CN112465261A - Planning method of comprehensive energy system for multi-element main body access - Google Patents
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Abstract
The invention discloses a planning method of a comprehensive energy system for multi-element main body access, which comprises the following steps: constructing an energy flow graph of the comprehensive energy system based on the basic characteristics of the comprehensive energy system; determining constraint conditions based on the energy flow graph; constructing a comprehensive energy system planning model under an optimal planning scheme on the basis of an energy flow diagram and constraint conditions and on the premise of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency; and providing guidance suggestions for planning the comprehensive energy system based on the comprehensive energy system planning model under the optimal planning scheme. According to the invention, by analyzing the characteristics of the comprehensive energy system, a comprehensive energy system planning design model is constructed with the aims of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency, and guidance suggestions are provided for the planning of the comprehensive energy system.
Description
Technical Field
The invention relates to the technical field of comprehensive energy system planning design, in particular to a planning method of a comprehensive energy system for multi-element main body access.
Background
With the development of society, people's demand for clean energy is increasing, and it is under this background that this concept of comprehensive energy system is produced. The comprehensive energy system is taken as a main component of an energy internet, is currently considered as a main operation form of future human social energy, and can better improve the energy utilization rate and achieve the effect of 1+1>2 under the condition of collaborative optimization of different energy forms.
The ubiquitous network literally means a network which faces the public and the society and widely exists, takes ubiquitous, ubiquitous and ubiquitous as basic characteristics, and is not limited by factors such as time, places, personnel and the like. In the related planning problem of the comprehensive energy system, when the ubiquitous power internet of things is discussed, the ubiquitous power internet of things is usually discussed as one of important links in the strategic target of 'three-type two-network, world first-class', and the ubiquitous power internet of things surrounds all links of the power system, fully applies modern information technologies such as mobile interconnection, artificial intelligence and the like, realizes the interconnection of everything and man-machine interaction in all links of the power system, and provides intelligent and convenient services for the planning of the comprehensive energy system.
Therefore, how to provide a planning method for a multi-element main body-oriented integrated energy system capable of reducing the integrated cost, reducing the low carbon emission and improving the integrated energy efficiency is a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides a method for planning an integrated energy system for multi-element body access, which is based on establishing an energy flow graph of the integrated energy system, and by analyzing the characteristics of the integrated energy system, constructs a planning and design model of the integrated energy system with the objectives of lowest integrated cost, lowest carbon emission, and highest integrated energy efficiency, and provides guidance and suggestion for planning the integrated energy system.
In order to achieve the purpose, the invention adopts the following technical scheme:
a planning method for a comprehensive energy system facing multi-element main body access comprises the following steps:
constructing an energy flow diagram of the integrated energy system based on basic characteristics of the integrated energy system;
determining constraint conditions based on the energy flow graph;
constructing a comprehensive energy system planning model under an optimal planning scheme on the basis of the energy flow graph and the constraint conditions and on the premise of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency;
and providing guidance suggestions for planning the comprehensive energy system based on the comprehensive energy system planning model under the optimal planning scheme.
Preferably, in the above method for planning an integrated energy system oriented to multiple subject access, the energy flow diagram includes: the coupling of each link of the comprehensive energy system, the operation characteristics of each key device in the comprehensive energy system and the transmission characteristics of various forms of energy in the comprehensive energy system.
Preferably, in the above planning method for a multi-agent access-oriented integrated energy system, the determining of the constraint condition includes: energy balance constraints, equipment physics constraints, investment quota constraints, and energy interaction constraints.
Preferably, in the above planning method for a multi-agent access-oriented integrated energy system, the expression of the energy balance constraint is as follows:
wherein, Pload(t) represents the consumer electrical load, Hload(t) represents a thermal load, Lload(t) represents cooling load in kW; pi(t) represents the supply power of device i; hm(t) represents the heating power of the plant m; l isn(t) represents the cooling power of the plant n.
Preferably, in the above planning method for a comprehensive energy system oriented to multi-agent access, the expression of the physical constraints of the device is as follows:
wherein, Pi minRepresents the minimum power, P, of the device ii maxRepresenting the maximum power of the equipment i, and the unit is kW; pj(t) represents the real-time output of the equipment i at the moment t, and the unit is kW; SOCminRepresenting a minimum value of the energy generated by the energy storage device; SOCmaxRepresents the maximum value of the residual energy of the energy storage device; soc (t) represents the remaining energy of the energy storage device at time t.
