CN115018203A - Regional composite energy system design optimization technology - Google Patents

Regional composite energy system design optimization technology Download PDF

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CN115018203A
CN115018203A CN202210811213.7A CN202210811213A CN115018203A CN 115018203 A CN115018203 A CN 115018203A CN 202210811213 A CN202210811213 A CN 202210811213A CN 115018203 A CN115018203 A CN 115018203A
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刘魁星
黄一凯
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Abstract

The invention relates to the technical field of regional energy optimization, and discloses a design optimization technology of a regional combined energy system, which comprises a regional combined energy system model selection optimization model, wherein the model system comprises conventional normal energy equipment such as a power generation device, and the generated energy can be supplied to the regional equipment and the illumination power consumption and can meet the power consumption of the equipment in an energy station; heating devices such as gas boilers, heat pumps, and power generation devices produce high temperature flue gas or hot water. The invention takes the optimization design of the regional energy system as a core, discusses and constructs the optimization design model of the regional energy system from the aspects of optimization targets, optimization variables, constraint conditions, solving methods thereof and the like. A computational method for solving the model is proposed. The energy planning problem of a certain area in Shanghai city is analyzed by utilizing the regional energy system optimization design, and the optimal equipment combination mode, the optimal equipment capacity configuration and the optimal operation strategy under the design load of the system are obtained.

Description

Regional composite energy system design optimization technology
Technical Field
The invention relates to the technical field of regional energy optimization, in particular to a design optimization technology of a regional combined type energy system.
Background
The regional composite energy microgrid system has great advantages and potentials in the aspects of demand side load response, supply and demand matching, energy conservation and emission reduction, system stability and the like. Therefore, the regional hybrid energy microgrid system mainly based on distributed combined cooling heating and power will become a main energy supply mode, but the existing research does not provide a general design method with a theoretical basis, and only depends on related experience. All main components of the regional energy microgrid system are carefully researched by professional researchers, and most of the regional energy microgrid systems are provided with relatively mature simulation software for static or dynamic simulation. However, when the components are combined into a system, the components are no longer operated in their optimum operating state or nominal state in many cases, but in varying different states, and are coupled to one another to form more complex simulation scenarios. The original simulation software is not suitable to a certain extent, and how to develop a system suitable for a regional energy microgrid system to meet the practical requirements of the development of a distributed combined cooling heating and power system becomes an important hotspot.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a design optimization technology of a regional composite energy system, and solves the problems in the background technology.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: the design optimization technology of the regional combined type energy system comprises a regional combined type energy system model selection optimization model, wherein the model system comprises conventional normal energy equipment such as a power generation device, and the generated energy can be supplied to the regional equipment and illumination power consumption and can meet the power consumption of equipment in an energy station; heating devices such as a gas boiler, a heat pump and high-temperature flue gas or hot water generated by a power generation device can meet the requirements of regional heating heat load and hot water heat load; refrigerating devices, such as absorption chillers and conventional electric refrigeration units, the refrigerating capacity being used to satisfy the jade area air conditioning cooling load; meanwhile, the system is provided with an energy storage device, and heating and cooling capacity can be directly supplied or stored in an energy storage tank (as shown in figure 1).
The mathematical description of the model is:
(1) and optimizing the target: the analysis of the regional hybrid energy system at present mainly focuses on three aspects: economical, environment-friendly and energy-saving; with the economic objective being the most commonly used one; selecting the average cost of the whole life cycle of the regional composite energy system as the standard of system evaluation; the total cost is as follows:
TC＝C Investment +C Operation +C Maintance +C Carbon (1)
wherein, C Investment The initial investment cost of the equipment is saved; c Operation The energy consumption cost is high; c Maintance Equipment maintenance costs; c Carbon Carbon emissions taxes;
a. initial investment cost of equipment: the partial cost refers to the purchase cost of the equipment, and in order to analyze the system energy of the equipment, the equipment in the regional energy system is divided into two types, one type is a discrete technology, such as PGU equipment, and for the equipment of the type, the method is more meaningful when a proper integer solution (namely the number of the equipment) is found; the other is a continuous technology, the design capacity of the equipment is determined to be crucial, and all the technologies are considered to be continuous technologies for simplifying calculation, namely, the technologies are continuously distributed when the capacity is rated;
Figure BDA0003739150070000021
Figure BDA0003739150070000022
wherein j represents the equipment type, such as HP, EChi, etc., UC represents the equipment unit capacity price,/kW, Ca represents the equipment rated capacity, kW, i represents the annual rate, j-life represents the equipment life, year,
Figure BDA0003739150070000023
is the initial investment of continuous equipment.
