CN116742638A - Method, system and medium for realizing source-charge cooperative control of photovoltaic and electric heating load power complementation - Google Patents
Method, system and medium for realizing source-charge cooperative control of photovoltaic and electric heating load power complementation Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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Abstract
The invention relates to a source load cooperative control method, a system and a medium for realizing complementation of photovoltaic and electric heating load power. Firstly, constructing a time-varying relation between heat supply quantity and indoor temperature change, constructing a thermal dynamic model, mapping a transient heat balance relation through an indoor temperature change rate, constructing a thermal comfort temperature of a human body in winter, and restricting the change range of the indoor temperature; evaluating the adjusting capability of the single electric heating load of start-stop control; then, clustering the electric heating load according to rated power, equivalent thermal resistance and equivalent heat capacity, and providing a relay type control strategy of the electric heating load group; and finally, based on the established electric heating load aggregation model, the collected distributed photovoltaic power generation power and electric heating load power signals are used as feedback signals to carry out comprehensive optimization control on the electric heating load power. The invention realizes accurate modeling of single electric heating load and quantitative evaluation of electric heating load adjusting capability on the premise of ensuring the heating comfort level of users.
Description
Technical Field
The invention belongs to the technical field of operation and control of electric power systems, and particularly relates to a source load cooperative control method, a system and a medium for realizing complementation of photovoltaic and electric heating load power.
Background
With the gradual progress of energy strategy to large-scale new energy power generation and networking, the influence of uncertainty of new energy such as distributed photovoltaic on safe and stable operation of a power grid becomes an urgent problem to be solved. From the economical and practical considerations, the novel flexible resource of load demand side response is utilized, and the novel flexible resource has important significance in participating in peak regulation and frequency modulation of the power grid and in absorbing new energy. The heating load, especially the electric heating load, has the characteristics of high power consumption and stable power, and has great power regulation potential. For the networking mode of the north heating load and the large power grid system, how to develop load demand response, the establishment of a source load cooperative control method through complementary operation of distributed photovoltaic and flexible heating load power is a powerful way for solving the problem of new energy consumption of photovoltaic and the like.
In summary, the aggregation control strategy of the distributed photovoltaic and the flexible heating load is researched to participate in demand response, and the auxiliary power grid stabilizes power fluctuation caused by new energy access, so that the method is a good mode of multiparty participation and multiparty reciprocity. The heating user can obtain certain economic compensation under the condition of permission of production conditions; the power grid company can guarantee the stable and reliable operation of the power grid at lower cost; the new energy power generation method improves the new energy access rate; overall improved overall economic benefit of the load-net-source is achieved.
Disclosure of Invention
The invention aims to provide a source load cooperative control method capable of realizing complementation of photovoltaic and electric heating load power, which comprises the following steps: and a heating load power regulation and control mode is provided by modeling the aggregation of the flexible heating loads. And comprehensively considering constraint conditions such as heating comfort level, electric heating load power regulation capability and the like, taking the collected distributed photovoltaic power signal as feedback quantity, and issuing a regulation instruction to electric heating loads of all levels by a dispatching center to realize the stabilization of distributed photovoltaic power fluctuation.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the source load cooperative control method for realizing the complementation of the photovoltaic and electric heating load power is characterized by comprising the following steps:
constructing a time-varying relation between heat supply quantity and indoor temperature change, constructing a thermal dynamic model according to thermodynamic characteristics of a standard building, and mapping a transient heat balance relation through an indoor temperature change rate; establishing the thermal comfort temperature of a human body in winter and restricting the change range of the indoor temperature; on the basis of the above, evaluating the adjustment capability of the single electric heating load of the start-stop control;
clustering electric heating loads according to rated power P, equivalent thermal resistance R and equivalent heat capacity C, and providing a relay type control strategy of an electric heating load group;
based on the established electric heating load aggregation model, the collected distributed photovoltaic power generation power and electric heating load power signals are used as feedback signals to carry out comprehensive optimization control on the electric heating load power.
In the above method, thermodynamic dynamic modeling of standard buildings is based on the following formula
Wherein C is air ，ρ air Air specific heat capacity and air density respectively;and->The indoor temperature and the outdoor temperature at t are respectively, S is the external surface area of a standard user determined according to the building body shape coefficient, V is the space volume of the standard user determined according to the building body shape coefficient, P eh The heat supply power for electric heating is K is the comprehensive heat conductivity coefficient of the outer surface obtained according to the heat conductivity coefficient relation in the building energy-saving design standard, and the heat supply power is +.>Is the rate of change of the indoor temperature.
Further neglecting the temperature difference between the indoor wall body and the outdoor wall body, the first-order ETP model of the electric heating load can be obtained by assuming that the indoor air temperature is the same as the solid temperature at the same time as follows:
t in out Is an outdoor temperature value; t (T) in Is an indoor temperature value; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; η is the heat conversion efficiency of the electric heating equipment, and P is the electric power of the electric heating equipment; k (K) t For the start-stop state of the electric heating equipment at the time t, a value of 1 indicates that the equipment is in an on state, and a value of 0 indicates that the equipment is in an off state; t is the simulation time, Δt is the simulation time step.
