CN108151242B - Central air conditioner control method facing cluster demand response - Google Patents
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Abstract
The invention discloses a central air conditioner control method facing to cluster demand response, which comprises the following steps: modeling a load factor type central air conditioner mechanism; based on the given total response instruction, obtaining the optimal response instruction of each central air conditioner by utilizing a space search single-peak clipping algorithm; the cluster central air-conditioning load demand response control center combines the optimal response instruction, the central air-conditioning equipment switching state and the comprehensive index value to formulate an equipment-level comprehensive index priority queue control strategy, and after the controlled equipment group receives the comprehensive index priority queue control strategy, the equipment state is updated and fed back to the information collection unit. The invention designs and establishes a cluster demand response strategy framework by utilizing a comprehensive index priority queue algorithm and a space search single-peak clipping algorithm and taking a central air conditioner as a demand response resource, and provides auxiliary service for the control of a power system.
Description
Technical Field
The invention relates to the field of intelligent power grid technology and demand response, in particular to a central air conditioner control method facing to cluster demand response.
Background
In recent years, the load of users increases rapidly, and great influence is brought to the stable and economic operation of a power grid. The air conditioner load occupies a large proportion, and the reasonable regulation and control of the air conditioner load is beneficial to optimizing resource allocation and relieving the operation pressure of a power grid. Compared with a single air conditioner used by a common resident user, the central air conditioner used by a commercial user (such as a hotel, a market and the like) has better regulation and control performance and has great potential in the aspect of realizing peak clipping and valley filling of a power grid. A more effective implementation way is to use a Demand Response (DR) technology, that is, to adjust the power consumption mode of the user or to manage the power consumption load of the user. The incentive-based DR mainly means that a scheduling center makes a deterministic policy or a time-varying policy to encourage a user to reduce load in time when a system is too intense or power rates are too high.
The central Air conditioner belongs to an Air conditioning system (HVAC), and some intensive research has been made on modeling and control strategies for HVAC. Single unit load (such as single unit air conditioner, heat pump, etc.): the thermodynamic characteristics and parameter diversity of the load are considered by the model proposed by the existing research, and the model is applied to direct load control; and establishing a load model, and fully considering the electricity utilization behavior characteristics of the user on the basis of a physical model. The central air conditioner modeling and control strategy aspect is as follows: considering the energy consumption characteristic of the central air conditioner, a cooling water system model is established, and a corresponding PID regulator is designed; the PID controller of the neural network is applied to the regulation and control of the central air conditioner, so that the response precision and speed are improved; in consideration of special requirements of an air conditioning system on a ship, a group of air circulation systems are designed based on the characteristics of air flow movement of the air conditioning system, and energy is saved by 30% finally; a duty ratio control strategy is applied to the central air-conditioning host machine, so that demand response is realized; in the prior art, an energy consumption supervision system of a central air conditioner is constructed by combining fuzzy control and frequency conversion technology; a physical model-based method has been proposed in the prior art, and the air conditioning load per hour is aggregated to embody the electricity utilization characteristics of the population; a mathematical model of a host machine and a water pump system is established based on a water chilling unit performance curve, and energy-saving optimization is performed by applying a simulated annealing algorithm. In addition, in recent years, many advances have been made in the fields of demand response and electric power market research, which provide a theoretical basis for central air conditioning load to participate in demand response.
All the researches belong to the modeling and control of the central air conditioner from top to bottom, the regulation and control objects are mostly hosts or water circulation systems, the whole central air conditioner terminal users can be influenced by each regulation and control, the 'bottom to top' control means taking the terminal users as the regulation and control cores is less concerned, and the selectivity for the regulation and control of the users is lacked.
Disclosure of Invention
The invention provides a central air conditioner control method facing cluster demand response, which takes a central air conditioner as a demand response resource to provide auxiliary service for electric power system control, and is described in detail as follows:
a central air conditioner control method facing cluster demand response comprises the following steps:
modeling a load factor type central air conditioner mechanism;
based on the given total response instruction, obtaining the optimal response instruction of each central air conditioner by utilizing a space search single-peak clipping algorithm;
the cluster central air-conditioning load demand response control center combines the optimal response instruction, the central air-conditioning equipment switching state and the comprehensive index value to formulate an equipment-level comprehensive index priority queue control strategy, and after the controlled equipment group receives the comprehensive index priority queue control strategy, the equipment state is updated and fed back to the information collection unit.