Preferably, in the planning method of the comprehensive energy system oriented to multi-agent access, the expression of the investment quota constraint is as follows:
wherein, CinvRepresenting the initial investment amount of the comprehensive energy system;
representing the maximum amount of investment that can be borne by the integrated energy system; cunit_tRepresenting the investment cost of equipment i per unit capacity; qunit_tRepresenting the planned capacity of device i; cLCRepresenting an integrated energy source.
Preferably, in the planning method of the comprehensive energy system oriented to multi-element principal access, the expression of the energy interaction constraint is as follows:
wherein the content of the first and second substances,
representing the minimum value of the exchange power between the power grid and the comprehensive energy system;
representing the maximum value of the exchange power between the power grid and the integrated energy system;
representing the minimum value of the interaction quantity between the natural gas network and the comprehensive energy system;
representing the maximum amount of interaction between the natural gas grid and the integrated energy system.
Preferably, in the planning method of the comprehensive energy system for multi-element main body access, based on the energy flow graph and the constraint condition, and on the premise of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency, a comprehensive energy system planning model under an optimal planning scheme is constructed; the method comprises the following steps:
constructing a comprehensive energy system planning model on the basis of the constraint conditions and taking the lowest comprehensive cost, the lowest carbon emission and the highest comprehensive energy efficiency as the consideration premises;
generating different planning schemes of the comprehensive energy system planning model based on different characteristics of a supply side, a transmission side and a demand side of the energy flow graph;
and solving the comprehensive energy system planning model under the different planning schemes by using a genetic algorithm to obtain an optimal scheme.
Preferably, in the planning method of the integrated energy system oriented to multi-element subject access, a construction process of the integrated energy system planning model is as follows:
respectively constructing objective functions of comprehensive cost, carbon emission and comprehensive energy efficiency; wherein, the objective function of the comprehensive cost is as follows:
F1＝Cfin＝Cequ+Cope+Cmai+Cdep；
wherein, CfinRepresents the minimum value of the annual equivalent comprehensive cost; cequRepresenting the annual cost of initial investment of equipment; copeRepresents the system operating cost; cmaiRepresents the cost of system maintenance; cdepRepresents equipment depreciation cost;
the objective function for carbon emissions is as follows:
wherein, minCcirRepresents the minimum value of carbon emissions; peleRepresenting the purchase amount of the integrated energy system; f. ofgasRepresenting the gas purchasing quantity of the integrated energy system;
carbon dioxide emission coefficient per unit of electricity;
a carbon dioxide emission coefficient representing a unit gas amount;
the objective function of the integrated energy efficiency is as follows:
wherein maxEC represents the maximum value of the comprehensive energy efficiency; ploadRepresenting the electrical load of the integrated energy system, coneleRepresents the power consumption of the integrated energy system; congasRepresenting the gas consumption of the integrated energy system; etagasRepresenting the conversion coefficient of natural gas into electricity as heat.
Preferably, in the method for planning an integrated energy system oriented to multi-element subject access, a genetic algorithm is used to solve the integrated energy system planning models under the different planning schemes to obtain an optimal scheme, including:
coding each device related in the comprehensive energy system model to obtain a population, and determining the initial population size and the maximum iteration number;
randomly generating an initialization population S with the scale of N;
calculating the individual fitness of the population by using the following formula;
F＝min(F1+F2+F3)；
fit＝min(F)；
in the above formula, fit is the minimum value of the individual fitness function, and represents that the individual fitness is the highest;
selecting, crossing and mutating the initialization population S and generating a child population Q of the initialization population S;
calculating economic and environmental target values of the offspring population Q to obtain individual fitness of the offspring population Q;
and selecting the optimal offspring from the mixed population of the parent population and the offspring population, and iterating until the maximum iteration times is reached, and outputting the optimal scheme.