The above-mentioned squareAccording to the method, PMV index lambda of human body comfort level PMV The calculation formula is as follows:
wherein M is the energy metabolism of human body, t s Is the temperature of human skin, t a Is the indoor ambient temperature, I c1 Is the thermal resistance of the clothing of the human body. When PMV is at [ -1,1]When the range is within the interval range, the thermal comfort of the user to the environment is satisfied, and when the range is exceeded, the thermal comfort of the user is poor. When PMV is more than or equal to 0.5 and less than or equal to 1 according to the related content of 'civil building heating ventilation and air conditioning design specification', i.e. II-level comfort level is achieved, the heating temperature interval is [18 ℃,22℃ ]]。
The range of variation of the indoor temperature is restrained by utilizing the thermal comfort temperature, and the method is specifically shown as the following formula:
wherein T is min Is the lower limit of the indoor temperature, T, set by the operation of the electric heating equipment max Is the upper limit of indoor temperature set by the operation of the electric heating equipment, and deltat is the simulation step size.
Based on a first-order ETP model of the electric heating load, the control mode of the electric heating load related to the patent is start-stop control, so that the adjusting capacity of the electric heating load in the power dimension is fixed, namely, when the electric heating load is started, the power of the electric heating load is rated power, and when the electric heating load is stopped, the power of the electric heating load is zero. The adjustment duration of the single electric heating load is quantitatively analyzed, and the down adjustment duration tau of the electric heating load can be obtained off And the up-regulation time length tau on ：
T in out Is an outdoor temperature value; t (T) in Is an indoor temperature value; η is the heat conversion efficiency; p is the power of an electric heating load; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; t is the simulation time.
From the above formula, it can be further deduced that the theoretical initial indoor temperature is T max Maximum time tau for shutting down the electric heating load off_max And an initial indoor temperature of T min Maximum time τ of turn-on on_max ：
In the method, the electric heating groups are grouped according to the rated power, and rated powers in the groups are the same. Firstly, the electric heating loads are initially divided into X groups according to the load power, and the load powers in the groups are approximately equal. After preliminary grouping, carrying out cluster analysis on the loads of the X groups according to the equivalent thermal resistance R and the equivalent heat capacity C, wherein each group forms Y load groups. And finally, adopting the parameter value of the clustering center point of each load group as the equivalent thermal resistance R and the equivalent heat capacity C of the electric heating load in the group. The specific steps are as follows:
(1) After preliminary grouping, let matrix V be the parameter matrix of equivalent thermal resistance R, equivalent heat capacity C of n electric heating loads containing a certain electric heating load group, namely matrix V be n×2 matrix. Normalizing the elements in the matrix V, and recording the normalized matrix as V':
v in ij Is the original element in the matrix V, V' ij Is the element of matrix V after normalization processing, V imax Is the maximum of the j-th term in the set of parameters.
(2) Setting the electric heatingThe aggregation group number Y of the load group and the threshold epsilon of iteration end, Y samples are randomly extracted in a matrix V' as initial values and are assigned to an aggregation center Z L (L＝1,2,Y),Z L ＝(Z L1 ,Z L2 )。
(3) The equivalent thermal resistance R and the equivalent heat capacity C of the kth (k is more than or equal to 1 and less than or equal to n) load in the electric heating load group jointly form a parameter v' k ，v' k ＝[v' k1 ,v' k2 ]The Euclidean distance D to the center of each polymer is calculated according to the following formula kL
Wherein z' L1 ,z' L2 Respectively the parameter values of the current polymerization center point, v' k1 ,v' k2 The parameter values of the kth load, respectively.
(4) Solving the membership M of the kth individual to the center point of the L-th polymer in the data matrix V' formed by R, C kL 。
D in ky And Y is the total number of clustering center points, wherein the distance from the kth individual to the kth aggregation center point is the total number of clustering center points.
(5) Substituting the results obtained in the steps (3) and (4) into the following centers X of the first electric heating polymers L And performing iterative updating.
M in the formula kL Membership of the kth individual to the center point of the L-th polymer in the data matrix V ', V' k Is a parameter composed of the equivalent thermal resistance R and the equivalent heat capacity C of the kth (k is more than or equal to 1 and less than or equal to n) load in the electric heating load group.
(6) According to steps (3) to (5), an objective function G (t) is determined as shown in the following formula
M in the formula kL Membership of kth individual to the center point of the L-th polymer in data matrix V', D kL Euclidean distance from kth individual to the center of the L-th aggregate in data matrix V'.
(7) And judging the convergence of G (t). Setting the objective function of the previous iteration as G (t-1), if the difference between G (t) and G (t-1) is larger than epsilon, returning to the step (3) for continuing, if the difference between G (t) and G (t-1) is smaller than epsilon, ending the cluster grouping process, and using X L As the final polymerization center.
Comparing the membership degree calculated in the step (4) with the samples V ' in the data matrix V ' formed by R, C ' k Membership degree M to individual Polymer Lk The electric heating loads are grouped according to the size of the electric heating load, and finally, an electric heating load homogeneous aggregation group with power close to that of the electric heating load and with the equivalent heat capacity and the equivalent thermal resistance similar to each other is formed.
In the method, the electric heating load aggregation model is expressed as
P (t) is the aggregate power of n electric heating loads at t time, P i Rated power for the ith electric heating equipment; k (K) i t Indicating the start-stop state of the ith electric heating load at the moment T set Representing the operation set temperature value of the electric heating equipment, delta is a human body heat comfort temperature zoneWidth of the space; t (T) out Is an outdoor temperature value; t (T) in Is an indoor temperature value; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; η is the heat conversion efficiency of the electric heating equipment, and P is the electric power of the electric heating equipment; k (K) t For the start-stop state of the electric heating equipment at the time t, a value of 1 indicates that the equipment is in an on state, and a value of 0 indicates that the equipment is in an off state; t is the simulation time, Δt is the simulation time step.
