CN115829142A - Industrial enterprise comprehensive energy system optimization planning method - Google Patents
Industrial enterprise comprehensive energy system optimization planning method Download PDFInfo
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Abstract
The invention relates to an optimization planning method for an industrial enterprise comprehensive energy system, which comprises the following steps: collecting equipment related data of the industrial enterprise comprehensive energy system; determining equipment configuration of the comprehensive energy system based on a multi-party participating subject of the industrial enterprise comprehensive energy system; establishing equipment models and equipment capacity constraints based on equipment configuration of the comprehensive energy system; establishing a multi-subject game model, wherein a non-cooperative game is performed between multi-benefit subjects and industrial enterprise users in the multi-subject game model, and a cooperative game is performed between the multi-benefit subjects; solving a non-cooperative game in the multi-main-body game model based on a KKT-BM method, and determining the equipment capacity and the transaction price of the comprehensive energy system; and (3) solving the cooperative game in the multi-subject game model based on a Shapley value method, and performing benefit distribution on the multi-benefit subjects. Compared with the prior art, the invention considers multi-subject benefit interaction, improves the benefits of each participating subject, enhances the renewable energy consumption capability and can provide stable energy supply for users.
Description
Technical Field
The invention relates to the technical field of optimization planning of an industrial enterprise comprehensive energy system, in particular to an optimization planning method of an industrial enterprise comprehensive energy system based on multi-benefit-subject game.
Background
An industrial integrated energy system relates to the production, transfer and consumption of various energy sources such as electricity, heat, cold, gas and the like. The traditional industrial enterprise power distribution and utilization system lacks effective interaction between a production capacity side and a demand side, so that the problems of resource waste and energy shortage generally exist, and the system operation efficiency and the economic and environmental benefits are greatly influenced. In recent years, with the development of intelligent power distribution and utilization technologies and demand response technologies, a scientific and reasonable interaction mechanism becomes an effective solution for realizing the optimization of industrial enterprise comprehensive users and promoting multi-party interaction, and the method is favorable for better meeting the energy demand of users and reducing the energy cost. Meanwhile, the development of energy Internet and multi-energy complementary technology also provides technical and environmental conditions for interactive response among various energy systems such as electricity, heat, cold and the like.
Due to the fact that the structure of the comprehensive energy system and the flow coupling relation of various energy sources are complex, involved operation main bodies comprise a plurality of energy source subsystems such as an electric power system, a natural gas system and a thermal system, users installed with new energy sources and the like, benefit targets of different main bodies are different, and considered operation constraints are different. The countries encourage social capital to participate in the power market, including various power generation enterprises, power selling enterprises, power users, power trading organizations, power dispatching organizations, independent auxiliary service providers and the like, so as to improve the diversity and competitiveness of the power market main body. The spot market can be divided into an electric energy market, an auxiliary service market, a demand response market and the like from the commodity attribute, and the comprehensive energy system is used as a distribution side role and participates in the spot trading market by means of a superior power grid. Therefore, a reasonable energy transaction mechanism is established, and energy transaction and scheduling strategies with balanced benefits are sought on the basis of ensuring the safe operation of different benefit agents, so that the method is an important basis for ensuring the efficient and reasonable utilization of energy.
At present, many related researches on a multi-interest subject interaction mechanism in an integrated energy system at home and abroad are carried out, a mechanism for transaction among the multi-interest subjects in a series of integrated energy systems is provided, the diversity of energy supply channels in the integrated energy system is greatly improved, the consumption capability of renewable energy of the system is enhanced, and the realization of a double-carbon target is facilitated.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide an optimization planning method for an industrial enterprise comprehensive energy system, which considers multi-subject benefit interaction, improves the benefits of each participating subject, enhances the renewable energy consumption capability and can provide stable energy supply for users.
The purpose of the invention can be realized by the following technical scheme:
an optimization planning method for an industrial enterprise comprehensive energy system comprises the following steps:
collecting equipment related data of the industrial enterprise comprehensive energy system;
determining the equipment configuration of the comprehensive energy system based on a multi-party participation main body of the industrial enterprise comprehensive energy system, wherein the participation main body comprises an energy storage operator, a comprehensive energy operator and an industrial enterprise user, and the energy storage operator and the comprehensive energy operator form a cooperative alliance to serve as a multi-benefit main body;
establishing equipment models and equipment capacity constraints based on the equipment configuration of the comprehensive energy system;
establishing a multi-subject game model, wherein a non-cooperative game is performed between multi-subject and industrial enterprise users in the multi-subject game model, and a cooperative game is performed between the multi-subject;
solving a non-cooperative game in the multi-main-body game model based on a KKT-BM method, and determining the equipment capacity and the transaction price of the comprehensive energy system;
and solving the cooperative game in the multi-subject game model based on a Shapley value method, and performing benefit distribution on the energy storage operator and the comprehensive energy operator.
As a preferred scheme of the present invention, the data related to the industrial enterprise integrated energy device includes annual power and heat load data of industrial enterprise users, gas turbine performance parameters, gas boiler performance parameters, photovoltaic device performance parameters, power storage device performance parameters, heat storage device performance parameters, electric boiler performance parameters, power distribution network time-of-use prices, gas purchase costs, and heat supply network heat prices.
