CN108258679B - Electric-thermal comprehensive energy system optimization scheduling method considering heat storage characteristics of heat supply network - Google Patents

Electric-thermal comprehensive energy system optimization scheduling method considering heat storage characteristics of heat supply network Download PDF

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CN108258679B
CN108258679B CN201711419432.6A CN201711419432A CN108258679B CN 108258679 B CN108258679 B CN 108258679B CN 201711419432 A CN201711419432 A CN 201711419432A CN 108258679 B CN108258679 B CN 108258679B
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CN108258679A (en
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陈飞
郑伟民
王蕾
孙可
刘家齐
潘弘
戴攀
黄晶晶
张利军
胡哲晟
刘瞾煜
赵玉勇
张平
袁翔
张西竹
王坤
张曼颖
朱超
邹波
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Zhejiang University ZJU
State Grid Zhejiang Electric Power Co Ltd
Jiaxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Zhejiang Electric Power Co Ltd
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Zhejiang University ZJU
State Grid Zhejiang Electric Power Co Ltd
Jiaxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Zhejiang Electric Power Co Ltd
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Abstract

The invention discloses an optimized dispatching method of an electric-heat comprehensive energy system considering heat storage characteristics of a heat supply network. The renewable energy consumption level is synergistically improved by utilizing a source, a network and a load, and electricity is fixed by heat through decoupling of electric heating equipment at the source side; on the load side, the response capability of the demand side is flexibly enhanced by utilizing the thermal load; on the network side, the power network has the characteristics of easiness in transmission and difficulty in storage, the thermal network has the characteristics of easiness in storage and difficulty in transmission, the heat supply network has the natural heat storage characteristic due to the time delay from a heat source to heat supply of a user, a refined heat supply network model considering the thermal dynamic characteristics of the heat supply network such as heat supply time delay and heat supply loss is established according to the physical structure of the thermal system, the renewable energy consumption level is improved by utilizing the complementary characteristics of the power system and the thermal system, and the adjustment flexibility of the system is enhanced. The method can effectively solve the problem of new energy consumption caused by large-scale centralized grid connection.

Description

Electric-thermal comprehensive energy system optimization scheduling method considering heat storage characteristics of heat supply network
Technical Field
The invention relates to the field of optimized dispatching of an electric-thermal integrated energy system, in particular to an optimized dispatching method of an electric-thermal integrated energy system considering heat storage characteristics of a heat supply network.
Background
At present, the installed capacities of wind power generation and photovoltaic power generation in China are the first in the world, but aeipathia diseases such as wind abandonment and light abandonment which are transversely long before the development of renewable energy sources cannot be solved well all the time. Statistical data of the national energy agency show that the national wind electricity abandonment amount reaches 497 hundred million kWh in 2016, the wind abandonment rate of part of regions exceeds 40%, western regions are important regions for development of photovoltaic power stations in China, the installed capacity of the photovoltaic power stations is still rapidly increased, and the average light abandonment rate reaches 20%. In order to improve the consumption rate of renewable energy, researchers at home and abroad propose various methods, including configuration of energy storage, demand side response, virtual power plants and the like. The measures effectively solve the randomness, fluctuation and intermittence of the power generation of the renewable energy sources, but at present, the wind and light abandon is serious in many areas with enriched renewable energy sources, and the measures are mainly related to factors such as insufficient peak regulation capacity, the use of heat for electricity determination, mismatch of installed capacity of local renewable energy sources and power demand, asynchronization of power supply construction and power grid construction, limitation of outgoing transmission and transmission channels and the like.
On the premise of no external transfer industry, the regional renewable energy consumption capability is difficult to obviously change in a short period, and the national energy agency proposes to expand energy terminal consumption, increase electric energy substitution, fully excavate the electric energy consumption potential of renewable energy enrichment regions, for example, clean heating by using night wind power in winter to replace a coal-fired boiler, and the like. Solving the problem of renewable energy consumption requires source, network and load three-party cooperation: on the source side, the electrical heating device can be decoupled to some extent to thermally fix the electricity; on the load side, the heat load increases the renewable energy consumption space, and meanwhile, because of the fuzziness of the requirement of a user on the room temperature, the room temperature fluctuating in a certain range does not influence the comfort level, and the heat load is more flexible than the electric load; on the network side, the heat supply network provides a transmission channel for the renewable energy power generation limited by the transmission capacity, on the other hand, the power system has the characteristics of easiness in transmission and difficulty in storage, the thermal system has the characteristics of easiness in storage and difficulty in transmission, the time delay from a heat source to user heat supply enables the heat supply network to have the natural heat storage characteristic, and the complementary characteristic of the power system and the thermal system is strong. Therefore, the complementation of electricity and heat in the electricity-heat comprehensive energy system is an important way for exploiting the consumption capability of renewable energy sources, but most of the research on the cogeneration at present does not fully consider the complementary characteristics of the electricity and the heat. On the other hand, in the research of the current electric-thermal comprehensive energy system, the modeling mode of the heat supply network is simpler, most researches only consider the heat transmission process under the steady-state operation working condition of the heat supply network, but do not consider the influence of heat supply delay, and the heat storage capacity of the heat supply pipeline is not reflected.
Therefore, modeling of the thermal dynamic characteristics of the heat supply pipeline is very necessary, and the problem of utilizing the heat storage characteristics of the heat supply network and the mutual coordination and decoupling of the source, the network and the load in the electric-thermal comprehensive energy system to fix the electricity by heat so as to promote the consumption of renewable energy sources is worthy of attention.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an electric-thermal comprehensive energy system scheduling method considering the heat storage characteristics of a heat supply network, so as to effectively reduce the rigid coupling relationship between heat and electricity and increase the consumption of renewable energy.