Based on the above method and the electric heating load uniformity aggregation model, a relay type control strategy in the electric heating load group is provided, and the electric dispatching center gives an electric heating load increasing/reducing and the regulating duration is t control On the premise of meeting the thermal comfort temperature constraint, the load in the electric heating load group can be divided into two types with the adjusting capability and the load without the adjusting capability, and further the load with the adjusting capability is divided into two types: one type is that the adjustable time length is greater than or equal to t control Another category is that the adjustable duration is less than t control A kind of electronic device. When relay control is adopted, the adjustment potential of the electric heating load group can be fully excavated, the load which originally has the adjustment duration not meeting the requirement is brought into the dispatch, and the mutual coordination among the loads can realize that the adjustment time of the electric heating load group is t control Time modulated capacity boost ΔP control Electric quantity lifting delta W capable of being increased/reduced control 。
In the above method, the relay control strategy includes:
(1) First, the total number N of loads included in the electric heating load group, the load power P, the equivalent thermal resistance R and the equivalent heat capacity C of the user are set, and the electric heating loads in the load group are numbered (i=1, 2 … …, N).
(2) The method comprises the steps of collecting indoor initial temperature and outdoor temperature data of each electric heating load, generating a time sequence of load operation by using an established electric heating load thermodynamic model, and evaluating the adjustment capability of the load.
(3) Judging whether relay control is performed or not according to the scheduling requirement R and the individual load regulation capacity R, and if the load regulation capacity R is larger than R, increasing the regulation capacity of the load group by P. For the load with the adjustment capacity R < R, the two relay modes can be matched with each other, so that the adjustment requirement is met, and the adjustable capacity of the load group is improved.
(4) And (3) until the last electric heating load is finished (2) and (3), finishing the control process, and outputting the adjustment capacity (adjustment time and adjustment capacity) of the electric heating load group and the load information which can participate in dispatching.
In the method, when comprehensively controlling, firstly, initial conditions such as electric heating heat supply power, building indoor temperature and the like are given, and a dispatching center determines a dispatching target in a certain period according to the collected distributed photovoltaic power signals and the real-time electric heating load power signals and transmits indexes to an electric heating polymer; and the electric heating aggregate receiving the instruction adjusts the load by changing the start-stop state, and returns the updated indoor temperature and load information of the standard user electric heating load to the load aggregator after meeting the requirement of the dispatching instruction, and the load aggregator returns to the dispatching center of the power system.
The invention has the following advantages:
(1) The invention realizes accurate modeling of single electric heating load and quantitative evaluation of electric heating load adjusting capability on the premise of ensuring the heating comfort level of users.
(2) The invention provides a cluster treatment for distributed electric heating loads according to load power and equivalent thermal parameters of users, and provides relay in the electric heating load group "
And the control strategy effectively improves the adjustment capability of the electric heating load group.
(3) The invention utilizes the regulating capability of the electric heating load aggregate to participate in power grid dispatching, thereby realizing the cooperative operation of the distributed photovoltaic and electric heating load group, effectively stabilizing the power fluctuation of the photovoltaic unit, improving the internet-surfing electric quantity of the photovoltaic unit and increasing the economic benefit.
Drawings
FIG. 1 is a flow chart of a "relay" control strategy;
FIG. 2 is a simulation circuit diagram of an electric heating load first-order ETP model;
FIG. 3a is a schematic diagram of the response capability of a single electric heating load (schematic diagram of the downward regulation of the electric heating load);
FIG. 3b is a schematic diagram of the response capability of a single electric heating load (schematic diagram of the upward adjustment of the electric heating load);
FIG. 4 is a general schematic diagram of an electrical heating load participating in demand response;
FIG. 5 is a "relay" control scenario one;
FIG. 6 is a second "relay" control scenario;
FIG. 7a is a schematic diagram of a multi-time scale relay back and forth adjustment capability (up adjustment capability);
FIG. 7b is a schematic diagram of a multi-time scale relay back and forth adjustment capability (downadjustment capability);
Detailed Description
The technical scheme of the invention is further specifically described below through examples and with reference to the accompanying drawings.
Examples:
the method comprises the following steps:
step 1, constructing a time-varying relation between heat supply quantity and indoor temperature change, constructing a thermal dynamic model according to thermodynamic characteristics of a standard building, and revealing a transient heat balance relation through indoor temperature change rate; establishing the thermal comfort temperature of a human body in winter and restricting the change range of the indoor temperature;
step 2, clustering the electric heating load according to the rated power, the equivalent thermal resistance R, the equivalent heat capacity C and other parameters to realize the cluster aggregation modeling and regulation of the electric heating load parameter homogenization;
step 3, based on the established electric heating load aggregation model, the collected distributed photovoltaic power generation power and electric heating load power signals are used as feedback signals, and a comprehensive control strategy of the electric heating load power is provided, so that complementary operation of the distributed photovoltaic power and the flexible heating load power is realized;
in the above method for implementing source load cooperative control of complementation of photovoltaic and electric heating load power, the specific implementation of step 1 includes:
step 1.1, thermodynamic dynamic modeling of a standard building:
due to the building enclosure structure, the building has certain heat storage capacity. Comprehensively considering the energy transfer process between the environment and the building, considering the difference among the indoor air, the outer wall and the inner wall temperature, and establishing a state equation of the temperature variable of the working state and related parameters. The heat transfer amount per unit building area per unit time for a standard user is calculated as follows:
wherein: q (Q) i Heat transfer per unit building area per unit time; A. s is the total area and the outer surface area of the standard user determined according to the building body shape coefficient. Epsilon is the correction coefficient of the heat transfer coefficient of the building surface. K is the comprehensive heat conductivity of the outer surface obtained according to the heat conductivity relation in the building energy-saving design standard,is the indoor temperature at the moment t>The outdoor temperature at time t.