b. Equipment operating cost: the operation cost comprises two parts, wherein the first part is operation electricity cost, the second part is operation gas cost, the operation electricity cost only comprises electricity cost for purchasing electricity from a power grid, the electricity cost policy is different due to different regions, the operation gas cost can be summarized into three parts, namely basic cost, peak cost and demand cost, the operation gas cost is divided into two parts, the first part is PGU gas consumption, and the second part is gas consumption of a gas boiler;
C Operation ＝C grid +C gas (4)
the basic cost of the power grid:
C F-grid ＝∑ m∈M UC F-grid ·Ca DT (5)
peak cost of the power grid:
Figure BDA0003739150070000031
the power grid demand cost:
Figure BDA0003739150070000032
gas cost:
Figure BDA0003739150070000033
wherein H represents hour, H ═ H., (24), D represents day, D ═ M represents month, M ═ 1,2, 3 ·, 12), UC — represents the price of consuming unit capacity, Ca · represents the price of consuming unit capacity, and c · represents the price of consuming unit capacity DT Representing the rated capacity of the transformer, N-representing typical days of the day, Δ t-representing the power consumption period, Pr-representing the energy price,/kWh, EC-electricity purchase for the grid side, energy consumption for the plant side, kWh, GC-representing the gas consumption, kWh;
c. equipment maintenance cost: the equipment maintenance cost can be divided into fixed enclosure cost and variable maintenance cost, wherein the fixed maintenance cost is optimized with the installed capacity of the equipment, and the variable maintenance cost is mainly related to the running output of the equipment;
Figure BDA0003739150070000034
in the formula, alpha j-f -represents a fixed maintenance cost factor, α j-v -represents a variable maintenance cost factor, EO-represents energy production, such as PGU power production, HP heat production or heat and cold production, etc., d carbon emission cost;
the carbon emission is mainly carried out by three ways, namely, the carbon emission generated indirectly by purchasing power grid electricity, the carbon emission generated directly by gas turbine consumed gas and the carbon emission generated directly by gas boiler consumed gas are firstly carried out;
Figure BDA0003739150070000041
in the formula: beta represents a carbon emission coefficient, which means the amount of carbon dioxide emitted per unit of energy produced, and epsilon represents carbon rejection.
(2) Constraint conditions
a. Electric quantity balance constraint
The electricity consumption end mainly comprises architectural illumination or equipment electricity consumption, electricity consumption of an electric refrigerating unit in an energy system, electricity consumption of a heat pump unit and electricity consumption of auxiliary equipment thereof. The electric quantity balance in the h time period is as follows:
Figure BDA0003739150070000042
in the formula: EC (EC) h，AE For power consumption of attached devices in the system, EL h Area lighting and equipment electrical loads, and b is heat balance constraint;
the hot end mainly comprises building hot water or heating heat, the absorption chiller refrigeration heat, the heat production end mainly comprises a power generation device, a gas boiler and a heat pump, the energy storage equipment can be used as the hot end and the heat production section, and the heat balance in the h time period is as follows:
Figure BDA0003739150070000043
in the formula:
Figure BDA0003739150070000044
-representing the power plant thermoelectric ratio, δ -being the rate of heat loss,
Figure BDA0003739150070000045
-representing the efficiency of heat release and heat storage, respectively, of the energy storage device;
c. cold quantity balance restraint
The cold end is mainly used for the cold load of the air conditioner of the building. Similarly, the energy storage device can be used as a cold end and a release end, and the cold quantity in the h period is balanced as follows:
Figure BDA0003739150070000051
the energy storage device is used to store cold in summer and heat in the rest of the season, so in equations (4-19)
Figure BDA0003739150070000052
Respectively, cold accumulation rate and cold release rate.