The technical scheme adopted by the invention is as follows: an electric-thermal comprehensive energy system optimal scheduling method considering heat storage characteristics of a heat supply network comprises the following steps:
1) dynamic modeling of a thermodynamic system, which comprises modeling of heat source and heat exchange station nodes, heat supply pipeline node mass flow continuity, node temperature mixing and heat supply pipeline water temperature dynamic characteristics;
2) establishing an electric-thermal comprehensive energy system optimization scheduling model considering heat storage characteristics of a heat supply network through mutual coordination of sources, networks and loads in the electric-thermal comprehensive energy system; on the source side, the electric heating equipment is used for decoupling to fix the power by heat; on the load side, the response capability of the demand side is flexibly enhanced by utilizing the thermal load; on the network side, the complementary characteristics of the electric power system and the thermodynamic system are utilized to improve the consumption level of renewable energy sources and enhance the adjustment flexibility of the system.
In addition to the above method, in step 1), the nodes of the heat source and the heat exchange station are modeled as follows:
heat source node:
Figure BDA0001522741860000031
heat exchange station nodes, i.e. heat load nodes:
Figure BDA0001522741860000032
allowing value T of water supply temperature and water return temperature to be influenced by pipeline temperature simultaneouslyg,min、Tg,maxAnd (3) limiting:
Figure BDA0001522741860000033
Figure BDA0001522741860000034
in the formula:
Figure BDA0001522741860000035
respectively providing heat for the heat source node and consuming heat for the heat load node; c is the specific heat capacity of water;
Figure BDA0001522741860000036
hot water mass flow at the heat source node and the heat load node, respectively;
Figure BDA0001522741860000037
respectively representing the water supply temperature and the water return temperature at the node;
due to user's perception of temperature comfortWith some ambiguity to ensure user comfort, assume that the flexible regulation of the thermal load is such that the amount of heat absorbed by the load node i during time t ① is satisfied
Figure BDA0001522741860000038
In that
Figure BDA0001522741860000039
Figure BDA00015227418600000310
② T' time periods, the total heat consumed by the heat exchange station and the optimal heating demand of the user
Figure BDA00015227418600000311
The total amounts are equal, i.e.:
Figure BDA00015227418600000312
Figure BDA00015227418600000313
the larger T 'is, the larger the time scale for adjusting the heating demand can be, and T' is 1, namely, the heating is strictly according to the optimal demand of the user;
in addition to the above method, in step 1), the heat supply pipeline node mass flow continuity modeling is as follows:
node mass flow continuity, i.e. the inflow mass flow of hot water to each node is equal to the outflow;
Figure BDA0001522741860000041
in the formula:
Figure BDA0001522741860000042
respectively a set of starting/ending pipelines connected with and starting from the node i;
Figure BDA0001522741860000043
for the hot water mass flow in pipe j for time period t,
Figure BDA0001522741860000044
is the hot water mass flow in the pipe k for a period t.
In addition to the above method, in step 1), the node temperature mixture is modeled as follows:
the node temperature mixing means that hot water with different temperatures flows to the same node from different pipelines and then is mixed, the temperature of the hot water flowing into different pipelines from the same node after mixing is the same, and ideal mixing temperature is as follows:
Figure BDA0001522741860000045
in the formula:
Figure BDA0001522741860000046
the outlet temperature of the hot water in the pipeline j is a time period t;
Figure BDA0001522741860000047
the hot water inlet temperature in the pipe k is a time period t.
In addition to the above method, in step 1), the heat supply pipeline water temperature dynamic characteristic is modeled as follows:
the dynamic water temperature characteristic of the heat supply pipeline refers to the coupling relation between the inlet temperature and the outlet temperature of hot water in the same pipeline and the time of the inlet temperature and the outlet temperature, and is the key for describing the heat storage characteristic of a heat supply network; in the pipeline, the temperature change at the inlet is slowly expanded to the outlet, and the time delay of temperature transmission is basically consistent with the time of hot water flowing through the pipeline; in addition, due to the difference between the temperature of the hot water in the pipeline and the ambient temperature, heat loss is generated during flowing to cause the temperature of the water to drop;
Figure BDA0001522741860000048
Figure BDA0001522741860000049
Figure BDA00015227418600000410
in the formula (I), the compound is shown in the specification,
Figure BDA00015227418600000411
is a time period t-tauj，tHot water inlet temperature in conduit j;
the above equation can be approximated as:
Figure BDA0001522741860000051
in the formula: tau isj,tIs a delay time; t isa,tThe ambient temperature at which the pipeline is located; lambda is the thermal conductivity of the pipe material; l isjIs the length of pipe j. In the usual case of the use of a magnetic tape,
Figure BDA0001522741860000052
therefore, can be neglected in
Figure BDA0001522741860000053
The case (1).
As a supplement to the above method, in step 2), the optimal scheduling model of the electric-thermal integrated energy system takes the lowest operation cost as an optimization target, the uncertainty of the output of the renewable energy is processed by a scene method, and in order to promote the consumption of the power generation of the renewable energy, the wind curtailment cost and the light curtailment cost are added to the total operation cost of the system, and the objective function is as follows:
Figure BDA0001522741860000054
Figure BDA0001522741860000055
Figure BDA0001522741860000056
in the formula:
Figure BDA0001522741860000057
planned output of a cogeneration unit i and a conventional unit i are respectively provided;
Figure BDA0001522741860000058
actual electric output and thermal output of the cogeneration unit i in a time period t under a scene s;
Figure BDA0001522741860000059
the actual output of the conventional unit i;
Figure BDA00015227418600000510
the electric power is used for the heat pump;
Figure BDA00015227418600000511
abandoning optical power for abandoning wind; rhopenIn actual operation, punitive price of unit output is adjusted temporarily, and the degree of the conventional unit and the cogeneration unit tending to output according to plan is reflected; c. Chpα is the cost coefficient of wind and light abandoning;
Figure BDA00015227418600000512
the running cost of the cogeneration unit is reduced;
Figure BDA0001522741860000061
the running cost of the conventional unit is reduced; p is a radical ofsFor scene probability, T is the scheduling period, NchpNumber of cogeneration units, NGThe number of the conventional units is the number of the conventional units;
Pi,tfor the electric power of the unit i during a time period t, Hi,tFor the heating power of the cogeneration unit i in the time period t, a0,i、a1,i、a2,i、a3,i、a4,i、a5,i、b0,i、b1,i、b2,iAre all parameters.