Further simplifying the model, establishing a first-order ETP model of electric heating load, wherein the simulation circuit diagram is shown in figure 2, R and C are respectively equivalent thermal resistance, equivalent heat capacity and T of a room in Is the indoor temperature, T out Is the outdoor temperature, Q c Is the heat storage capacity of the room. The first-order ETP model derivation process of the electric heating load is as follows:
assume that the heating quantity Q of the electric heating load at the t-th moment eh,t Is that
Q eh,t ＝ηP
Wherein eta is the heat conversion efficiency of the electric heating equipment, and P is the electric power of the electric heating equipment.
Room heat dissipating capacity at time tQ s,t The method comprises the following steps:
k in the formula i The heat dissipation coefficient of the enclosure structure; s is S i The heat dissipation area of the enclosure structure is;the indoor temperature at time t; />The outdoor temperature at time t; n is the number of the enclosure structures, including an inner wall layer, an outer wall layer, a roof layer, a door and window floor and the like.
Heat storage quantity Q of room at t-th moment c,t The method comprises the following steps:
the final thermodynamic model of the overall available room is:
simplifying the model, further neglecting the temperature difference between the indoor wall and the outdoor wall, and assuming that the indoor air temperature is the same as the solid temperature at the same time [9] The first-order ETP model of the available electric heating load is as follows:
t in out Is an outdoor temperature value; t (T) in Is an indoor temperature value; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; k is the start-stop state of the electric heating equipment, a value of 1 indicates that the equipment is in an on state, a value of 0 indicates that the equipment is in an off state, and the subsequent analysis of the operation characteristics of the electric heating load can involve the analysis of the start-stop state; t is the simulation time, Δt is the simulationTrue time step.
Step 1.2, human comfort temperature constraints indoor temperature variation
The indoor temperature needs to meet the requirements of the human body on the thermal comfort, namely the thermal comfort temperature. The thermal comfort temperature is affected by many aspects of the person's physiology, psychology and behavior, humidity parameters in the environment, etc., and is also typically a range of values. The comfort of the human body is usually indicated by PMV indicators. The PMV index represents the average value of the cold and hot sensations of a plurality of people in the same environment, 7-level scales are used for corresponding to 7 sensations of a human body, PMV is 0 and corresponds to the optimal thermal comfort state of the indoor thermal environment, PMV is +1, +2 and +3 respectively represent slightly warm, warm and hot, and PMV is-1, -2 and-3 respectively represent slightly cool, cool and cool. The floating interval of PMV is + -1, and the comfort PMV index lambda of human body PMV The calculation formula is as follows:
wherein M is the energy metabolism of human body, t s Is the temperature of human skin, t a Is the indoor ambient temperature, I c1 Is the thermal resistance of the clothing of the human body. When PMV is at [ -1,1]When the range is within the interval range, the thermal comfort of the user to the environment is satisfied, and when the range is exceeded, the thermal comfort of the user is poor. When PMV is more than or equal to 0.5 and less than or equal to 1 according to the related content of 'civil building heating ventilation and air conditioning design specification', i.e. II-level comfort level is achieved, the heating temperature interval is [18 ℃,22℃ ]]。
The range of variation of the indoor temperature is constrained by the thermal comfort temperature, as follows. From the piecewise linearized thermal equilibrium equation:
wherein T is min Is the lower limit of the indoor temperature, T, set by the operation of the electric heating equipment max Is the upper limit of indoor temperature set by the operation of the electric heating equipment, and deltat is the simulation step size.
For single electric heating load, its responseThe capacity is shown in fig. 3a, when the electric heating apparatus is in an on state, the indoor temperature is continuously increased, and at this time, the apparatus does not have an up-regulation capacity, but has a down-regulation capacity. The down-regulation capability is represented by the load capacity delta P which can be cut off down After the electric heating equipment is shut down, the indoor temperature is reduced to the lower temperature limit T min Is τ off Product ΔE of the two down Indicating the amount of electricity that can be cut down during this period. As shown in fig. 3b, when the electric heating apparatus is in a shut-down state, the indoor temperature is continuously decreased, and at this time, the apparatus does not have a down-regulation capability but has an up-regulation capability. The up-regulation capability is represented by delta P which can be increased load capacity up After the electric heating equipment is started, the indoor temperature rises to the upper temperature limit T max Is τ on Product ΔE of the two up Indicating the amount of electricity that can be used to increase over the period of time.
Based on a first-order ETP model of the electric heating load, quantitatively analyzing the adjustment duration of a single electric heating load to obtain the down-adjustment duration tau of the electric heating load off And the up-regulation time length tau on Respectively is
T in out Is an outdoor temperature value; t (T) in Is an indoor temperature value; η is the heat conversion efficiency; p is the power of an electric heating load; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; t is the simulation time.