The obtaining of the optimal response instruction of each central air conditioner by using a space search single-peak clipping algorithm based on the given total response instruction specifically comprises the following steps:
dividing the response target distribution result of each central air conditioner into a plurality of unimodal regions by using the running state of the central air conditioner and the optimization target; identifying and ranking regions most likely to contain an optimal solution; fitting a kriging model by using Latin square sampling in the most promising region, and identifying an optimal point;
moving to the next most promising region until all promising regions have been executed, the global optimal response instruction may be finalized by comparing all local optima.
Further, the comprehensive index value is specifically:
wherein, Ii,tRepresenting the composite index of the ith equipment at the time t. The indicator is determined by a number of factors, including: historical switching frequency index of ith equipment at time t
Index of indoor temperature
User intention index
Electricity price index
λHSNIs an index coefficient of historical switching times, lambdaTEMIs an index coefficient of indoor temperature, lambdaWFIndex coefficient of user's will, lambdaPFIs the electricity price index coefficient. When the influence of an index is considered, the coefficient of the index takes 1, otherwise, the coefficient takes 0.
The comprehensive index and the user intention have positive correlation, and when the user intention is higher, the user intention index value is increased to reflect the user requirement; on the contrary, the comprehensive index and the historical switching times of the equipment have a negative correlation relationship, the service life of the equipment is prolonged, and the switching times of the equipment are limited within a reasonable range.
Further, the method adds an index coefficient of the number of times of switching the device
Reflecting the influence of the switching times, wherein the more the equipment switching times are, the smaller the index coefficient of the equipment switching times is;
the comprehensive index and the electricity price index have a negative correlation relationship, and an index coefficient is obtained by adding the switching times of the equipment
To reflect the effect of the switching times.
Further, the device-level comprehensive index priority queue control strategy specifically includes:
and sequencing the central air-conditioning terminal equipment based on the comprehensive indexes according to the numerical value of the response signal, accurately screening the equipment to be regulated by a stacking method until the requirement of the response signal is met, and changing the on-off state of the terminal equipment to be regulated.
The technical scheme provided by the invention has the beneficial effects that:
1. the invention constructs a mathematical model of a load factor type central air conditioner based on the thermodynamic dynamic characteristics of the central air conditioner and the electric-thermal coupling relationship thereof;
2. the invention constructs a comprehensive index priority queue algorithm, provides an accurate equipment optimization screening method for the central air conditioner to participate in demand response on the premise of considering various influence factors, and ensures that the regulated and controlled equipment is the most suitable object in the current equipment group;
3. the invention designs and establishes a cluster demand response strategy framework by utilizing a space search single-peak clipping algorithm and taking a central air conditioner as a demand response resource, provides help for peak clipping and valley filling of an electric power system and provides auxiliary service for control of the electric power system.
Drawings
Fig. 1 is a flowchart of a central air conditioner control method oriented to cluster demand response;
FIG. 2 is a diagram illustrating the operation mechanism and structure of the central air conditioner according to the present invention;
FIG. 3 is a schematic diagram of the indoor temperature variation of the house provided by the present invention;
FIG. 4 is a flow chart of a spatial search unimodal clipping algorithm provided by the present invention;
FIG. 5 is a schematic diagram of the temperature index variation provided by the present invention;
FIG. 6 is a schematic diagram of the effect of demand response considering only temperature indicators according to the present invention;
FIG. 7 is a schematic diagram of the effect of demand response considering only the price of electricity;
FIG. 8 is a schematic diagram of a demand response effect considering only historical switch frequency indicators according to the present invention;
FIG. 9 is a schematic diagram of the effect of demand response considering temperature and electricity price indicators provided by the present invention;
FIG. 10 is a schematic diagram of the effect of demand response considering temperature and historical switching times provided by the present invention;
fig. 11 is a schematic diagram of a demand response effect considering temperature, electricity price, and historical switching frequency indexes according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
The central air conditioner demand response control strategy provided by the embodiment of the invention is a 'bottom-up' control method, and is characterized in that a central air conditioner group is screened according to the running state of equipment by integrating an index priority queue algorithm and a space search single-peak clipping algorithm, the optimal control target of the central air conditioner group is calculated by considering multi-constraint conditions such as electricity price constraint, running cost constraint, comfort constraint, given target and the like, and a control instruction is issued to provide service for stabilizing fluctuation of a power system and complete various auxiliary service functions.