In addition to the above method, in step 2),
the constraint conditions of the optimization scheduling model of the electricity-heat comprehensive energy system comprise thermodynamic system constraint and electric power system constraint,
the power system and the thermodynamic system are coupled with each other through a cogeneration unit and a heat pump, and the cogeneration unit is supposed to operate in a constant heat-to-power ratio mode, and the constraint conditions are as follows:
Figure BDA0001522741860000062
Figure BDA0001522741860000063
Figure BDA0001522741860000064
in the formula, khp,iIs the thermoelectric ratio;
Figure BDA0001522741860000065
the upper limit and the lower limit of the unit output are respectively set;
Figure BDA0001522741860000066
maximum up-regulation power and maximum down-regulation power in unit time delta t of the unit are respectively;
heat pump power conversion from power consumption to heat power
Figure BDA0001522741860000067
Thermal output
Figure BDA0001522741860000068
Satisfies the following conditions:
Figure BDA0001522741860000069
Figure BDA00015227418600000610
Figure BDA00015227418600000611
in the formula (I), the compound is shown in the specification,
Figure BDA00015227418600000612
power consumption of the heat pump connected with wind power and photovoltaic respectively, η is the heat pump electric heat conversion coefficient;
Figure BDA00015227418600000613
the upper limit of the output of the heat pump; n is a radical ofW、NPVThe number of the wind power plants and the number of the photovoltaic power stations are respectively;
optical power is abandoned to system abandon wind
Figure BDA00015227418600000614
Comprises the following steps:
Figure BDA0001522741860000071
in the formula (I), the compound is shown in the specification,
Figure BDA0001522741860000072
wind power and photovoltaic power generation under the scene s respectively;
Figure BDA0001522741860000073
respectively connecting wind power and photovoltaic power into a power grid;
the upper and lower limit constraints and the climbing constraints of the output of the conventional unit are as follows:
Figure BDA0001522741860000074
power system power balance constraint:
Figure BDA0001522741860000075
in the formula: pL,tThe system electrical load is a time period t;
power flow constraint of the power system:
Figure BDA0001522741860000076
in the formula:
Figure BDA0001522741860000077
is the power flow of branch j in time period t;P line,j、
Figure BDA0001522741860000078
respectively, the lower limit and the upper limit of the branch j power flow.
The invention has the beneficial effects that:
the invention can break through the limitation of 'fixing the power by heat' operation mode by mutually coordinating the source, the network and the load in the electric-heat comprehensive energy system, realize the time translation and the optimized matching of the electricity and heat supply and demand curves, and obviously improve the consumption level of renewable energy.
The invention utilizes centralized heat supply to expand energy terminal consumption, relieves the effectiveness of the power grid operation pressure caused by the continuous improvement of the power generation permeability of renewable energy sources, provides a new method for solving the problem of new energy consumption caused by large-scale centralized grid connection, and is suitable for popularization in renewable energy enrichment areas.
Drawings
FIG. 1 is a diagram showing the basic structure of a thermodynamic system in the implementation steps of the method of the present invention.
FIG. 2 is a model diagram of heat source and load nodes of the thermodynamic system in the implementation step of the method of the present invention.
FIG. 3 is a cross-sectional view of a heat supply pipeline in an implementation step of the method of the present invention.
FIG. 4 is a diagram showing a basic structure of an electric-thermal integrated energy system in the implementation step of the method of the present invention.
Fig. 5 is a diagram of an electric-thermal integrated energy system composed of an IEEE39 node electric power system and a 26 node thermal power system in an application example of the method of the present invention.
FIG. 6 is a diagram illustrating the optimal scheduling result of the electric-thermal integrated energy system in the application example of the method of the present invention.
FIG. 7 is a comparison graph of the consumption of two wind farms in an application example of the method of the present invention.
FIG. 8 is a comparison graph of wind power consumption of the system under different heat pump capacities in an application example of the method of the present invention.
FIG. 9 is a daily payload plot for the Hill area in an example of an application of the method of the present invention.
FIG. 10 is a topological diagram of an electric-thermal integrated energy system in the Jianshan area of Haining in an application example of the method of the present invention.
Fig. 11 is a diagram showing an optimized scheduling result of the electricity-heat comprehensive energy system in the hill area in the application example of the method of the present invention.
FIG. 12 is a flow chart of the method of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and the embodiments.
The method of the present invention, as shown in fig. 12, comprises the following steps:
1) heat storage characteristic analysis and thermodynamic system dynamic modeling of a heat supply network, wherein the modeling comprises modeling of heat sources, heat exchange station nodes and heat supply pipelines;
2) and establishing an electric-heat comprehensive energy system optimization scheduling model considering heat storage characteristics of a heat supply network.
Step 1) heat storage characteristic analysis and thermodynamic system dynamic modeling of a heat supply network.
A typical thermodynamic system comprises a heat source, a heat supply network, a heat exchange station and a heat load. Like electric power systems, thermodynamic systems can be divided into transmission systems (primary pipe network) and distribution systems (secondary pipe network), as shown in fig. 1. The physical networks of the primary pipe network and the secondary pipe network are not communicated, and heat exchange is carried out through the heat exchange station. The heat exchange station is used as a heat load in the transport system and a heat source in the distribution system. Transmission systems are primarily considered herein. In the transmission system, heat transfer media convey heat from each heat source to each heat exchange station through a water supply pipe network, and then return to the heat source through a water return pipe network, and continuously circulate in the heat supply network.