From the above formula, it can be further deduced that the theoretical initial indoor temperature is T max Maximum time tau for shutting down the electric heating load off_max And an initial indoor temperature of T min Maximum time τ of turn-on on_max ：
The specific implementation of the step 2 comprises the following steps:
step 2.1, electric heating load clustering treatment
Firstly, the electric heating loads are initially divided into X groups according to the load power, and the load powers in the groups are approximately equal. After preliminary grouping, carrying out cluster analysis on the loads of the X groups according to the equivalent thermal resistance R and the equivalent heat capacity C, wherein each group forms Y load groups. And finally, adopting the parameter value of the clustering center point of each load group as the equivalent thermal resistance R and the equivalent heat capacity C of the electric heating load in the group. The specific steps are as follows:
(1) After preliminary grouping, let matrix V be the parameter matrix of equivalent thermal resistance R, equivalent heat capacity C of n electric heating loads containing a certain electric heating load group, namely matrix V be n×2 matrix. Normalizing the elements in the matrix V, and recording the normalized matrix as V':
v in ij Is the original element in the matrix V, V' ij Is the element of matrix V after normalization processing, V imax Is the maximum of the j-th term in the set of parameters.
(2) Setting the aggregation group number Y of the electric heating load group and the threshold epsilon of iteration ending, randomly extracting Y samples in a matrix V' as initial values and giving the initial values to an aggregation center Z L (L＝1,2，…Y),Z L ＝(Z L1 ,Z L2 )。
(3) The equivalent thermal resistance R and the equivalent heat capacity C of the kth (k is more than or equal to 1 and less than or equal to n) load in the electric heating load group jointly form a parameter v' k ，v' k ＝[v' k1 ,v' k2 ]The Euclidean distance D to the center of each polymer is calculated according to the following formula kL
Wherein z' L1 ,z' L2 Respectively the parameter values of the current polymerization center point, v' k1 ,v' k2 The parameter values of the kth load, respectively.
(4) Solving the membership M of the kth individual to the center point of the L-th polymer in the data matrix V' formed by R, C kL 。
D in ky And Y is the total number of clustering center points, wherein the distance from the kth individual to the kth aggregation center point is the total number of clustering center points.
(5) Substituting the results obtained in the steps (3) and (4) into the following centers X of the first electric heating polymers L And performing iterative updating.
(6) According to steps (3) to (5), an objective function G (t) is determined as shown in the following formula
(7) And judging the convergence of G (t). Setting the objective function of the previous iteration as G (t-1), if the difference between G (t) and G (t-1) is larger than epsilon, returning to the step (3) for continuing, if the difference between G (t) and G (t-1) is smaller than epsilon, ending the cluster grouping process, and using X L As the final polymerization center.
Comparing the membership degree calculated in the step (4) with the samples V ' in the data matrix V ' formed by R, C ' k Membership degree M to individual Polymer Lk The electric heating loads are grouped according to the size of the electric heating load, and finally, an electric heating load homogeneous aggregation group with power close to that of the electric heating load and with the equivalent heat capacity and the equivalent thermal resistance similar to each other is formed.
Step 2.2, electric heating load aggregation modeling
The parameter values of the household electric heating load model obey a certain probability distribution, the parameter values of different electric heating loads are relatively independent, but the heat supply power has a certain positive correlation with the building area and the equivalent heat capacity and the equivalent thermal resistance. The equivalent heat capacity C and the equivalent thermal resistance R can be randomly selected according to a probability model.
Firstly, extracting parameters required by individual modeling of electric heating loads: rated power P for electric heating eh And constructing a probability model by using the equivalent heat capacity C of the user, the equivalent thermal resistance R and the like, wherein the equivalent heat capacity C and the equivalent thermal resistance R of the electric heating room accord with Gaussian distribution. And sampling according to the probability distribution to select the specific values of the two parameters R, C.
When the electric heating load in the electric heating aggregate after parameter homogenization is different from the initial state and the other parameters are equal, the aggregation model is expressed as
P (t) is the aggregate power of n electric heating loads at t time, P i Rated power for the ith electric heating equipment; k (K) i t Indicating the start-stop state of the ith electric heating load at the moment T set The operation set temperature value of the electric heating equipment is represented, delta is the width of a human body thermal comfort temperature interval; t (T) out Is an outdoor temperature value; t (T) in Is an indoor temperature value; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; η is the heat conversion efficiency of the electric heating equipment, and P is the electric power of the electric heating equipment; k (K) t For the start-stop state of the electric heating equipment at the time t, a value of 1 indicates that the equipment is in an on state, and a value of 0 indicates that the equipment is in an off state; t is the simulation time, Δt is the simulation time step.
The specific implementation of the step 3 comprises the following steps:
step 3: comprehensive control strategy for electric heating load
The control strategies for the electric heating load are generally divided into start-stop control, temperature control and periodic pause control. The patent relates to an electric heating device for start-stop control, which directly operates a control strategy of an electric heating load through a switch of the electric heating device, so that the large oscillation of the electric heating load power in a recovery process is reduced to a certain extent, a decision variable of the start-stop control of the electric heating load is in a state of the switch, and various start-stop optimization combination control can be performed through various objective functions and related constraint conditions.
The following 2 aspects are considered in formulating an electric heating load comprehensive control strategy:
(1) The heating load meets the temperature range of human body thermal comfort;
(2) The power complementation of the flexible heating load and the distributed photovoltaic is realized;
fig. 4 is a general schematic diagram of an electric heating load participating in demand response. When the control is carried out, initial conditions such as electric heating power, building indoor temperature and the like are given at first, and a dispatching center determines a dispatching target of a certain period according to the collected distributed photovoltaic power signals and the real-time electric heating load power signals and transmits indexes to an electric heating polymer; the electric heating aggregate receiving the instruction adjusts the self load by changing the indoor temperature set value, starting and stopping, periodically suspending and other control modes. After the requirement of the dispatching instruction is met, the updated indoor temperature and load information of the standard user electric heating load are returned to the load aggregator, and the load aggregator returns to the power system dispatching center.