According to the technical scheme, compared with the prior art, the invention discloses a planning method of a comprehensive energy system for multi-element main body access, which comprises the following steps of: the carbon emission and the emission of other pollutants are effectively reduced, and the environment is protected; the advantages of different energy supply systems can be integrated, and the optimal scheduling of different energy systems can be realized; the energy flow graph can be constructed by integrating basic characteristics such as optimized utilization of different energy forms and combining the coupling characteristics (including aspects such as economy and reliability) of the comprehensive energy system, the operating characteristics of key equipment in the comprehensive energy system and the transmission characteristics (including various energy forms such as electricity, heat and gas) of the comprehensive energy system. Then, according to the energy flow diagram, the most appropriate constraint condition is determined, and in the selection of the constraint condition, in addition to the energy balance constraint, energy interaction constraint between different energy forms is also considered. And secondly, establishing a comprehensive energy system planning model according to the energy flow diagram and the constraint conditions, and optimizing the comprehensive energy system planning model to finally obtain an optimal scheme. Finally, under the guidance of the optimal scheme, energy supply equipment, a transmission network and the like in the park are integrally planned and built, so that the lowest comprehensive economic cost in the system is met, the carbon emission is effectively reduced, and the comprehensive energy efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flow chart of a planning method of a comprehensive energy system facing multi-element main body access provided by the invention;
FIG. 2 is a schematic diagram of the power flow of the integrated energy system under a typical scenario provided by the present invention;
FIG. 3 is a flow chart of a genetic algorithm provided by the present invention;
FIG. 4 is a graph showing a 8760 hour year round cold compliance curve, a thermal load curve and a charge curve in accordance with the present invention;
FIG. 5 is a graph showing a wind speed curve and an illumination intensity curve for 8760 hours a year round in accordance with the present invention;
FIG. 6 is a graph showing the results of pareto provided by the present invention;
FIG. 7 is a graph of typical daily user load curves provided by the present invention;
FIG. 8 is a schematic diagram of the point system supply and demand balance provided by the present invention;
FIG. 9 is a schematic diagram of the heat system supply and demand balance provided by the present invention;
FIG. 10 is a schematic view of the balance of supply and demand of the cooling system provided by the present invention;
FIG. 11 is a graph showing the results of an analysis of sensitivity to investment quota provided by the present invention.
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.
As shown in fig. 1-2, the embodiment of the invention discloses a method for planning a comprehensive energy system for multi-element main body access, which comprises the following steps:
and S1, constructing an energy flow graph of the comprehensive energy system based on the basic characteristics of the comprehensive energy system.
Among them, the integrated energy system itself has the following basic features: (1) the use of the comprehensive energy system can effectively reduce the carbon emission and the emission of other pollutants, and is green and environment-friendly; (2) the comprehensive energy system can comprehensively provide the advantages of different energy supply systems and realize the optimized scheduling of different energy systems; (3) the integrated energy system can integrate the optimized utilization of different energy forms.
In the framework process of the energy flow graph, firstly, the coupling characteristics of the comprehensive energy system are researched, wherein the coupling characteristics comprise the aspects of economy, reliability and the like; secondly, researching the operating characteristics of key equipment in the comprehensive energy system; finally, the transmission characteristics of the comprehensive energy system are researched, and the comprehensive energy system comprises various energy forms such as electricity, heat, gas and the like.
And S2, determining constraint conditions based on the energy flow graph.
When the planning constraint condition of the comprehensive energy system is considered, energy balance constraint and energy interaction constraint among different energy forms are also considered. The method specifically comprises the following steps: energy balance constraints, equipment physics constraints, investment quota constraints, and energy interaction constraints.
Wherein the expression of the energy balance constraint is:
wherein, Pload(t) represents the consumer electrical load, Hload(t) represents a thermal load, Lload(t) represents cooling load in kW; pi(t) represents the supply power of device i; hm(t) represents the heating power of the plant m; l isn(t) represents the cooling power of the plant n.
The expression of the physical constraints of the device is:
wherein, Pi minRepresents the minimum power, P, of the device ii maxRepresenting the maximum power of the equipment i, and the unit is kW; pj(t) represents the real-time output of the equipment i at the moment t, and the unit is kW; SOCminRepresenting a minimum value of the energy generated by the energy storage device; SOCmaxRepresents the maximum value of the residual energy of the energy storage device; soc (t) represents the remaining energy of the energy storage device at time t.
The expression for the investment quota constraint is:
wherein, CinvRepresenting the initial investment amount of the comprehensive energy system;
representing the maximum amount of investment that can be borne by the integrated energy system; cunit_tRepresenting the investment cost of equipment i per unit capacity; qunit_tRepresenting the planned capacity of device i; cLCRepresenting an integrated energy source. The expression of the energy interaction constraint is:
wherein the content of the first and second substances,
representing the minimum value of the exchange power between the power grid and the comprehensive energy system;
representing the maximum value of the exchange power between the power grid and the integrated energy system;
representing the minimum value of the interaction quantity between the natural gas network and the comprehensive energy system;
representing the maximum value of the interaction quantity between the natural gas network and the comprehensive energy system; pgridIndicating the exchange of power, P, between the grid and the integrated energy systemNGRepresenting the amount of interaction between the natural gas grid and the integrated energy system.