The thermodynamic system and the electric system have certain structural similarity, so that each heat source, the heat exchange station and a pipeline connecting point can be regarded as a node, each pipeline is used as a branch, the flowing direction of water in the pipeline is defined as the direction of the branch, and the thermodynamic system is modeled by taking the electric system as reference.
A. Heat source and heat exchange station node model
The heat source node in the thermodynamic system includes a cogeneration unit, and electric heat conversion devices such as a heat pump and an electric boiler, and the heat exchange station is used as a load node, and the relationship between the supplied/absorbed heat and the water temperature change is shown in fig. 2.
The specific heat capacity c of the water is 4.2 kJ/(kg. DEG C), assuming that the heat source node i supplies heat in the time period t
Figure BDA0001522741860000091
The mass of the heat source flowing through is
Figure BDA0001522741860000092
From the return water temperature
Figure BDA0001522741860000093
Raising the temperature to the water supply temperature
Figure BDA0001522741860000094
Figure BDA0001522741860000095
Suppose that the load node (heat exchange station) i consumes heat during the period t
Figure BDA0001522741860000096
The mass of the flow-through heat exchange station is
Figure BDA0001522741860000097
The water temperature of the water supply
Figure BDA0001522741860000098
Reducing the temperature to the return water temperature
Figure BDA0001522741860000099
Figure BDA00015227418600000910
To ensure comfort for the user, it is assumed that the flexible regulation of the thermal load satisfies the heat absorbed at load node i during time t ①
Figure BDA00015227418600000911
Within a certain range
Figure BDA00015227418600000912
② T' time periods, the total heat consumed by the heat exchange station and the optimal heating demand of the user
Figure BDA00015227418600000913
The total amounts are equal, i.e.:
Figure BDA00015227418600000914
Figure BDA0001522741860000101
the larger T ', the larger the heating demand can be adjusted on a larger time scale, and T' 1 means heating strictly according to the most ideal demand of the user.
The water supply temperature and the water return temperature are limited by the allowable value of the pipeline temperature:
Figure BDA0001522741860000102
Figure BDA0001522741860000103
B. heat supply pipeline model
The operation condition of the heat supply pipeline can be described by a node mass flow continuity equation, a node temperature mixing equation and a heat supply pipeline water temperature dynamic characteristic equation.
① node Mass flow continuity, i.e., each node hot water inflow Mass flow equals outflow.
Figure BDA0001522741860000104
In the formula:
Figure BDA0001522741860000105
respectively a set of starting/ending pipelines connected with and starting from the node i;
Figure BDA0001522741860000106
is the hot water mass flow in pipe j for time period t.
② mixing the temperatures of the hot water at different temperatures flowing from different pipes to the same node, and mixing the hot water flowing from the same node to different pipes at the same temperature.
Figure BDA0001522741860000107
In the formula:
Figure BDA0001522741860000108
the outlet temperature of the hot water in the pipeline j is a time period t;
Figure BDA0001522741860000109
the hot water inlet temperature in the pipe k is a time period t.
③ Water temperature dynamic characteristics of heating pipe, referring to the coupling relationship between the inlet temperature and the outlet temperature of hot water in the same pipe and the time, which is the key for describing the heat storage characteristics of heating network, in the pipe, the change of the inlet water temperature will be extended to the outlet slowly, the temperature transmission delay is basically consistent with the time of hot water flowing through the pipe, besides, because the temperature of hot water in the pipe is different from the ambient temperature, heat loss will be generated during flowing to cause the water temperature to drop, the section of the heating pipe is shown in FIG. 3, where Δ t is the length of the scheduling period, the time delay and heat loss are calculated in two steps:
the first step is as follows: suppose the time required for the hot water in the pipe j to pass from the inlet to the outletIs tauj,tAnd no heat loss in the middle, then:
Figure BDA0001522741860000111
Figure BDA0001522741860000112
equation (9) shows that the outlet water temperature of the pipeline j at the time t is not considered when the heat loss of the pipeline is consumed
Figure BDA0001522741860000113
And inlet t-tj,tInstantaneous inlet water temperature
Figure BDA0001522741860000114
Equal; characteristic quantity F of pipe j in equation (10)jIs determined by the parameters of the length, the sectional area and the like of the pipeline.
The second step is that: and calculating the influence of heat loss in the transmission process.
Figure BDA0001522741860000115
The above equation can be approximated as:
Figure BDA0001522741860000116
in the formula: t isa,tThe ambient temperature at which the pipeline is located; lambda is the thermal conductivity of the pipe material; l isjIs the length of pipe j. In the usual case of the use of a magnetic tape,
Figure BDA0001522741860000117
therefore, can be omitted in formula (12)
Figure BDA0001522741860000118
The case (1).
Step 2) establishing an optimized dispatching model of the electric-heat comprehensive energy system considering heat storage characteristics of the heat supply network
A. Basic architecture of electricity-heat comprehensive energy system
The basic structure of the electricity-heat comprehensive energy system is shown in fig. 4, and mainly comprises units such as a conventional unit, a fan, a photovoltaic unit, a CHP unit, and an electric heating device, and the electric power and the thermodynamic systems are coupled through cogeneration, electric heating, and the like. The source side electric heating equipment can be decoupled to a certain extent to fix the power by heat; on the load side, the heat load increases the renewable energy consumption space; on the network side, the heat supply network provides a transmission channel for the renewable energy power generation limited by the transmission capacity, on the other hand, the power system has the characteristics of easiness in transmission and difficulty in storage, the thermal system has the characteristics of easiness in storage and difficulty in transmission, the time delay from a heat source to user heat supply enables the heat supply network to have the natural heat storage characteristic, and the complementary characteristic of the power system and the thermal system is strong.