The relay type control strategy mainly considers two situations: one is that the loads with the current regulation capability but the regulation duration does not meet the requirement are matched with each other, and the other is that the loads with the current regulation capability but the regulation duration does not meet the requirement are matched with the loads without the current regulation capability. The two cases will be specifically described by taking the up-regulation load as an example, and the equipment operation temperature interval is set to be 18 ℃ and 22 ℃ on the assumption that the load power involved in regulation is equal.
The first case is shown in fig. 5: at 2599s, the regulation time for issuing the up-regulation instruction to require the load is 15min, namely at least 15min is required for the current switching of the electric heating load from the off state to the on state. At this time, the electric heating of the No. 1 and the electric heating of the No. 2 are in the off state and have the up-regulating capability, but the adjustable duration of the two is not satisfied, so that the dispatching cannot be participated in under normal conditions. When relay control is adopted, 2599s time, the adjustable time length of 1# electric heating is 5min38s, and the state is switched to the open state. At 2937s, the indoor temperature of the 1# electric heating reaches the maximum value, and the state is turned into a shutdown state. At this time, the adjustable time length of the 2# electric heating is prolonged to 12min48s, and the state is changed into an open state. At 3715s, the indoor temperature of the electric heating system 2# reaches the maximum value, and the system is turned into a shutdown state. After relay control, the starting time of the 1# and 2# electric heating loads is 18min26s in total, so that the scheduling requirement is met.
The second case is shown in fig. 6: at 2770s, the regulation time for issuing the up-regulation instruction to require the load is 25min, namely, at least 25min is required for switching the electric heating load from the off state to the on state. At this time, the 1# electric heating is in a shutdown state and has the up-regulation capability, but the adjustable duration is only 11min and 14s, so that the dispatching cannot be participated in under normal conditions. The electric heating load 2# is in an on state at the moment and does not have the up-regulation capability. When relay type control is adopted, the 1# electric heating can be firstly turned into an on state at 2770 s. At 3444s, the indoor temperature of the 1# electric heating reaches the maximum value, and the state is turned into the off state. At this time, the electric heating of the No. 2 is in a shutdown state, has the capability of up-regulating, and the regulating and controlling duration is 16min22s, and is changed into an on state. At 4426s, the indoor temperature of the electric heating system 2# reaches the maximum value, and the system is turned into a shutdown state. After relay control, the starting time of the 1# and 2# electric heating loads is 27min36s in total, so that the scheduling requirement is met.
In order to verify the effect of the proposed relay control strategy on improving the adjustable capacity of the electric heating load group, the following simulation calculation examples are set, and specific simulation conditions are as follows:
(1) The electric heating load group contains user information as shown in table 1, and the electric heating load aggregate contains 300 users in total.
TABLE 1 user information
(2) Electric heating equipment operation settlement temperature: the operation set temperature of the electric heating load is set to be randomly selected within the range of [19.5 ℃ and 20.5 ℃, so that the difference of the requirements of different users on the thermal comfort degree is reflected.
When the simulation starts, the initial indoor temperature is randomly selected within 18 ℃ and 22 ℃, and the initial load start-stop state is randomly selected as "on" or "off".
And verifying the improvement effect of the relay control strategy on the electric heating load group regulation capacity under a plurality of time scales. At this time, the outdoor temperature T out The control time of 5min to 20min was set at =0deg.C, and the adjustment capacity of the electric heating load group was evaluated by using the conventional control method and the "relay" control method, and the obtained results are shown below.
TABLE 2 Multi-timescale Relay Up-Capacity Regulation before and after
TABLE 3 Multi-timescale Relay capacity Down-Regulation before and after
Analysis of the above results revealed that: as the regulation time is continuously increased, the lifting amount and the lifting proportion of the regulation capacity of the load group by the relay type control strategy are also continuously increased. The reason for this is that as the control time increases, the load that would normally be fully satisfactory gradually decreases, and the advantages of the "relay" control strategy become more apparent. The more the electric heating load aggregate is fully excavated, the better the effect of the electric heating load aggregate in participating in photovoltaic unit power fluctuation stabilization and in light extinction is achieved, the more complex dispatching targets can be met, the number of the influenced electric heating loads is effectively reduced, and the dispatching economic cost is reduced.
The specific embodiments described herein are offered by way of illustration only. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (10)
1. The source load cooperative control method for realizing the complementation of the photovoltaic and electric heating load power is characterized by comprising the following steps:
constructing a time-varying relation between heat supply quantity and indoor temperature change, constructing a thermal dynamic model according to thermodynamic characteristics of a standard building, and mapping a transient heat balance relation through an indoor temperature change rate; establishing the thermal comfort temperature of a human body in winter and restricting the change range of the indoor temperature; on the basis of the above, evaluating the adjustment capability of the single electric heating load of the start-stop control;
clustering electric heating loads according to rated power P, equivalent thermal resistance R and equivalent heat capacity C, and providing a relay type control strategy of an electric heating load group;
based on the established electric heating load aggregation model, the collected distributed photovoltaic power generation power and electric heating load power signals are used as feedback signals to carry out comprehensive optimization control on the electric heating load power.