Example 1
A central air-conditioning control method facing cluster demand response, referring to fig. 1 and 2, the central air-conditioning control method comprising the steps of:
101: modeling a load factor type central air conditioner mechanism;
102: based on the given total response instruction, obtaining the optimal response instruction of each central air conditioner by utilizing a space search single-peak clipping algorithm;
103: the cluster central air-conditioning load demand response control center combines the optimal response instruction, the central air-conditioning equipment switching state and the comprehensive index value to formulate an equipment-level comprehensive index priority queue control strategy, and after the controlled equipment group receives the comprehensive index priority queue control strategy, the equipment state is updated and fed back to the information collection unit.
The comprehensive index and the user intention have positive correlation, and when the user intention is higher, the user intention index value is increased to reflect the user requirement; on the contrary, the number of the first and second electrodes,
the negative correlation exists between the comprehensive index and the historical switching times of the equipment, the service life of the equipment is prolonged, and the switching times of the equipment is limited within a reasonable range.
Further, the method adds the index coefficient of the switching times of the equipment
Reflecting the influence of the switching times, wherein the more the equipment switching times are, the smaller the index coefficient of the equipment switching times is;
the comprehensive index and the electricity price index have a negative correlation relationship, and an index coefficient is obtained by adding the switching times of the equipment
To reflect the effect of the switching times.
Further, the device-level comprehensive index priority queue control strategy specifically includes:
and sequencing the central air-conditioning terminal equipment based on the comprehensive indexes according to the numerical value of the response signal, accurately screening the equipment to be regulated by a stacking method until the requirement of the response signal is met, and changing the on-off state of the terminal equipment to be regulated.
In summary, in the embodiments of the present invention, a comprehensive indicator priority queue algorithm and a space search single-peak clipping algorithm are used, a central air conditioner is used as a demand response resource, a cluster demand response strategy architecture is designed and established, and an auxiliary service is provided for power system control.
Example 2
The scheme in embodiment 1 is further described below with reference to specific calculation formulas, examples, and fig. 2 to 5, and is described in detail below:
201: modeling the mechanism of the load rate type central air conditioner;
the key components of the load factor type central air conditioning unit comprise: the three parts of the host, the water circulation system and the terminal group device are specifically formed as shown in figure 2.
The quantitative circulating water is frozen by the central air-conditioning host, and the water separator sends cold water to the air-conditioning terminal equipment and the air processing unit. The air handling unit improves the comfort level of the user by adjusting the circulating air, and the air conditioning terminal equipment directly sends cold air to the terminal user. After passing through the two devices, the water temperature will rise, and the water collector sends the high-temperature water to the central air-conditioning main unit as a heat exchange resource. The water flows through the insulated cooling tower, preventing the waste heat from diffusing into the surrounding air and thereby reducing power losses.
the central air-conditioning host and the water circulation system occupy about 90% of the power consumption of the whole central air-conditioning, the load rate η is an important control parameter of the load rate type central air-conditioning, and the value of the load rate η is equal to the ratio of the actual refrigerating area of the air-conditioning to the total refrigerating area:
in the formula, QmaxThe maximum value of the air-conditioning cooling capacity is shown, Q is the current air-conditioning cooling capacity, SonArea of the house opened for air-conditioning terminal, StotalThe total area of the house where all the terminals are located.
Load factor type central air conditioner main unit and water circulation system energy consumption PmAnd PcCan be written as a function of the load rate:
therefore, the total power consumption P of the central air conditionertotalExpressed as the sum of the energy consumptions of the parts:
Ptotal＝Pm+Pc+Pother＝f(η)＝g(Son) (3)
in the formula, Potherrepresenting the power consumption of other parts such as terminal equipment, f (η) is the functional relation between the load factor and the total power consumption, g (S)on) As a function of the cooling area and the total power consumed.