B. Electricity-heat comprehensive energy system optimization scheduling model considering heat storage characteristics of heat supply network
The wind, light and other renewable energy sources have uncertainty in power generation, the scene analysis method can clearly describe probability characteristics of the uncertainty, and the optimization model is convenient to calculate, so that the method is widely used. Assuming S wind-solar output scenes, wherein the probability of the scene S is psT scheduling periods. The model takes the lowest operation cost as an optimization target, and adds the cost of wind abandoning and light abandoning into the total operation cost of the system to promote the consumption of renewable energy power generation, and the objective function is as follows:
Figure BDA0001522741860000121
Figure BDA0001522741860000122
Figure BDA0001522741860000123
the total cost formula (13) of the system operation comprises a cogeneration unit, the power generation cost and the temporary adjustment punishment cost of the conventional unit, the operation cost of the electric heating equipment, the wind curtailment cost and the light curtailment cost, wherein:
Figure BDA0001522741860000124
Figure BDA0001522741860000125
planned output of a cogeneration unit i and a conventional unit i are respectively provided;
Figure BDA0001522741860000126
actual electric output and thermal output of the cogeneration unit i in a time period t under a scene s;
Figure BDA0001522741860000127
the actual output of the conventional unit i;
Figure BDA0001522741860000128
the electric power is used for the heat pump;
Figure BDA0001522741860000129
abandoning optical power for abandoning wind; rhopenIn actual operation, punitive price of unit output is adjusted temporarily, and the degree of the conventional unit and the cogeneration unit tending to output according to plan is reflected; c. ChpThe heat pump operation cost coefficient, α the wind and light abandoning cost coefficient, and 14 the operation cost of the cogeneration unit
Figure BDA0001522741860000131
Formula (15) represents the running cost of the conventional unit
Figure BDA0001522741860000132
The power system and the thermodynamic system are coupled with the heat pump through a cogeneration unit. The cogeneration unit can be in a plurality of working states, and the cogeneration unit is supposed to operate in a constant heat-power ratio mode, and the constraint conditions are as follows:
Figure BDA0001522741860000133
Figure BDA0001522741860000134
Figure BDA0001522741860000135
formula (16) is a cogeneration unit i thermoelectric ratio constraint, where khp,iIs the thermoelectric ratio; the formula (17) is the constraint of the upper and lower limits of the unit output; formula (18) is a unit ramp constraint, wherein
Figure BDA0001522741860000136
The maximum up-regulation power and the down-regulation power in unit time of the unit are respectively.
Heat pump power conversion from power consumption to heat power
Figure BDA0001522741860000137
Thermal output
Figure BDA0001522741860000138
Satisfies the following conditions:
Figure BDA0001522741860000139
Figure BDA00015227418600001310
Figure BDA00015227418600001311
in the formula:
Figure BDA00015227418600001312
power consumption of the heat pump connected with wind power and photovoltaic respectively, η is the heat pump electric heat conversion coefficient;
Figure BDA00015227418600001313
is the upper limit of the output of the heat pump.
Optical power is abandoned to system abandon wind
Figure BDA00015227418600001314
Comprises the following steps:
Figure BDA00015227418600001315
in the formula:
Figure BDA0001522741860000141
wind power and photovoltaic power generation under the scene s respectively;
Figure BDA0001522741860000142
wind power and photovoltaic are respectively connected into power grid power.
The upper and lower limit constraints and the climbing constraints of the output of the conventional unit are as follows:
Figure BDA0001522741860000143
power system power balance constraint:
Figure BDA0001522741860000144
in the formula: pL,tThe system electrical load is time period t.
Power flow constraint of the power system:
Figure BDA0001522741860000145
in the formula:
Figure BDA0001522741860000146
is the power flow of branch j in time period t;P line,j、
Figure BDA0001522741860000147
respectively, the lower limit and the upper limit of the branch j power flow.
Thermodynamic system constraints are detailed in equations (1) - (12).
The application of the invention is as follows:
the application example data of the invention is based on an IEEE39 node power grid, a 26 node heat supply network coupling system and a Hingen Hill area power grid.
Simulation verification of A.IEEE39 node power grid and 26 node heat supply network coupling system
An IEEE39 node grid and 26 node heat supply network coupling system is shown in fig. 5, wherein the electro-thermal coupling device comprises: CHP1 at grid node 34/heat network node 1, CHP2 at grid node 36/heat network node 15, and two 200MW heat pumps at grid node 32, node 35. Other parameters such as the conventional unit parameters, the load curve, the predicted output of the wind power plant and the like of the system are shown in tables 1 to 3.
The result of the coupled system optimized scheduling is shown in fig. 6. As can be seen from fig. 6, the heat source heat supply of the thermodynamic system and the heat exchange station heat load are asynchronous. For example, after 20:00, the system electric load is decreased and the heat load is increased, wherein 1:00-6:00 are the lowest valley of the electric load and the highest peak of the heat load in the whole day. After 20:00, the output of the conventional unit is gradually reduced, the output of the CHP unit is basically stable, the surplus wind power is converted into heat energy through a heat pump and stored in a heat supply network, the heat energy entering the heat supply network is obviously smaller than the heat supply requirement during the period of 1:00-6:00, the heat energy stored in the heat supply network in advance is released to make up for the heat supply deficiency, the dependence of a thermodynamic system on the CHP unit is reduced, and a small amount of abandoned wind during the period is caused by the capacity limit of a power transmission line and the capacity limit of the heat pump; the heat energy entering the heat supply network at 7:00 is more than the heat supply demand, the redundant heat energy is stored in the heat supply network, the electric load of the system is increased after 8:00, more wind power is used for supplying power except that the conventional unit begins to climb the slope by outputting power, and the difference between the heat load supply and demand is compensated by the heat energy stored in the heat pipeline at the earlier stage. Because the heat energy generated by the heat source reaches each heat exchange station through the heat supply networks with different lengths, the instant time delay is different, and through the source, network and load coordination of the electric-heat comprehensive energy system, the on-site consumption of surplus wind power is realized, and the CHP set is prevented from fixing the power with heat. In addition, the difference between the total heat supply from the heat source and the total heat load demand in fig. 6(b) is the heat loss of the heat supply network itself, which accounts for about 2.5% of the heat load in the system.