d. Device constraints
Any equipment has a minimum and maximum output range, the equipment has a start-stop state, and for the power generation device, the following balance exists between the power generation amount and the gas consumption amount of the power generation device at the moment h:
GC h，PGU ＝EO h，PGU /η PGU (14)
and there is a maximum minimum of the power generation:
Figure BDA0003739150070000053
in the formula: eta PGU -determining the power generation efficiency of the power plant, and performing a fixed value processing; bin (n) h，PGU Binary variable, bin, representing the start-stop of the power plant h，PGU E {0, 1 }; when the value is equal to 1, the unit is opened, and when the value is equal to 0, the unit is closed; PGU EO，
Figure BDA0003739150070000054
-respectively representing the minimum maximum power production of the unit;
for absorption chillers, there is a balance between refrigeration capacity and heat consumption as follows:
EC h，AC ＝EO h，AC /COP AC (16)
the unit refrigerating capacity is restricted as follows:
Figure BDA0003739150070000055
bin h，AC ≤bin h，PGU (18)
for a heat pump unit, the heat pump unit can be used for heating and refrigerating, the heat pump unit is constrained forcibly to be only used for refrigerating in summer, and the heat pump unit can be only used for heating in other seasons;
Figure BDA0003739150070000056
Figure BDA0003739150070000057
Figure BDA0003739150070000061
Figure BDA0003739150070000062
Figure BDA0003739150070000063
Figure BDA0003739150070000064
the formula (4-30) ensures that the unit can not be cooled and heated simultaneously;
for an electric refrigerating unit, the refrigerating capacity and the power consumption are balanced:
EC EChi ＝EO EChi /COP EChi (25)
maximum and minimum cooling capacity constraints:
Figure BDA0003739150070000065
for a gas boiler, the gas consumption and the heat production are balanced:
GC h，B ＝EO h，B /η B (27)
maximum and minimum heat generation constraints:
Figure BDA0003739150070000066
for energy storage, the stored energy balance in the energy storage device is constrained:
Figure BDA0003739150070000067
assuming the optimal case, after the end of one period, the stored energy is equal to the stored energy at the starting time, that is:
Figure BDA0003739150070000068
the maximum energy release rate of the energy storage device is as follows:
Figure BDA0003739150070000069
the maximum energy storage rate of the energy storage device is:
Figure BDA00037391500700000610
energy storage and release cannot be performed simultaneously, so that:
Figure BDA0003739150070000071
the maximum stored energy of the energy storage device is less than the rated capacity of the device:
Figure BDA0003739150070000072
other constraints in the system are that the surplus generated energy of the power generation transposition does not allow online sales, so that:
Figure BDA0003739150070000073
(3) optimizing variables
There are many devices in a regional energy system, some of which do not need to be optimized, for example, the capacity of a heat exchanger must meet the maximum heat load requirement, or the capacity of other devices can be determined naturally after the capacity of a certain device is selected. Therefore, the selection of the optimization variables of the regional energy system should follow the principles of independence, importance and determinism, and in particular, the selection of the optimization variables of the regional energy system generally comprises the following aspects;
a. capacity allocation of regional energy system power generation device
The capacity of the main equipment in the regional energy system in the power generation equipment determines the operation mode of the system, the capacity of the heat storage equipment and the maximum power supplement amount of the power grid. If the capacity of the power generation device is small, the system operation economy cannot be realized well by using the energy price policy in the system operation stage, and if the capacity is large, the initial investment of the system becomes large, and the time for operating the power generation device at the low load rate increases. The economics of the system may be reduced for the entire life cycle;
b. capacity allocation of thermal storage devices in regional energy systems
The heat storage device is arranged in the regional energy system to store the recovered redundant heat and improve the waste heat utilization rate, so that the energy utilization rate of the whole system is improved. Meanwhile, the heat storage device can also improve the economical efficiency of system operation by utilizing the time-of-use difference of the energy price. The increase in the capacity of the heat storage device is advantageous for the improvement of the heat storage effect, but increases the investment in the heat storage device. The capacity of the heat storage device depends on the composition and load characteristics of a regional energy system and needs to be obtained through optimized calculation;
c. refrigeration device capacity determination in a regional energy system
The refrigerating device in the regional energy system comprises absorption type cold and conventional electric refrigerating units and a heat pump unit. The three can provide the cold energy needed by the area at the same time. The absorption chiller can make full use of the waste heat generated by the power generation device to refrigerate, so as to improve the overall efficiency of the system, but the refrigeration efficiency of the absorption chiller is generally lower than that of the conventional chiller and heat pump unit. And the electric refrigerating unit and the heat pump unit need to be electrically driven for refrigeration. The primary energy is used as a standard, and the electricity price is higher than the gas price. Therefore, how to allocate the capacities of the three components not only affects the initial investment of the system but also affects the operating cost of the system;
d. start-stop control of each device
The equipment generally has a certain designed operation range, and has higher operation efficiency in the changed range, while the equipment efficiency is sharply reduced under low load rate. Therefore, it is necessary to define the start and stop of the lowest operation load rate control device to increase the operation load of the system, thereby increasing the operation efficiency of the system. Fumo. N et al [100,101] set the minimum load rate to be 0.25 to control the start and stop of equipment in a regional energy system, but because the heat, electricity and cold demand characteristics of different regions are different, the equipment performance should be combined and optimized to obtain the optimal minimum load rate, thereby achieving the maximum benefit of the system;
e. control of output of each device
Because of the difference of efficiency and energy consumption types among the similar devices, the difference of device energy consumption and operating cost exists under the same output condition. Meanwhile, for a single device, the efficiency values under different output conditions are different, so that the output of each device in the regional energy system must be obtained by an optimization means, and an operation optimization strategy of the system is obtained.