As can be seen from the expressions (1) to (3), the power consumption P of the single-unit central air conditionertotalThe load factor is calculated through the load factor, and the relationship between the load factor and the load factor can be described in an exponential function form.
further, the sum of the terminal cooling areas of a plurality of terminal users of a single central air conditioner determines the magnitude of the load rate η of the central air conditioner.
End user's indoor temperature audience multi-factor influence includes: switching state and initial temperature T of terminal equipmentoTemperature set value TsetAnd upper and lower limits Thigh、TlowOutdoor temperature, wall material, etc. When a certain end user is not controlled, the indoor temperature change curve is shown in fig. 3.
At any time, there are 2 central air-conditioning terminal groups, an on group and an off group, for any single central air-conditioner, represented by the following formula:
where t is the simulation time, OtAnd CtIs an open group and a close group at time t, the corresponding number of terminals is n1And n2. The total number of terminals is n ═ n1+n2. Over time, n1And n2But also with the operational state of the terminal. General central air-conditioning terminal group AtCan be defined by the following formula:
202: based on a given total response instruction, obtaining an optimal response instruction of each central air conditioner by using a space search single-peak clipping algorithm, wherein a flow chart of the algorithm is shown in fig. 4, and the specific steps are as follows:
1) dividing the response target distribution result of each central air conditioner into a plurality of unimodal regions by using the running state of the central air conditioner and the optimization target;
2) identifying and ranking regions most likely to contain an optimal solution;
3) fitting a kriging model by using Latin square sampling in the most promising region, and identifying an optimal point;
4) move to the next most desirable area;
5) the search process is performed until all the promising regions have been performed, and global optimality can be finally determined by comparing all local optimality.
The above-mentioned spatial search single-peak clipping algorithm is well known to those skilled in the art, and is not described in detail in the embodiments of the present invention.
203: and the cluster central air-conditioning load demand response control center combines the calculated optimal response instruction with the central air-conditioning equipment on-off state and the comprehensive index value to formulate an equipment-level comprehensive index priority queue control strategy, and after receiving the instruction, the controlled equipment group updates the equipment state and feeds back the equipment state to the information collection unit.
In the original priority queue ordering method, only the current indoor temperature is arranged, and the comprehensiveness is lacked, so that in the embodiment of the invention, besides the indoor temperature factor, the influence of multiple aspects such as electricity price, equipment switching times, user wishes and the like is also considered, and a comprehensive index priority queue algorithm is provided.
The temperature index change is as shown in fig. 5, the controllable device groups are divided into an opening group and a closing group according to the on-off state of the central air conditioner, and in each group, the terminal devices are sorted according to the temperature index and move to the next state point in the clockwise direction.
In each group, the terminal equipment carries out temperature development according to thermodynamic characteristics of the single central air conditioner, and the temperature index of each equipment in the group is continuously reduced along with the time under the condition of no external control signal. This process can be considered as a constant in clockwise motion. When the temperature index value of the central air-conditioning equipment is reduced to zero, the switching state of the equipment is reversed in the next time step, and the equipment jumps to the head of another group.
Existence between the composite index and the user's intentionPositive correlation, when the user's intention is higher, by increasing the user's intention index value
To reflect such needs of the user. On the contrary, the comprehensive index and the historical switching times of the equipment have a negative correlation relationship, and in order to protect the terminal equipment and prolong the service life of the equipment, the switching times of the equipment are limited within a reasonable range.
The embodiment of the invention adds the index coefficient of the switching times of the equipment
The influence of the switching times is reflected, and the more the equipment switching times are, the smaller the index coefficient of the equipment switching times is.
The comprehensive index and the electricity price index have a negative correlation relationship, and the embodiment of the invention adds the index coefficient of the switching times of the equipment
To reflect the effect of the switching times.
For a single central air-conditioning terminal:
wherein, Ii,tRepresenting the composite index of the ith equipment at the time t. The indicator is determined by a number of factors, including: historical switching frequency index of ith equipment at time t
Index of indoor temperature
User intention index
Electricity price index
λHSNIs an index coefficient of historical switching times, lambdaTEMIs an index coefficient of indoor temperature, lambdaWFIndex coefficient of user's will, lambdaPFIs the electricity price index coefficient.