And S3, constructing a comprehensive energy system planning model under the optimal planning scheme on the basis of the energy flow diagram and the constraint conditions and on the premise of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency. The method specifically comprises the following steps:
s31, constructing a comprehensive energy system planning model on the premise of considering the lowest comprehensive cost, the lowest carbon emission and the highest comprehensive energy efficiency based on constraint conditions;
s32, generating different planning schemes of the comprehensive energy system planning model based on different characteristics of a supply side, a transmission side and a demand side of an energy flow graph;
and S33, solving the comprehensive energy system planning model under different planning schemes by using a genetic algorithm to obtain an optimal scheme.
In S31, the construction process of the comprehensive energy system planning model is as follows:
respectively constructing objective functions of comprehensive cost, carbon emission and comprehensive energy efficiency; wherein, the objective function of the comprehensive cost is as follows:
F1＝Cfin＝Cequ+Cope+Cmai+Cdep；
wherein, CfinRepresents the minimum value of the annual equivalent comprehensive cost; cequRepresenting the annual cost of initial investment of equipment; copeRepresents the system operating cost; cmaiRepresents the cost of system maintenance; cdepRepresents equipment depreciation cost;
the objective function for carbon emissions is as follows:
wherein, minCcirRepresents the minimum value of carbon emissions; peleRepresenting the purchase amount of the integrated energy system; f. ofgasRepresenting the gas purchasing quantity of the integrated energy system;
carbon dioxide emission coefficient per unit of electricity;
a carbon dioxide emission coefficient representing a unit gas amount;
the objective function of the integrated energy efficiency is as follows:
wherein maxEC represents the maximum value of the comprehensive energy efficiency; ploadRepresenting the electrical load of the integrated energy system, coneleRepresents the power consumption of the integrated energy system; congasRepresenting the gas consumption of the integrated energy system; etagasRepresenting the conversion coefficient of natural gas into electricity as heat.
S33 shown in fig. 3 specifically includes:
s331, initializing data, coding each device related in the comprehensive energy system model to obtain a population, and determining the size of the initial population and the maximum iteration number;
s332, randomly generating an initialization population S with the scale of N;
s333, calculating the individual fitness of the population by using the following formula;
F＝min(F1+F2+F3)；
the objective function is a target value of the economy and the environmental protection of the comprehensive energy system, and can directly reflect the quality of chromosomes, so the objective function is directly selected as a standard for evaluating the fitness. That is to say directly regarding the objective function as a fitness function. The expression of the fitness function of the target function of the individual is as follows:
fit＝min(F)；
the evaluation rule for the fitness of the method is as follows: the smaller the objective function value of an individual is, the higher the fitness function is; conversely, a larger value of the objective function of an individual indicates a lower fitness. fit is the minimum value of the individual fitness function and represents that the individual fitness is the highest.
S334, selecting, crossing and mutating the initialized population S and generating a child population Q of the initialized population S;
s3341, selecting individuals, and randomly selecting two individuals on the premise that the individuals cannot be selected repeatedly;
s3342, selecting a crossing mode, and randomly distributing an individual crossing mode, wherein the operation comprises a row crossing mode and a column crossing mode;
s3343, performing cross operation, namely interchanging columns of the two individuals behind the cross position, and combining to generate two new individuals;
s3344, performing mutation operation on the offspring chromosomes according to the mutation probability Pm, wherein the value of Pm is 0.001-0.1.
S335, calculating economic and environmental target values of the offspring population Q to obtain individual fitness of the offspring population Q;
and S336, selecting the optimal offspring from the mixed population of the parent population and the offspring population, and outputting the optimal scheme when the iteration reaches the maximum iteration times.
And S4, providing guidance suggestions for the planning of the comprehensive energy system based on the comprehensive energy system planning model under the most planning scheme.