As shown in fig. 2, the solution method of the model is:
s1, initialization: ILP for initial integer programming problem 0 Indicating that the upper bound is set to
Figure BDA0003739150070000081
For a L ∈ L, its lower bound is set toz l ＝-∞；
S2, terminating: if it is not
Figure BDA0003739150070000082
Then x is solved * So that the target value
Figure BDA0003739150070000083
Is optimal if there is no such x * Then ILP is not feasible;
s3, problem selection: selecting and deleting a problem ILP from L l ；
S4, relaxation issue: solving Linear Programming ILP l If the relaxation problem is not trusted, letz l + ∞, then step S6 is performed, if it is limited, letz l Let x be the optimal target value for the relaxation problem IR Recording as the optimal solution, otherwise, orderz l ＝-∞；
S5, adding a cutting plane: if desired, a cut plane is found which disrupts x IR If found, add it to the relaxation problem and return to step S4;
s6, measure and delete: if it is not
Figure BDA0003739150070000091
Returning to step S2; if it is not
Figure BDA0003739150070000092
And x IR Is an integer and is feasible, updated
Figure BDA0003739150070000093
All questions in L are deleted and the process returns to step S2;
s7, dividing: let
Figure BDA0003739150070000094
Is problem ILP l Constraint set S of l One division of (a); adding problems to L
Figure BDA0003739150070000095
Here ILP Ij Is ILP l To S Ij Is limited by the feasible region of (A), andz Ij (j ═ 1, 2.. times, k) is a set of values of problem l, and the process returns to step S2.
(III) advantageous effects
The invention provides a design optimization technology of a regional combined energy system, which has the following beneficial effects:
the invention takes the optimization design of the regional energy system as a core, discusses and constructs the optimization design model of the regional energy system from the aspects of optimization targets, optimization variables, constraint conditions, solving methods thereof and the like. A computational method for solving the model is proposed. The energy planning problem of a certain area in Shanghai city is analyzed by utilizing the optimization design of the area energy system, and the optimal equipment combination mode, the optimal equipment capacity configuration and the optimal operation strategy under the design load of the system are obtained.
Drawings
FIG. 1 is a schematic diagram of a regional utility energy system;
FIG. 2 is a schematic flow chart of a solution;
FIG. 3 is a diagram of a regional cooling, heating and power distribution system;
FIG. 4 is a diagram of a district combined cooling heating and power system (without energy storage);
FIG. 5 is a diagram of a district combined cooling heating and power system (with energy storage);
FIG. 6 is a typical daily cooling load map for a regional building;
FIG. 7 is a typical solar heat load map for a regional building;
FIG. 8 is a typical daily electrical load graph for a regional building;
FIG. 9 is a diagram of a typical summer cooling schedule for the system;
FIG. 10 is a diagram of a typical daily cooling scheme for the second summer of the system;
FIG. 11 is a schematic view of a typical day cooling strategy in the third summer of the system;
FIG. 12 is a diagram of a typical daily heating schedule for the system;
FIG. 13 is a diagram of a second exemplary daily heating schedule for the system;
FIG. 14 is a diagram of a three typical daily heating schedule for the system;
FIG. 15 is a diagram of a typical daily power scheme for the system;
FIG. 16 is a diagram of a typical daily power scheme for a second system;
FIG. 17 is a diagram of a three typical day power scheme for the system;
FIG. 18 is a chart of annual operating costs of the system;
FIG. 19 is a graph of a peak-to-valley power consumption rate ratio of the system;
FIG. 20 is a diagram of a system peak-to-valley level power consumption rate ratio;
FIG. 21 is a diagram of the peak-to-valley power cost ratio of the system.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For the regional energy system, the cooling, heating and installed capacities of power supply equipment of the regional energy system are determined by an optimization method according to the time-by-time cooling, heating and electric loads of the region all the year and the regional energy price policy, and an optimized operation strategy of the system is preliminarily given. Therefore, in order to evaluate the advantages of the combined cooling heating and power system, the cooling and power system shown in fig. 3 is selected as a reference system of the combined cooling, heating and power system. In order to further analyze the influence of the energy storage device on the design and operation of the combined cooling heating and power system, the systems of fig. 4 and 5 are provided.