FIG. 7 is a comparison of two wind farm consumptions in the system. It can be seen from the figure that the power grid is still the main channel for consuming wind power, and particularly in the period from 9:00 to 16:00, the system has higher electric load level, lower heat load and less available wind power in daytime, so that the power grid can fully consume the wind power; and after 20:00, the heat pump converts the surplus wind power into heat energy, and the heat energy is stored in a heat supply network in advance and used for supplying heat at night. 17:00 the heat pump electric-to-heat power is suddenly increased, and basic data analysis shows that the reason is that a peak appears in the available wind power in the period, and the heat pump absorbs most fluctuation quantity of the wind power through electric-to-heat conversion, so that punitive cost caused by frequent scheduling of a conventional unit and deviation of a CHP unit from planned output is avoided. As can be seen from fig. 7(a), the grid-connected electric quantity ratio of the wind farm 1 is greater than that of the wind farm 2, and the analysis shows that the wind farm 2 is more severely limited by the transmission capacity than the wind farm 1, and as can be seen from fig. 7(b), in the corresponding time period, more electric energy in the wind farm 2 is converted into heat energy by the heat pump, and obviously, when the grid-connected electric quantity of the wind farm is limited by the transmission capacity, the heat network provides another channel for energy transmission.
The power flow constraint of the power system, the wind power plant access position and the heat pump capacity all affect the wind power consumption condition, and fig. 8 shows the influence of the heat pump capacity configured in the wind power plant on the wind power consumption capacity of the system. The capacity of the heat pump is increased, the wind power consumption capacity of the system is continuously improved, the improvement effect is slowed down, when the heat pump reaches 300MW, the wind power is completely consumed, and if the initial investment cost of the heat pump is considered, the system has an optimal heat pump configuration capacity.
B. Simulation verification of Jianshan new area of Haining
The total area of the Hill new area is 42 square kilometers, and the Hill new area is formed by artificial reclamation, is a rising industrial new urban area, is dedicated to building an international advanced manufacturing center, and comprises a plurality of large enterprises such as a Haining automobile new energy project, a universal photovoltaic industrial park, a Jingke energy, a Mulberry solar energy and a Wanbao new energy. Due to a plurality of factors such as a policy of subsidy of renewable energy power generation, local photovoltaic panel capacity, demonstration area effect and the like, the installed capacity of new energy power generation in the hill new area is rapidly increased, and by 8 months in 2017, the installed total capacity of the connected photovoltaic power station in the hill area is 173MW, and the installed total capacity of a fan is 50MW, and the installed capacity is continuously increased. The high-permeability renewable energy power generation increases the operating pressure of the regional power distribution network, the renewable energy power generation output has the problem that the renewable energy power generation output cannot be absorbed on the spot, and the phenomenon of power transmission to the main network occurs in the load valley. Based on the daily load curve and the photovoltaic output data in the area of day 28 in 1 month in 2017, the net load change situation of the system after photovoltaic access with different permeability is analyzed, as shown in fig. 9. As can be seen from fig. 9, when the photovoltaic capacity is only 80% of the current installed capacity, the system has a net load less than 0, that is, the power is sent back. Aiming at the situation, the current measures to be taken in the Sharp mountain area comprise improving the power grid structure and utilizing the output of the power transfer of the distribution network by perfecting the transfer of the distribution network rack connection to the Anjiang river, constructing a flexible interconnection technology application demonstration project and an intelligent alternating current-direct current hybrid micro-grid technology application demonstration project. The measures can solve the problem that the installed capacity of renewable energy sources in the hill region is not matched with the electricity demand to a certain extent, and flexible and reliable loads and various loads of different types are introduced, so that the response capacity of the participation demand side can be improved; by coordinating the source-network-load-storage and transportation of various energy sources, the problem of local renewable energy consumption can be solved fundamentally.
In order to ensure safe and stable operation of a power grid in an area, the local consumption level of renewable energy power generation needs to be enhanced urgently. "Haining City central heating plan" was issued by Zhejiang province development and planning institute in 2016, and central heating was proposed in Haining City. In this context, the model presented herein is applied to the simulation analysis of the electric-thermal integrated energy system in the new mountainous area. The topological structure of the system is shown in the attached figure 10, and the installation scheme of the regional thermal power plant is 1 20MW cogeneration unit.
The result of the optimized dispatching of the area is shown in fig. 11 after considering the structure of the electric-thermal integrated energy system. Since the industrial load is taken as the main load in the hill area, the time period of 9:00-17:00 is the peak period of the heat load demand and is matched with the photovoltaic output curve, as can be seen from fig. 11, most of the photovoltaic output in the time period is converted into heat energy for heat supply of a heat network through coordinated dispatching of an electric-thermal integrated energy system, the risk of backward transmission of the power generated by the renewable energy is effectively reduced, the pressure on the operation of the power network caused by the continuous improvement of the power generation permeability of the renewable energy is relieved, meanwhile, the residual output of the renewable energy is fully utilized for heat supply, the capacity demand of a CHP unit and the output of the unit are reduced, and the energy conservation and emission reduction of a.