In order to verify the effectiveness of the comprehensive energy system planning model, a certain park of China is selected as a case for simulation. As shown in the energy flow chart, the load demand guidance of the comprehensive energy system constructed by the invention is cold, hot and electric loads, so that the cold, hot and electric loads in 8760 hours in the whole year of the park are selected as load data input parameters. The case input parameters also comprise technical and economic parameters of the equipment, energy price and other parameters. Under the condition of satisfying load data of cold, heat and electricity in the park, the mode of 'remaining electricity is not on line and electricity shortage is purchased' is adopted for each investment quota limit, the time scheduling period T is 24h, and the time unit interval delta T is 1 h.
The data required by simulation mainly comprises electric load, thermal load, cold load, energy price, technical and economic parameters of equipment and the like. Annual power load, thermal load and cold load are shown in fig. 4, and the light intensity and wind speed curves are shown in fig. 5.
The technical economic parameters of the equipment are shown in table 1, and the performance coefficients of the equipment are shown in table 2.
TABLE 1 technical economic coefficient of equipment
TABLE 2 Equipment Performance coefficients
| Parameter(s) | Parameter value |
| Coefficient of performance of electric boiler | 0.95 |
| Heating efficiency of gas boiler | 0.90 |
| Heating/cooling efficiency of ground source heat pump | 3.80 |
| Heat storage tank charge-discharge efficiency | 0.90 |
| Energy storage charge-discharge efficiency | 0.95 |
| Self discharge rate of stored energy | 0.05 |
| Coefficient of performance of conventional refrigerating unit | 4.00 |
| Refrigeration coefficient of double-working-condition refrigerating unit | 3.00 |
| Cold storage coefficient of double working condition refrigerating unit | 3.00 |
| Cold charging and discharging coefficient of ice storage tank | 0.98 |
On the basis of the initial data and parameter settings described above, the planning optimization model of the invention was performed in MATLAB R2019b by NWSFA (newton-weighted and frieichi method). The result of the pareto solution is obtained according to 3 objective functions, the population size is set to 200, and feasible solutions of the objective functions in the pareto solution are shown in fig. 6:
from the optimization results, it can be seen that there is an irregularity relationship between the 3 objective functions. When the annual equivalent comprehensive cost is too high or too low, the carbon dioxide emission is higher or lower, and the comprehensive energy efficiency is higher or lower; when the low carbon property is too high or too low, the comprehensive energy efficiency is mostly in the condition of too low. Therefore, if the comprehensive energy system is to realize 3 goals of good economical efficiency, excellent environmental performance and high social benefit, the annual equivalent cost needs to be controlled within a certain range.
Since each solution in the pareto frontier is a feasible solution, the present invention seeks the optimal solution in the multi-objective pareto set using the VIKOR method. In order to verify the accuracy of the sought optimal solution, 3 optimal schemes of a single target are selected to be compared with the optimal result, and the scheme 1 is the optimal scheme under the VIKOR; scheme 2: the scheme with the lowest annual equivalent integrated cost (F1); scheme 3: the lowest carbon emission (F2); scheme 4: the scheme with the highest comprehensive energy efficiency (F3).
The planning results and the equipment capacity configurations of the above 4 cases are shown in tables 3 and 4:
TABLE 3 VIKOR-based planning results
| Annual equivalent integrated cost (yuan) | Carbon emission (kg) | Efficiency of | |
| Scheme | |||
| 1 | 5390374.84 | 3218222.15 | 0.82 |
| |
5371362.99 | 3281319.66 | 0.81 |
| |
5392481.55 | 3218219.12 | 0.82 |
| |
5467335.79 | 3381243.97 | 0.84 |
TABLE 4 Capacity allocation results under different scenarios
In order to check the reliability of the planning model, summer typical day data is selected to perform operation simulation analysis on the scheme 1, and a load curve is shown in fig. 7:
fig. 8 is a typical daily power system supply and demand balance situation. In an electric system, besides a user electric load, energy requirements of a ground source heat pump, a dual-working-condition refrigerator and a conventional refrigerator for cooling and energy requirements of the ground source heat pump and an electric boiler for heating are also required to be met. In the system, the photovoltaic and the fan preferentially supply system loads, and the rest parts are mainly satisfied by a municipal power grid.
Fig. 9 shows the supply and demand balance of the thermal system. Wherein the heat load is satisfied by the ground source heat pump and the gas boiler at 1: 00-7: 00 and 22: 00-24: 00, the heat storage tank preferentially supplies heat at the electricity price of 8: 00-12: 00 peak, and the rest is complemented by the gas boiler.