Taking a certain area of the sea city as an example, the area of the building is 20 ten thousand meters 2 The building area proportion of the six types of buildings is 32 percent of office buildings, hospital buildings, residential buildings, venue buildings, market buildings and hotel buildings, 9 percent of office buildings, 27 percent of hospital buildings, 10 percent of residential buildings, 10 percent of venue buildings and 11 percent of market buildings. Typical daily air conditioning cold and hot water and electrical loads for this area are shown in fig. 6-8.
Results of the experiment
Fig. 10, 11, 13, 14, 16 and 17 show the optimal operation strategy of the system. The greatest difference from the system one is that the functional strategies of the system two and the system three become complicated. Since the case takes the minimum cost as the optimization target, as shown in the light-colored line frame of fig. 10, the heat pump unit basically performs refrigeration in the valley power period, and the absorption heat pump performs refrigeration in the peak power period, or the heat pump unit performs little refrigeration. As shown in fig. 11, for the third system, a similar strategy is also adopted for the heat pump unit to reduce the system operation cost. For the second system, the phenomenon of refrigeration in the peak power period also occurs, and as shown by a dark line frame in fig. 10, the heat pump unit can also produce a large amount of cold energy in the peak power stage. The area cold load is large at this moment, namely the absorption heat pump unit can not meet the system cold requirement even when operating under the rated working condition, so that the system cold requirement can be met even if more peak electricity is consumed based on the constraint of supply and demand balance. However, the restriction and balance between the system optimization design and the optimization operation are also reflected, the optimal scheme is not the scheme that the capacity of the absorption heat pump is increased to reduce the system operation cost, but an optimal balance point exists between the equipment investment and the operation cost.
As shown in the dark-colored frame of fig. 11, compared with the second system, the third system bears part of the peak load due to the energy storage equipment, so that the heat pump cooling capacity of the typical day of the month 7 in the third system is obviously reduced. And the energy storage device is substantially cooled during peak electricity periods. Obviously, the operating cost of the system three will be reduced. The same phenomenon exists for the system heating strategy shown in fig. 12-14. In terms of system power supply, the power supply amount is larger than the building electrical load in any system because the system is provided with a heat pump unit and auxiliary power consumption equipment thereof. For the system, all electricity is purchased from the grid. For the second system and the third system, the internal combustion engine generates electricity and bears most of basic electric loads, and the power grid purchasing electricity is responsible for peak electric loads and electric loads in valley electricity periods.