2. The method for realizing complementary source load cooperative control of photovoltaic and electric heating load power according to claim 1, wherein the thermodynamic dynamic modeling of the standard building is based on the following formula
Wherein C is air ，ρ air Air specific heat capacity and air density respectively;and->The indoor temperature and the outdoor temperature at t are respectively, S is the external surface area of a standard user determined according to the building body shape coefficient, V is the space volume of the standard user determined according to the building body shape coefficient, P eh The heat supply power for electric heating is K is the comprehensive heat conductivity coefficient of the outer surface obtained according to the heat conductivity coefficient relation in the building energy-saving design standard, and the heat supply power is +.>Is the rate of change of the indoor temperature;
further neglecting the temperature difference between the indoor wall body and the outdoor wall body, the first-order ETP model of the electric heating load can be obtained by assuming that the indoor air temperature is the same as the solid temperature at the same time as follows:
t in out Is an outdoor temperature value; t (T) in Is an indoor temperature value; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; η is the heat conversion efficiency of the electric heating equipment, and P is the electric power of the electric heating equipment; k (K) t For the start-stop state of the electric heating equipment at the time t, a value of 1 indicates that the equipment is in an on state, and a value of 0 indicates that the equipment is in an off state; t isAt the simulation time, Δt is the simulation time step.
3. The method for realizing complementary power source load cooperative control of photovoltaic and electric heating load according to claim 1, wherein the method is characterized by comprising the following steps of PMV The calculation formula is as follows:
wherein M is the energy metabolism of human body, t s Is the temperature of human skin, t a Is the indoor ambient temperature, I c1 Is the thermal resistance of the clothing of the human body; when PMV is at [ -1,1]When the range is within the interval range, the thermal comfort level of the user to the environment is satisfied, and after the range is exceeded, the thermal comfort level of the user is poor; when the II-level comfort level is achieved according to the related content of PMV (permanent magnet synchronous motor) of 0.5-1 in the design specification of heating ventilation and air conditioning of civil buildings, the heating temperature interval is 18 ℃ and 22 DEG C]；
The range of variation of the indoor temperature is restrained by utilizing the thermal comfort temperature, and the method is specifically shown as the following formula:
wherein T is min Is the lower limit of the indoor temperature, T, set by the operation of the electric heating equipment max Is the upper limit of indoor temperature set by the operation of the electric heating equipment, and deltat is the simulation step length;
based on a first-order ETP model of the electric heating load, the control mode of the electric heating load related to the patent is start-stop control, so that the adjusting capacity of the electric heating load in the power dimension is fixed, namely, when the electric heating load is started, the power of the electric heating load is rated power, and when the electric heating load is stopped, the power of the electric heating load is zero; the adjustment duration of the single electric heating load is quantitatively analyzed, and the down adjustment duration tau of the electric heating load can be obtained off And the up-regulation time length tau on ：
T in out Is an outdoor temperature value; t (T) in Is an indoor temperature value; η is the heat conversion efficiency; p is the power of an electric heating load; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; t is the simulation time;
from the above formula, it can be further deduced that the theoretical initial indoor temperature is T max Maximum time tau for shutting down the electric heating load off_max And an initial indoor temperature of T min Maximum time τ of turn-on on_max ：
4. The method for realizing the source load cooperative control of complementation of photovoltaic and electric heating load power according to claim 1, wherein the electric heating groups are grouped according to rated power, and rated power in the groups is the same; firstly, the electric heating loads are initially divided into X groups according to the load power, and the load powers in the groups are approximately equal; after preliminary grouping, carrying out cluster analysis on the loads of the X groups according to the equivalent thermal resistance R and the equivalent heat capacity C, wherein each group forms Y load groups; finally, adopting the parameter value of the clustering center point of each load group as the equivalent thermal resistance R and the equivalent heat capacity C of the electric heating load in the group; the specific steps are as follows:
(1) After preliminary grouping, setting a matrix V as a parameter matrix containing equivalent thermal resistances R and equivalent heat capacities C of n electric heating loads of a certain electric heating load group, namely setting the matrix V as an n multiplied by 2 matrix; normalizing the elements in the matrix V, and recording the normalized matrix as V':
v in ij Is the original element in the matrix V, V' ij Is the element of matrix V after normalization processing, V imax Is the maximum of the j-th term in the set of parameters;
(2) Setting the aggregation group number Y of the electric heating load group and the threshold epsilon of iteration ending, randomly extracting Y samples in a matrix V' as initial values and giving the initial values to an aggregation center Z L (L＝1,2,…Y),Z L ＝(Z L1 ,Z L2 )；
(3) The equivalent thermal resistance R and the equivalent heat capacity C of the kth (k is more than or equal to 1 and less than or equal to n) load in the electric heating load group jointly form a parameter v' k ，v' k ＝[v' k1 ,v' k2 ]The Euclidean distance D to the center of each polymer is calculated according to the following formula kL
Wherein z' L1 ,z' L2 Respectively the parameter values of the current polymerization center point, v' k1 ,v' k2 The parameter values of the kth load respectively;
(4) Solving the membership M of the kth individual to the center point of the L-th polymer in the data matrix V' formed by R, C kL ；
D in ky The distance from the kth individual to the kth aggregation center point is the total number of clustering center points;
(5) The results obtained in the steps (3) and (4) are processedSubstituting into the following formula for the first electric heating polymer center X L Performing iterative updating;
m in the formula kL Membership of the kth individual to the center point of the L-th polymer in the data matrix V ', V' k Is a parameter formed by the equivalent thermal resistance R and the equivalent heat capacity C of the kth (k is more than or equal to 1 and less than or equal to n) load in the electric heating load group;
(6) According to steps (3) to (5), an objective function G (t) is determined as shown in the following formula
M in the formula kL Membership of kth individual to the center point of the L-th polymer in data matrix V', D kL Euclidean distance from kth individual to center of the L th polymer in data matrix V';
(7) Judging the convergence of G (t); setting the objective function of the previous iteration as G (t-1), if the difference between G (t) and G (t-1) is larger than epsilon, returning to the step (3) for continuing, if the difference between G (t) and G (t-1) is smaller than epsilon, ending the cluster grouping process, and using X L As the final polymerization center;
comparing the membership degree calculated in the step (4) with the samples V ' in the data matrix V ' formed by R, C ' k Membership degree M to individual Polymer Lk The electric heating loads are grouped according to the size of the electric heating load, and finally, an electric heating load homogeneous aggregation group with power close to that of the electric heating load and with the equivalent heat capacity and the equivalent thermal resistance similar to each other is formed.