Fig. 10 shows the supply and demand balance of the cooling system. The system cold load is mainly satisfied by a double-working-condition refrigerating unit and a conventional refrigerating unit, the ice storage tank stores ice at the valley power price and preferentially supplies cold at the peak power price of 08: 00-12: 00.
As shown in fig. 11, as the investment quota increases from 4000 ten thousand yuan to 6000 ten thousand yuan for the energy integration efficiency, an ascending situation is presented; when the investment quota is increased from 4000 ten thousand yuan to 6500 ten thousand yuan, the annual equivalent comprehensive cost of the system shows a descending trend, and when the investment quota is increased from 4000 ten thousand yuan to 7000 ten thousand yuan, the carbon emission of the system shows a descending trend. This is mainly because when the user has abundant fund investment energy equipment, can construct fan, photovoltaic and energy storage equipment of bigger capacity, reduces outside electric quantity of buying, reduces the reliance to external energy network to reduce the carbon emission of system.
And when the investment quota is respectively greater than 6500 ten thousand yuan, 7000 ten thousand yuan and 6000 ten thousand yuan, carrying out sensitivity analysis on the investment quota.
Therefore, the annual equivalent comprehensive cost, the carbon emission and the comprehensive energy efficiency of the system gradually show a stable trend, and the economic benefit, the environmental benefit and the social benefit can not be obviously improved. And it can be seen that, compared with economic benefits and social benefits, environmental benefits are more greatly influenced by investment quota, and meanwhile, reasonable investment requirements of the comprehensive energy system under the scene are between 6000 ten thousand yuan and 7000 ten thousand yuan. Namely, in the face of ubiquitous power internet of things, in the face of income distribution brought by investment, economic benefits and social benefits are paid more attention in an inclined mode to complement short boards. According to the demand of the benefit of the comprehensive energy system planning, in the face of the situation of ubiquitous access to the power network, a comprehensive energy system planning model based on investment quota is provided. The planning results were analyzed as follows:
(1) a preliminary framework is made for the comprehensive energy system planning of the rated investment, and the comprehensive energy planning model is guaranteed to realize economic benefits, environmental benefits and social benefits when being accessed universally.
(2) And optimizing multiple targets such as annual equivalent comprehensive cost, carbon emission, comprehensive energy efficiency and the like, and carrying out sensitivity analysis on the investment quota to obtain the investment quota most suitable for realizing various benefits.
(3) The analysis is carried out from the perspective of investors, and the necessity of considering quota investment conditions during the planning of the comprehensive energy system is explained and analyzed. With the development of the comprehensive energy system and the continuous development and perfection of various price mechanisms, more optimization means are added in the planning of the comprehensive energy system in the future, so that the planning configuration scheme is more economic and environment-friendly.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A planning method for a comprehensive energy system facing multi-element main body access is characterized by comprising the following steps:
constructing an energy flow diagram of the integrated energy system based on basic characteristics of the integrated energy system;
determining constraint conditions based on the energy flow graph;
constructing a comprehensive energy system planning model under an optimal planning scheme on the basis of the energy flow graph and the constraint conditions and on the premise of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency;
and providing guidance suggestions for planning the comprehensive energy system based on the comprehensive energy system planning model under the optimal planning scheme.
2. The method for planning the comprehensive energy system oriented to multi-subject access according to claim 1, wherein the energy flow graph comprises: the coupling of each link of the comprehensive energy system, the operation characteristics of each key device in the comprehensive energy system and the transmission characteristics of various forms of energy in the comprehensive energy system.
3. The method for planning the comprehensive energy system oriented to multi-element subject access according to claim 1, wherein the determining of the constraint condition comprises: energy balance constraints, equipment physics constraints, investment quota constraints, and energy interaction constraints.
4. The method for planning the comprehensive energy system oriented to multi-element subject access according to claim 3, wherein the expression of the energy balance constraint is as follows:
wherein, Pload(t) represents the consumer electrical load, Hload(t) represents a thermal load, Lload(t) represents cooling load in kW; pi(t) represents the supply power of device i; hm(t) represents the heating power of the plant m; l isn(t) represents the cooling power of the plant n.