For a fixed system architecture, the system operating policy determines how much the system is operating at a cost. Because the first system adopts a fixed simple operation strategy, and the second system and the third system adopt an optimized operation strategy, the annual operation cost of the second system and the third system is obviously reduced compared with that of the third system. As shown in fig. 18, the operating cost of the system two is reduced by 39% compared with that of the system one, and in the system three, because the energy storage equipment is added, the energy is stored in the valley power period and released in the peak power period, the operating cost of the system is further reduced, and compared with the system one, the operating cost is reduced by about 45%. Fig. 19-21 count the proportion of power consumption charges at different time intervals, and the peak power charge of system one and system two is significantly higher than that of system three. The electricity consumption of the system III is mainly concentrated in the electricity leveling stage, and the ratio of the valley electricity consumption is higher than the ratio of the electricity consumption of the system I and the electricity consumption of the system II. The crucial role of energy storage in reducing the operating costs of the system is therefore fully verified.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (1)

1. The design optimization technology of the regional combined type energy system comprises a regional combined type energy system model selection optimization model and is characterized in that: the model system comprises conventional normal energy equipment such as a power generation device, and the generated energy can be supplied to regional equipment and illumination power consumption and can meet the requirement of power consumption of equipment in an energy station; heating devices such as a gas boiler, a heat pump and high-temperature flue gas or hot water generated by a power generation device can meet the requirements of regional heating heat load and hot water heat load; refrigerating devices, such as absorption chillers and conventional electric refrigeration units, the refrigerating capacity being used to satisfy the jade area air conditioning cooling load; meanwhile, the system is provided with an energy storage device, and heating and refrigerating capacity can be directly supplied and also can be stored in an energy storage tank;
the mathematical description of the model is:
(1) and optimizing the target: the analysis of the regional hybrid energy system at present mainly focuses on three aspects: economical, environment-friendly and energy-saving; with the economic objective being the most commonly used one; selecting the average cost of the whole life cycle of the regional composite energy system as the standard of system evaluation; the total cost is as follows:
TC＝G Investment +C Operation +C Maintance +C Carbon (1)
wherein, C Investment The initial investment cost of the equipment is saved; c Operation The energy consumption cost is high; c Maintance Equipment maintenance costs; c Carbon Carbon emissions taxes;
a. initial investment cost of equipment: the partial cost refers to the purchase cost of the equipment, and in order to analyze the system energy of the equipment, the equipment in the regional energy system is divided into two types, one type is a discrete technology, such as PGU equipment, and for the equipment, it is more meaningful to find a proper integer solution (namely the number of the equipment); the other is a continuous technology, the design capacity of the equipment is determined to be crucial, and all the technologies are considered to be continuous technologies for simplifying calculation, namely, the technologies are continuously distributed when the capacity is rated;
Figure FDA0003739150060000011
Figure FDA0003739150060000012
wherein j represents the equipment type, such as HP, EChi, etc., UC represents the equipment unit capacity price,/kW, Ca represents the equipment rated capacity, kW, i represents the annual rate, j-life represents the equipment life, year,
Figure FDA0003739150060000013
is the initial investment of continuous equipment;
b. equipment operating cost: the operation cost comprises two parts, wherein the first part is operation electricity cost, the second part is operation gas cost, the operation electricity cost only comprises electricity cost for purchasing electricity from a power grid, the electricity cost policy is different due to different regions, the operation gas cost can be summarized into three parts, namely basic cost, peak cost and demand cost, the operation gas cost is divided into two parts, the first part is PGU gas consumption, and the second part is gas consumption of a gas boiler;
C Operation ＝C grid +C gas (4)
the basic cost of the power grid:
C F-grid ＝∑ m∈M UC F-grid ·Ca DT (5)
peak cost of the power grid:
Figure FDA0003739150060000021
the power grid demand cost:
Figure FDA0003739150060000022
gas cost:
Figure FDA0003739150060000023
wherein H represents hour, H ═ H., (24), D represents day, D ═ M represents month, M ═ 1,2, 3 ·, 12), UC — represents the price of consuming unit capacity, Ca · represents the price of consuming unit capacity, and c · represents the price of consuming unit capacity DT Representing the rated capacity of the transformer, N-representing typical days of the day, Δ t-representing the power consumption period, Pr-representing the energy price,/kWh, EC-electricity purchase for the grid side, energy consumption for the plant side, kWh, GC-representing the gas consumption, kWh;
c. equipment maintenance cost: the equipment maintenance cost can be divided into fixed enclosure cost and variable maintenance cost, wherein the fixed maintenance cost is optimized with the installed capacity of the equipment, and the variable maintenance cost is mainly related to the running output of the equipment;
Figure FDA0003739150060000031
in the formula, alpha j-f -represents a fixed maintenance cost factor, α j-v -represents a variable maintenance cost factor, EO-represents energy production, such as PGU power production, HP heat production or heat and cold production, etc., d carbon emission cost;
the carbon emission is mainly carried out by three ways, namely, the carbon emission generated indirectly by purchasing power grid electricity, the carbon emission generated directly by gas turbine consumed gas and the carbon emission generated directly by gas boiler consumed gas are firstly carried out;
Figure FDA0003739150060000032
in the formula: beta represents a carbon emission coefficient, which means the amount of carbon dioxide emitted per unit of energy produced, and epsilon represents carbon rejection.