In the comprehensive index priority queue algorithm, firstly, according to the numerical value of the response signal, the comprehensive index I is based oni,tAnd sequencing the central air-conditioning terminal equipment, accurately screening the equipment to be regulated by a stacking method until the requirement of a response signal is met, and changing the on-off state of the terminal equipment to be regulated.
In summary, the embodiment of the present invention constructs a cluster load model composed of central air conditioners based on thermodynamic dynamic characteristics of the central air conditioners and electrical-thermal coupling relationships thereof, and designs and establishes a demand response strategy architecture with the central air conditioners as demand response resources by using a comprehensive index priority queue algorithm and a space search single peak clipping algorithm, so as to provide auxiliary services for power system control.
Example 3
The feasibility verification of the solutions of examples 1 and 2 is carried out below with reference to fig. 6-11, as described in detail below:
fig. 6 to 11 reflect the demand response effect of the central air conditioner when different indexes and index combinations are considered, and it can be seen from the results that the effect is better when the control strategy of the temperature index is considered because the temperature index considers the coupling relationship between electricity and heat. Meanwhile, considering more indexes, the response effect is more restricted and worse, but considering the indexes protects the benefit of the user or the service life of the equipment from different aspects.
In the embodiment of the present invention, except for the specific description of the model of each device, the model of other devices is not limited, as long as the device can perform the above functions.
Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-described embodiments of the present invention are merely provided for description and do not represent the merits of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (1)
1. A central air-conditioning control method facing cluster demand response is characterized by comprising the following steps:
modeling a load factor type central air conditioner mechanism;
based on the given total response instruction, obtaining the optimal response instruction of each central air conditioner by utilizing a space search single-peak clipping algorithm;
the cluster central air-conditioning load demand response control center combines the optimal response instruction, the central air-conditioning equipment switching state and the comprehensive index value to formulate an equipment-level comprehensive index priority queue control strategy, and after the controlled equipment group receives the comprehensive index priority queue control strategy, the equipment state is updated and fed back to the information collection unit;
the obtaining of the optimal response instruction of each central air conditioner by using a space search single-peak clipping algorithm based on the given total response instruction specifically comprises the following steps:
dividing the response target distribution result of each central air conditioner into a plurality of unimodal regions by using the running state of the central air conditioner and the optimization target; identifying and ranking regions most likely to contain an optimal solution; fitting a kriging model by using Latin square sampling in the most promising region, and identifying an optimal point;
moving to the next most promising region until all promising regions have been executed, the global optimal response instruction may be finally determined by comparing all local optima;
the comprehensive index value is specifically as follows:
wherein, Ii,tRepresents a composite indicator of the ith plant at time t, the indicator being determined by a number of factors including: history opening of ith device at time tIndex of number of times of closure
Index of indoor temperature
User intention index
Electricity price index
λHSNIs an index coefficient of historical switching times, lambdaTEMIs an index coefficient of indoor temperature, lambdaWFIndex coefficient of user's will, lambdaPFIs the electricity price index coefficient; when the influence of a certain index is considered, the coefficient of the index is 1, otherwise, the coefficient is 0;
the comprehensive index value has positive correlation with the user intention, and when the user intention is higher, the user intention index value is increased to reflect the user requirement; on the contrary, the number of the first and second electrodes,
the comprehensive index value and the historical switching times of the equipment have a negative correlation relationship, so that the service life of the equipment is prolonged, and the switching times of the equipment are limited within a reasonable range;
the method adds an index coefficient of the switching times of the equipment
Reflecting the influence of the switching times, wherein the more the equipment switching times are, the smaller the index coefficient of the equipment switching times is;
the comprehensive index value and the electricity price index have a negative correlation relationship, and an index coefficient is obtained by adding an equipment switching frequency index
To reflect the influence of the switching times;
the equipment-level comprehensive index priority queue control strategy specifically comprises the following steps:
sequencing the central air-conditioning terminal equipment based on the comprehensive indexes according to the numerical value of the response signal;
and screening the equipment needing to be regulated by a stacking method until the requirement of the response signal is met.
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| CN112865113B (en) * | 2021-01-21 | 2023-05-26 | 华中科技大学 | Direct load control method and system for aggregate air conditioner demand response |
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