5. The method for planning the comprehensive energy system oriented to the multi-element subject access according to claim 3, wherein the expression of the physical constraints of the equipment is as follows:
wherein, Pi minRepresents the minimum power, P, of the device ii maxRepresenting the maximum power of the equipment i, and the unit is kW; pj(t) represents the real-time output of the equipment i at the moment t, and the unit is kW; SOCminRepresenting a minimum value of the energy generated by the energy storage device; SOCmaxRepresents the maximum value of the residual energy of the energy storage device; soc (t) represents the remaining energy of the energy storage device at time t.
6. The method for planning the comprehensive energy system oriented to multi-element subject access according to claim 3, wherein the expression of the investment quota constraint is as follows:
wherein, CinvRepresenting the initial investment amount of the comprehensive energy system;
representing the maximum amount of investment that can be borne by the integrated energy system; cunit_tRepresenting the investment cost of equipment i per unit capacity; qunit_tRepresenting devices iPlanning the capacity; cLCRepresenting an integrated energy source.
7. The method for planning the comprehensive energy system oriented to multi-element subject access according to claim 1, wherein the expression of the energy interaction constraint is as follows:
wherein the content of the first and second substances,
representing the minimum value of the exchange power between the power grid and the comprehensive energy system;
representing the maximum value of the exchange power between the power grid and the integrated energy system;
representing the minimum value of the interaction quantity between the natural gas network and the comprehensive energy system;
representing the maximum amount of interaction between the natural gas grid and the integrated energy system.
8. The method for planning the comprehensive energy system oriented to the multi-element main body access according to claim 1, wherein a comprehensive energy system planning model under an optimal planning scheme is constructed on the basis of the energy flow graph and the constraint conditions and on the premise of lowest comprehensive cost, lowest carbon emission and highest comprehensive energy efficiency; the method comprises the following steps:
constructing a comprehensive energy system planning model on the basis of the constraint conditions and taking the lowest comprehensive cost, the lowest carbon emission and the highest comprehensive energy efficiency as the consideration premises;
generating different planning schemes of the comprehensive energy system planning model based on different characteristics of a supply side, a transmission side and a demand side of the energy flow graph;
and solving the comprehensive energy system planning model under the different planning schemes by using a genetic algorithm to obtain an optimal scheme.
9. The method for planning the integrated energy system oriented to multi-element subject access according to claim 8, wherein the integrated energy system planning model is constructed by the following steps:
respectively constructing objective functions of comprehensive cost, carbon emission and comprehensive energy efficiency; wherein, the objective function of the comprehensive cost is as follows:
F1＝Cfin＝Cequ+Cope+Cmai+Cdep；
wherein, CfinRepresents the minimum value of the annual equivalent comprehensive cost; cequRepresenting the annual cost of initial investment of equipment; copeRepresents the system operating cost; cmaiRepresents the cost of system maintenance; cdepRepresents equipment depreciation cost;
the objective function for carbon emissions is as follows:
wherein, minCcirRepresents the minimum value of carbon emissions; peleRepresenting the purchase amount of the integrated energy system; f. ofgasRepresenting the gas purchasing quantity of the integrated energy system;
carbon dioxide emission coefficient per unit of electricity;
a carbon dioxide emission coefficient representing a unit gas amount;
the objective function of the integrated energy efficiency is as follows:
wherein maxEC represents the maximum value of the comprehensive energy efficiency; ploadRepresenting the electrical load of the integrated energy system, coneleRepresents the power consumption of the integrated energy system; congasRepresenting the gas consumption of the integrated energy system; etagasRepresenting the conversion coefficient of natural gas into electricity as heat.
10. The method for planning the comprehensive energy system oriented to multi-element subject access according to claim 9, wherein solving the comprehensive energy system planning model under the different planning schemes by using a genetic algorithm to obtain an optimal scheme comprises:
coding each device related in the comprehensive energy system model to obtain a population, and determining the initial population size and the maximum iteration number;
randomly generating an initialization population S with the scale of N;
calculating the individual fitness of the population by using the following formula;
F＝min(F1+F2+F3)；
fit＝min(F)；
in the above formula, fit is the minimum value of the individual fitness function, and represents that the individual fitness is the highest;
selecting, crossing and mutating the initialization population S and generating a child population Q of the initialization population S;
calculating economic and environmental target values of the offspring population Q to obtain individual fitness of the offspring population Q;
and selecting the optimal offspring from the mixed population of the parent population and the offspring population, and iterating until the maximum iteration times is reached, and outputting the optimal scheme.
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