(2) Constraint conditions
a. Electric quantity balance constraint
The electricity consumption end mainly comprises architectural illumination or equipment electricity consumption, electricity consumption of an electric refrigerating unit in an energy system, electricity consumption of a heat pump unit and electricity consumption of auxiliary equipment thereof. The electric quantity balance in the h time period is as follows:
Figure FDA0003739150060000033
in the formula: EC (EC) h，AE For power consumption of attached devices in the system, EL h Area lighting and equipment electrical loads, and b is heat balance constraint;
the hot end mainly comprises building hot water or heating heat, the absorption chiller is used for refrigeration, the heat production end mainly comprises a power generation device, a gas boiler and a heat pump, the energy storage equipment can be used as the hot end and a heat production section, and the heat balance in the h period is as follows:
Figure FDA0003739150060000034
in the formula:
Figure FDA0003739150060000041
-representing the power plant thermoelectric ratio, δ -being the rate of heat loss,
Figure FDA0003739150060000042
-representing the efficiency of heat release and heat storage, respectively, of the energy storage device;
c. cold quantity balance restraint
The cold end mainly refers to the cold load of the air conditioner of the building, and the energy storage equipment can be used as the cold end and also can be used as the release end, and the cold quantity in the h time period is balanced as follows:
Figure FDA0003739150060000043
the energy storage device is used to store cold in summer and heat in the rest of the season, so in equations (4-19)
Figure FDA0003739150060000044
Respectively indicating the cold accumulation rate and the cold release rate;
d. device constraints
Any equipment has a minimum and maximum output range, the equipment has a start-stop state, and for the power generation device, the following balance exists between the power generation amount and the gas consumption amount of the power generation device at the moment h:
GC h，PGU ＝EO h，PGU /η PGU (14)
and there is a maximum minimum of the power generation:
Figure FDA0003739150060000045
in the formula: eta PGU -determining the power generation efficiency of the power plant, and performing a fixed value processing; bin (binary) h，PGU Binary variable, bin, representing the start-stop of the power plant h，PGU E {0, 1 }; when the value is equal to 1, the unit is opened, and when the value is equal to 0, the unit is closed; PGU EO，
Figure FDA0003739150060000046
-respectively representing the minimum maximum power production of the unit;
for absorption chillers, there is a balance between refrigeration capacity and heat consumption as follows:
EC h，AC ＝EO h，AC /COP AC (16)
the unit refrigerating capacity is restricted as follows:
Figure FDA0003739150060000047
bin h，AC ≤bin h，PGU (18)
for a heat pump unit, the heat pump unit can be used for heating and refrigerating, the heat pump unit is constrained forcibly to be only used for refrigerating in summer, and the heat pump unit can be only used for heating in other seasons;
Figure FDA0003739150060000051
Figure FDA0003739150060000052
Figure FDA0003739150060000053
Figure FDA0003739150060000054
Figure FDA0003739150060000055
Figure FDA0003739150060000056
the formula (4-30) ensures that the unit can not be cooled and heated simultaneously;
for an electric refrigerating unit, the refrigerating capacity and the power consumption are balanced:
EC EChi ＝EO EChi /COP EChi (25)
maximum minimum capacity constraint:
Figure FDA0003739150060000057
for a gas boiler, the gas consumption and the heat production are balanced:
GC h，B ＝EQ h，B /η B (27)
maximum and minimum heat generation constraints:
Figure FDA0003739150060000058
for energy storage, the stored energy balance in the energy storage device is constrained:
Figure FDA0003739150060000059
assuming the optimal case, after the end of one period, the stored energy is equal to the stored energy at the starting time, that is:
Figure FDA0003739150060000061
the maximum energy release rate of the energy storage device is as follows:
Figure FDA0003739150060000062
the maximum energy storage rate of the energy storage device is:
Figure FDA0003739150060000063
energy storage and release cannot be performed simultaneously, so that:
Figure FDA0003739150060000064
the maximum stored energy of the energy storage device is less than the rated capacity of the device:
Figure FDA0003739150060000065
other constraints in the system are that the surplus generated energy of the power generation transposition does not allow online sales, so that:
Figure FDA0003739150060000066
(3) optimizing variables
The regional energy system comprises a large number of devices, wherein the capacities of some devices are not required to be optimized, for example, the capacity of a heat exchanger must meet the requirement of the maximum heat load, or the capacities of other devices can be determined naturally after the capacity of a certain device is selected, so that the selection of the optimization variables of the regional energy system follows the principles of independence, importance and determinacy, and particularly, the selection of the optimization variables of the regional energy system generally comprises the following aspects;
a. capacity allocation of regional energy system power generation device