Table 1 generator set parameters of IEEE39 node power system in simulation verification
Node point Maximum generated power/(MW) Minimum generated power/(MW) Climbing (landslide) rate/(MW-min) Type of unit
30 250 50 35 Conventional unit
31 250 50 35 Conventional unit
33 450 100 80 Conventional unit
34 540 150 110 Cogeneration unit 1
36 540 150 110 Cogeneration unit 2
37 250 50 35 Conventional unit
38 450 100 80 Conventional unit
39 450 100 80 Conventional unit
TABLE 2 simulation verification of medium and thermal load, wind power and outdoor temperature data
Figure BDA0001522741860000181
Table 3 simulation verification shows the basic parameters of the electric-heat comprehensive energy system consisting of the IEEE39 node electric power system and the 26 node thermal power system
a0,1/(yuan) a1,1V (yuan/(kW h)) a2,1V (yuan/(kW h)) a3,1/(yuan/(kW. h)2) a4,1/(yuan/(kW. h)2) a5,1/((yuan/(kW. h)2)
1650 14.5 4.2 0.0345 0.03 0.031
a0,2/(yuan) a1,2V (yuan/(kW h)) a2,2V (yuan/(kW h)) a3,2/(yuan/(kW. h)2) a4,2/(yuan/(kW. h)2) a5,2/(yuan/(kW. h)2)
1250 36 0.6 0.0435 0.027 0.011
khp b0/(yuan) b1V (yuan/(kW h)) b2/(yuan/(kW. h)2) Tgmin/(℃) Tgmax/(℃)
2.62 2000 11.669 0.0533 55 100
Thmin/(℃) Thmax/(℃) ηwh α/(yuan/(kW h)) crbV (yuan/(kW h)) ρpenV (yuan/(kW h))
40 70 1 100 80 300
The foregoing detailed description is intended to illustrate and not limit the invention, which is intended to be within the spirit and scope of the appended claims, and any changes and modifications that fall within the true spirit and scope of the invention are intended to be covered by the following claims.

Claims (6)

1. An electric-thermal comprehensive energy system optimization scheduling method considering heat storage characteristics of a heat supply network is characterized by comprising the following steps:
1) dynamic modeling of a thermodynamic system, which comprises modeling of heat source and heat exchange station nodes, heat supply pipeline node mass flow continuity, node temperature mixing and heat supply pipeline water temperature dynamic characteristics;
2) establishing an electric-thermal comprehensive energy system optimization scheduling model considering heat storage characteristics of a heat supply network through mutual coordination of sources, networks and loads in the electric-thermal comprehensive energy system;
on the source side, the electric heating equipment is used for decoupling to fix the power by heat; on the load side, the response capability of the demand side is flexibly enhanced by utilizing the thermal load; on the network side, the complementary characteristics of the electric power system and the thermodynamic system are utilized to improve the consumption level of renewable energy sources and enhance the adjustment flexibility of the system;
in the step 1), the dynamic characteristic of the water temperature of the heat supply pipeline is modeled as follows:
the dynamic water temperature characteristic of the heat supply pipeline refers to the coupling relation between the inlet temperature and the outlet temperature of hot water in the same pipeline and the time of the inlet temperature and the outlet temperature, in the pipeline, the change of the water temperature at the inlet is slowly expanded to the outlet, and the time delay of temperature transmission is basically consistent with the time of hot water flowing through the pipeline; in addition, due to the difference between the temperature of the hot water in the pipeline and the ambient temperature, heat loss is generated during flowing to cause the temperature of the water to drop;
Figure FDA0002399679680000011
Figure FDA0002399679680000012
Figure FDA0002399679680000013
in the formula (I), the compound is shown in the specification,
Figure FDA0002399679680000014
is a time period t-tauj,tHot water inlet temperature in conduit j;
Figure FDA0002399679680000015
to account for the time taken for heat loss in the pipe, the hot water outlet temperature of pipe j at time t; fjThe characteristic quantity of the pipeline j is a characteristic parameter related to the length and the sectional area of the pipeline;
Figure FDA0002399679680000016
is the hot water mass flow in the pipeline j in the time period t;
the above equation is approximated as:
Figure FDA0002399679680000021
in the formula: tau isj,tIs a delay time; t isa,tThe ambient temperature at which the pipeline is located; lambda is the thermal conductivity of the pipe material; l isjIs the length of the pipe j; c is the specific heat capacity of water;
Figure FDA0002399679680000022
the hot water outlet temperature in the pipe j is the time period t.
2. The optimal scheduling method of the electric-thermal comprehensive energy system considering heat storage characteristics of the heat supply network as claimed in claim 1, wherein: in the step 1), the heat source and heat exchange station nodes are modeled as follows:
heat source node:
Figure FDA0002399679680000023
heat exchange stationNode, i.e. heat load node:
Figure FDA0002399679680000024
allowing value T of water supply temperature and water return temperature to be influenced by pipeline temperature simultaneouslymin、TmaxAnd (3) limiting:
Figure FDA0002399679680000025
Figure FDA0002399679680000026
in the formula:
Figure FDA0002399679680000027
respectively providing heat for the heat source node and the heat absorbed by the load node i in the time period t;
Figure FDA0002399679680000028
hot water mass flow at the heat source node and the heat load node, respectively;
Figure FDA0002399679680000029
respectively representing the water supply temperature and the water return temperature at the node; t isg,min、Tg,maxRespectively setting a lower limit and an upper limit of a temperature allowable value of a water supply pipeline; t ish,min、Th,maxRespectively setting the lower limit and the upper limit of a temperature allowable value of a water return pipeline;
to ensure the comfort of the user, it is assumed that the flexible regulation capacity of the thermal load is satisfied that the heat absorbed by the load node i is ① t
Figure FDA00023996796800000210
In that
Figure FDA00023996796800000211
② T' time periods, the total heat consumed by the heat exchange station and the optimal heating demand of the user
Figure FDA00023996796800000212
The total amounts are equal, i.e.:
Figure FDA00023996796800000213
Figure FDA00023996796800000214
Figure FDA00023996796800000215
respectively, an upper limit and a lower limit of the heat absorbed by the load node i at the time t.