5. The method for controlling the source load in a coordinated manner to achieve the complementary operation of distributed photovoltaic and flexible heating load power according to claim 1, wherein the electric heating load aggregation model is expressed as
P (t) is the aggregate power of n electric heating loads at t time, P i Rated power for the ith electric heating equipment;indicating the start-stop state of the ith electric heating load at the moment T set The operation set temperature value of the electric heating equipment is represented, delta is the width of a human body thermal comfort temperature interval; t (T) out Is an outdoor temperature value; t (T) in Is an indoor temperature value; r is the equivalent thermal resistance of the room; c is the equivalent heat capacity of the room; η is the heat conversion efficiency of the electric heating equipment, and P is the electric power of the electric heating equipment; k (K) t For the start-stop state of the electric heating equipment at the time t, a value of 1 indicates that the equipment is in an on state, and a value of 0 indicates that the equipment is in an off state; t is the simulation time, Δt is the simulation time step.
6. The method for realizing the source load cooperative control of complementation of photovoltaic and electric heating load power according to claim 1, wherein a relay type control strategy in an electric heating load group is provided based on an electric heating load group control mode of a homogenization aggregation model, and an electric heating load is increased/reduced by a power dispatching center, and the regulation duration is t control Is meeting the thermal comfort temperature constraintOn the premise of the above, the loads in the electric heating load group can be divided into two types with and without the adjusting capability, and the loads with the adjusting capability can be further divided into two types: one type is that the adjustable time length is greater than or equal to t control Another category is that the adjustable duration is less than t control Is a kind of device for the treatment of a cancer; when relay control is adopted, the adjustment potential of the electric heating load group can be fully excavated, the load which originally has the adjustment duration not meeting the requirement is brought into the dispatch, and the mutual coordination among the loads can realize that the adjustment time of the electric heating load group is t control Time modulated capacity boost ΔP control Electric quantity lifting delta W capable of being increased/reduced control 。
7. The method for realizing the source load cooperative control of the complementation of the photovoltaic and the electric heating load power according to claim 1, wherein the flow chart of the relay type control strategy specifically comprises the following steps:
firstly, setting the total number N of loads contained in an electric heating load group, load power P, equivalent thermal resistance R and equivalent heat capacity C of a user, and numbering the electric heating loads in the load group (i=1, 2 … …, N);
collecting indoor initial temperature and outdoor temperature data of each electric heating load, generating a time sequence of load operation by using the established electric heating load thermodynamic model, and evaluating the adjustment capability of the load, wherein the evaluation of the adjustment capability is still adjustable time because the load power in the load group can be regarded as approximately equal;
judging whether relay control is performed or not according to the scheduling requirement R and the individual load regulation capacity R, and if the load regulation capacity R is more than R, increasing the regulation capacity of the load group by P; for the load with the adjustment capacity R < R, the two relay modes can be mutually matched, so that the adjustment requirement is met, and the adjustable capacity of a load group is improved;
and (3) until the last electric heating load finishes the data acquisition and judging whether relay control flow, the control process is finished, and the adjustment capacity of the electric heating load group and the load information which can participate in the adjustment are output.
8. The method for realizing the source load cooperative control of the complementation of the photovoltaic and the electric heating load power according to claim 1, wherein when the method is used for comprehensive control, initial conditions such as the electric heating power, the indoor temperature of a building and the like are given, and a dispatching center determines a dispatching target of a certain period according to the collected distributed photovoltaic power signal and the real-time electric heating load power signal and transmits an index to an electric heating polymer; and the electric heating aggregate receiving the instruction adjusts the load by changing the start-stop state, and returns the updated indoor temperature and load information of the standard user electric heating load to the load aggregator after meeting the requirement of the dispatching instruction, and the load aggregator returns to the dispatching center of the power system.
9. A system, comprising:
a first module: the system is configured to be used for constructing a time-varying relation between heat supply quantity and indoor temperature change, establishing a thermodynamic model according to thermodynamic characteristics of a standard building, and mapping a transient heat balance relation through an indoor temperature change rate; establishing the thermal comfort temperature of a human body in winter and restricting the change range of the indoor temperature; on the basis of the above, evaluating the adjustment capability of the single electric heating load of the start-stop control;
a second module: the electric heating load group is configured to perform cluster processing on the electric heating load according to rated power P, equivalent thermal resistance R and equivalent heat capacity C, and a relay type control strategy of the electric heating load group is provided;
and a third module: the system is configured to perform comprehensive optimization control on the electric heating load power by taking the collected distributed photovoltaic power generation power and the electric heating load power signal as feedback signals based on the established electric heating load aggregation model.
10. A computer medium, characterized in that a computer program is stored, said program being capable of performing the method steps of any one of claims 1 to 8.
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