The capacity of main equipment in a regional energy system of power generation equipment determines the operation mode of the system, the capacity of heat storage equipment and the maximum power supplement amount of a power grid, if the capacity of a power generation device is smaller, the system operation stage cannot well utilize an energy price policy to realize the system operation economy, and if the capacity is larger, the initial investment of the system is increased, the time for operating the power generation device at a low load rate is increased, and therefore, the economy of the system can be reduced in the whole life cycle;
b. capacity allocation of thermal storage devices in regional energy systems
The heat storage device is arranged in the regional energy system for storing the recovered surplus heat and improving the waste heat utilization rate, so that the energy utilization rate of the whole system is improved, meanwhile, the heat storage device can also improve the economical efficiency of the system operation by utilizing the time-sharing price difference of the energy price, the increase of the capacity of the heat storage device is beneficial to the improvement of the heat storage effect, but the investment of the heat storage device can be increased, and the size of the capacity of the heat storage device depends on the composition and the load characteristic of the regional energy system and needs to be obtained through optimized calculation;
c. refrigeration device capacity determination in a regional energy system
The refrigerating device in the regional energy system comprises an absorption type cold machine, a conventional electric refrigerating unit and a heat pump unit, the absorption type cold machine, the conventional electric refrigerating unit and the heat pump unit can simultaneously provide cold energy required by a region, the absorption type cold machine can fully utilize waste heat generated by a power generation device for refrigeration, and the overall efficiency of the system is improved, but the refrigerating efficiency of the absorption type cold machine is generally lower than that of the conventional cold machine and the heat pump unit, and the electric refrigerating unit and the heat pump unit need to be electrically driven for refrigeration; the primary energy is used as a standard, and the electricity price is higher than the gas price, so that how to distribute the capacities of the primary energy, the secondary energy and the gas price affects the initial investment of the system and the running cost of the system;
d. start-stop control of each device
The equipment generally has a certain designed operation range, has higher operation efficiency in the changed range, and has sharp reduction under low load rate, so the start-stop of the equipment needs to be controlled by defining the lowest operation load rate to improve the operation load of the system, thereby the operation efficiency of the system is improved, Fumo.N et al [100,101] sets the lowest load rate to be 0.25 to control the start-stop of the equipment in a regional energy system, but because the heat, electricity and cold demand characteristics of different regions are different, the equipment performance is combined and optimized to obtain the optimal lowest load rate, thereby the maximum benefit of the system is achieved;
e. controlling the output of each device
Because the efficiency of the similar equipment is different and the energy consumption types are different, the equipment energy consumption and the operation cost are different under the same output condition, and meanwhile, for a single equipment, the efficiency values under different output conditions are also different, the output of each equipment in the regional energy system must be obtained by an optimization means, and the operation optimization strategy of the system is obtained;
the solving method of the model comprises the following steps:
s1, initialization: ILP for initial integer programming problem 0 Indicating that the upper bound is set to
Figure FDA0003739150060000081
For a L ∈ L, its lower bound is set toz l ＝-∞；
S2, terminating: if it is used
Figure FDA0003739150060000082
Then x is solved * So that the target value
Figure FDA0003739150060000088
Is optimal if there is no such x * Then ILP is not feasible;
s3, problem selection: selecting and deleting a problem ILP from L l ；
S4, relaxation issue: solving Linear Programming ILP l If the relaxation problem is not trusted, letz l + ∞, then step S6 is performed, if it is limited, letz l Let x be the optimal target value for the relaxation problem IR Recording as the optimal solution, otherwise, orderz l ＝-∞；
S5, adding a cutting plane: if desired, a cut plane is found which disrupts x IR If found, add it to the relaxation problem and return to step S4;
s6, measure and delete: if it is not
Figure FDA0003739150060000083
Returning to step S2; if it is not
Figure FDA0003739150060000084
And x IR Is an integer and is feasible, updated
Figure FDA0003739150060000085
All questions in L are deleted and the process returns to step S2;
s7, dividing: let
Figure FDA0003739150060000086
Is problem ILP l Is a constraint set S l One division of (a); adding problems to L
Figure FDA0003739150060000087
Here ILP Ij Is ILP l To S Ij Is limited by the feasible region of (A), andz Ij where (j ═ 1, 2.., k) is the set of values for problem 1, the process returns to step S2.
CN202210811213.7A 2022-07-11 2022-07-11 Regional composite energy system design optimization technology Pending CN115018203A (en)

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