temperature controlled load is in an on state,the temperature controlled load in the off state,is composed of
1-4) establishing a unified state model, including
The numbers of the distributed power supply, the electric automobile and the temperature control load are respectively NG、NV、NLAnd satisfy NG+NV+NL=N;
According to the distributed power supply state model, the electric vehicle state model and the temperature control load state model respectively expressed by the above equations (2), (6) and (10), the demand side resource state model is expressed by equation (11):
wherein:
on the basis of equation (11), the demand-side resource unified state model is shown as equation (18):
x(t+Δt)=x(t)+P(t)δ(t) (18)
in equation (18), the column vector x (t) is the real-time status of the demand-side resource, and the element satisfiesThe superscript i represents a resource type, and i G, i V, i L represents that the resource type is a distributed power supply, an electric automobile and a temperature control load; the diagonal matrix P (t) is a real-time output power matrix of the resource at the demand side, and the diagonal elements meetThe column vector δ (t) is defined as the modified time interval;
step two, smooth control of a load curve:
and evaluating the load fluctuation condition of the power distribution network by using the power fluctuation rate, wherein the load fluctuation condition is expressed by formulas (19) and (20):
in the formulae (19) and (20), the function fTUsed for calculating the power fluctuation rate of the load in the time period T; function(s)Andused for calculating the maximum value and the minimum value of the load in the time period T;is the rated value of the load;andload maximum and minimum; pt DA real-time load value;
the method for realizing the smooth control of the load curve comprises the following steps:
the first step is as follows: determining a target power for load smoothing
By rtRepresents the real-time power fluctuation rate, as shown in equation (21):
then, a target power value P for load smoothing is determinedt *
Pt *=Pt D(24)
in equations (22), (23) and (24), the upper limit of the load real-time power fluctuation rateAnd lower limitAs shown in equation (25):
in the formula (25), the reaction mixture,is the power fluctuation ratio rTThe limit of (2); delta Pt *The target variation power for load smoothing is shown as equation (26);
ΔPt *=Pt *-Pt D(26)
the second step is that: determining responsiveness of different demand side resources
To implement a load curve smoothing strategy based on a unified state model, the matrix P (t) is decomposed into the product of two matricesI.e. real time output powerByInstead of, i.e. using
In the formula (27), the reaction mixture is,are diagonal matrix, diagonal elementsThe upper limit of the output power of the demand side resource j; the diagonal matrix B is an output power control matrix, and diagonal elementsTo increase or decrease the control variable for the output power of the demand-side resource j,
the formula (18) is rewritten as follows:
the ability to increase output power is:
the ability to reduce output power is:
in the formulas (29) and (30), matrixIs the maximum value of the controllable variable, the matrixBIs the minimum value of the controllable variable; l is0Is an N × 1 dimensional matrix with elements all 1; pup(t) is a matrix of dimension N × 1, the non-negative elements of the mth row indicating the ability of the mth resource to increase output power; pdn(t) is an N × 1 dimensional matrix, and the non-positive value element in the mth row represents the capability of the mth resource to reduce the output power;
define lower triangular matrixAnd lower triangular arrayB *Respectively evaluating the capacity of increasing output power and the capacity of reducing output power of the resource at the demand side, and setting a lower triangular arrayAnd lower triangular arrayB *The element in (1) is shown as formula (31):
the following are written over equations (29) and (30):
in the formula (32), Pup*(t) is an Nx 1 dimensional matrix, and the non-negative value element of the mth row represents the capability of increasing the output power of 1-m resources; pdn*(t) is also an N × 1 dimensional matrix, the non-positive value elements of the m-th row represent the ability of 1-m resources to reduce output power;
the third step: determining an actual control matrix B*
(ii) when Δ Pt *When the content is equal to 0, the content,
B*=B (34)
the output power of the demand-side resource is represented by equation (36):
the updated state model of the demand-side resource is represented by equation (37):
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