3. The optimal scheduling method of the electric-thermal comprehensive energy system considering heat storage characteristics of the heat supply network as claimed in claim 2, wherein: in the step 1), the heat supply pipeline node mass flow continuity modeling is as follows:
node mass flow continuity, i.e. the inflow mass flow of hot water to each node is equal to the outflow;
Figure FDA0002399679680000031
in the formula:
Figure FDA0002399679680000032
respectively a set of starting/ending pipelines connected with and starting from the node i;
Figure FDA0002399679680000034
is the hot water mass flow in the pipe k for a period t.
4. The optimal scheduling method of the electric-thermal comprehensive energy system considering heat storage characteristics of the heat supply network as claimed in claim 3, wherein: in the step 1), the heat supply pipeline node temperature hybrid modeling is as follows:
the node temperature mixing means that hot water with different temperatures flows to the same node from different pipelines and then is mixed, the temperature of the hot water flowing into different pipelines from the same node after mixing is the same, and ideal mixing temperature is as follows:
Figure FDA0002399679680000035
in the formula:
Figure FDA0002399679680000037
the hot water inlet temperature in the pipe k is a time period t.
5. The optimal scheduling method of the electric-thermal comprehensive energy system considering heat storage characteristics of the heat supply network according to any one of claims 1 to 4, wherein: in the step 2) described above, the step of,
the electricity-heat comprehensive energy system optimization scheduling model takes the lowest operation cost as an optimization target, treats the uncertainty of the output of the renewable energy by a scene method, adds the wind abandoning cost and the light abandoning cost into the total operation cost of the system to promote the consumption of the power generation of the renewable energy, and has the following objective functions:
Figure FDA0002399679680000038
Figure FDA0002399679680000041
Figure FDA0002399679680000042
in the formula:
Figure FDA0002399679680000043
planned output of a cogeneration unit i and a conventional unit i are respectively provided;
Figure FDA0002399679680000044
actual electric output and thermal output of the cogeneration unit i in a time period t under a scene s;
Figure FDA0002399679680000045
the actual output of the conventional unit i;
Figure FDA0002399679680000046
the electric power is used for the heat pump;
Figure FDA0002399679680000047
abandoning optical power for abandoning wind; rhopenIn actual operation, punitive price of unit output is adjusted temporarily, and the degree of the conventional unit and the cogeneration unit tending to output according to plan is reflected; c. Chpα is the cost coefficient of wind and light abandoning;
Figure FDA0002399679680000048
the running cost of the cogeneration unit is reduced;
Figure FDA0002399679680000049
the running cost of the conventional unit is reduced; p is a radical ofsFor scene probability, T is the scheduling period, NchpNumber of cogeneration units, NGThe number of the conventional units is the number of the conventional units;
Pi,tfor the electric power of the unit i during a time period t, Hi,tFor the heating power of the cogeneration unit i in the time period t, a0,i、a1,i、a2,i、a3,i、a4,i、a5,i、b0,i、b1,i、b2,iAre all parameters.
6. The optimal scheduling method of the electric-thermal comprehensive energy system considering heat storage characteristics of the heat supply network according to claim 5, wherein the optimal scheduling method comprises the following steps: in the step 2) described above, the step of,
the constraint conditions of the optimization scheduling model of the electricity-heat comprehensive energy system comprise thermodynamic system constraint and electric power system constraint,
the power system and the thermodynamic system are coupled with each other through a cogeneration unit and a heat pump, and the cogeneration unit is supposed to operate in a constant heat-to-power ratio mode, and the constraint conditions are as follows:
Figure FDA00023996796800000410
Figure FDA00023996796800000411
Figure FDA00023996796800000412
in the formula, khp,iIs the thermoelectric ratio;
Figure FDA00023996796800000413
respectively is the upper limit and the lower limit of the output of the cogeneration unit;
Figure FDA00023996796800000414
Figure FDA00023996796800000415
maximum up-regulation power and down-regulation power in unit time delta t of the cogeneration unit are respectively;
electric power for heat pump
Figure FDA0002399679680000051
Thermal output
Figure FDA0002399679680000052
Satisfies the following conditions:
Figure FDA0002399679680000053
Figure FDA0002399679680000054
Figure FDA0002399679680000055
in the formula (I), the compound is shown in the specification,
Figure FDA0002399679680000056
power consumption of the heat pump connected with wind power and photovoltaic respectively, η is the heat pump electric heat conversion coefficient;
Figure FDA0002399679680000057
the upper limit of the output of the heat pump; n is a radical ofW、NPVThe number of the wind power plants and the number of the photovoltaic power stations are respectively;
optical power is abandoned to system abandon wind
Figure FDA0002399679680000058
Comprises the following steps:
Figure FDA0002399679680000059
in the formula (I), the compound is shown in the specification,
Figure FDA00023996796800000510
wind power and photovoltaic power generation under the scene s respectively;
Figure FDA00023996796800000511
respectively connecting wind power and photovoltaic power into a power grid;
the upper and lower limit constraints and the climbing constraints of the output of the conventional unit are as follows:
Figure FDA00023996796800000512
Figure FDA00023996796800000513
respectively is the upper and lower output of the conventional unitLimiting;
power system power balance constraint:
Figure FDA00023996796800000514
in the formula: pL,tThe system electrical load is a time period t;
power flow constraint of the power system:
Figure FDA00023996796800000515
in the formula:
Figure FDA00023996796800000516
is the power flow of branch j in time period t;P line,j、
Figure FDA00023996796800000517
respectively, the lower limit and the upper limit of the branch j power flow.
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