As a preferable aspect of the present invention, the integrated energy system device is configured to: the equipment configuration is related to the subject attributes, and the comprehensive energy operator is an energy producer and consists of a Combined Heat and Power (CHP) unit, a gas boiler and a photovoltaic panel; the energy storage operator is also an energy producer and consists of a hybrid energy storage system, and the hybrid energy storage system specifically comprises an electricity storage device (a storage battery), a heat storage device (a heat storage tank) and an electric boiler; industrial enterprise users are energy consumers and are not equipped with energy supply equipment.
As a preferred embodiment of the present invention, the equipment model is:
wherein the content of the first and second substances,
the total power, kW, generated after the CHP unit burns natural gas is represented; h g The average low heat value of the natural gas is expressed, and 9.97 kW.h/m is taken 3 ；
Represents the inlet air power of the CHP unit, m 3 /h；
Respectively representing the power generation and heat generation of the CHP unit, kW;
represents the electrical efficiency of the CHP unit,%;
representing the thermoelectric ratio of the CHP unit; eta HE Represents heat exchanger efficiency,%;
wherein the content of the first and second substances,
is the power of a gas boiler, kW; eta GB Efficiency of gas boiler,%;
the inlet air power m of the gas boiler 3 /h；
Wherein the content of the first and second substances,
representing the output of photovoltaic power generation, kW; g t Representing hourly solar radiation, kW/m 2 (ii) a λ represents the photovoltaic module power generation efficiency,%; a is the area of the photovoltaic panel, m 2 ；
Wherein the content of the first and second substances,
representing the storage energy of the storage battery during the period t, kWh;
respectively charging and discharging the energy efficiency of the battery by percent;
respectively battery charging power and discharging power, kW; Δ t represents a unit time period, h;
wherein the content of the first and second substances,
representing the heat storage quantity of the heat storage tank during the time period t, kWh;
the heat storage efficiency and the heat release efficiency,%, of the heat storage tank are respectively expressed;
respectively representing heat storage power and heat release power of the heat storage tank, kW; Δ t represents a unit time period, h;
wherein the content of the first and second substances,
the power of the electric boiler is kW; eta EB Represents the electric heat conversion efficiency of the electric boiler,%;
indicating the power consumption of the electric boiler, kW.
As a preferable aspect of the present invention, the device capacity constraint includes:
wherein the content of the first and second substances,
respectively representing the upper limit and the lower limit of the output electric power of the CHP unit, kW;
respectively representing the upper limit and the lower limit of the output force of the gas boiler, kW;
respectively representing the upper limit and the lower limit, kW, of the output electric power of the distributed photovoltaic equipment;
wherein the content of the first and second substances,
the capacity of energy storage equipment at the starting time and the ending time of battery scheduling is respectively represented, and kWh is equal to the capacity of the energy storage equipment at the starting time and the ending time of the battery scheduling, so that the continuity of scheduling is ensured;
the upper limit and the lower limit of the capacity of the power storage equipment, kWh;
respectively representing the upper limit, kW, of the charging and discharging power of the power storage system;
and
the variables are 0-1 respectively representing the charging and discharging states of the energy storage system;
represents the charging and discharging power of the electricity storage system, positive represents discharging, negative represents charging, kW;
wherein the content of the first and second substances,
respectively representing the capacities of energy storage equipment at the dispatching starting time and the dispatching finishing time of the heat storage tank, wherein the balance between the capacities is the continuity of dispatching;
respectively representing the upper and lower limits of the capacity of the heat storage equipment, kWh;
respectively representing the upper limits of the heat storage power and the heat release power of the heat storage system, kW;
and
the variable is 0-1 respectively representing the heat storage and release states of the energy storage system;
the heat storage system is used for storing and releasing heat, positive represents heat release, negative represents heat storage and kW;
wherein the content of the first and second substances,
indicating the rated capacity of the electric boiler, kW.
As a preferred scheme of the present invention, in a multi-party participating subject of the integrated energy system, the interaction mechanism of the multi-party participating subject is:
in the comprehensive energy system, each main body has the capability of autonomous selection and autonomous regulation in the transaction process. Different energy conversion devices and market trading bodies, and the energy management mechanism and the information sharing and other elements in the trading process form a multi-body interaction mechanism of the system. The types of market exchange subjects include two categories, energy producer attributes and energy consumer attributes: energy producers reasonably make energy quotations according to the energy demands of users; energy consumers reasonably arrange own energy consumption strategies according to energy quotations of all parties;
in the integrated energy system, an integrated energy service provider and an energy storage operator, namely an energy producer, cooperate and play among the integrated energy service provider and the energy storage operator to form a cooperation alliance, and a uniform energy selling price is formulated to supply energy to energy consumers, namely industrial enterprise users. And the final benefits of the cooperation game of the comprehensive energy service provider and the energy storage operator are distributed by a Shapley value method. The industrial enterprise users are energy consumers, and complete information dynamic games are played between energy producers and energy consumers, namely master-slave games, wherein the producers are leaders and the consumers are followers. The producer carries out pricing according to the load demand of the consumer, then the consumer makes the energy ordering strategy according to the energy price and the objective function to the maximum, and the energy supply side adjusts the equipment capacity according to the energy ordering condition of the user to carry out reasonable planning, thereby achieving the optimal benefit. The producer and the consumer carry out non-cooperative game, solve the non-cooperative game by a KKT-BM method, and obtain the capacity and the energy transaction price of each device, and further obtain the specific outsourcing energy quantity and the output condition of each device.
As a preferable scheme of the invention, the multi-principal gaming model comprises objective functions of multi-principal benefits, objective functions of industrial enterprise users, non-cooperative gaming constraints and cooperative gaming constraints.
As a preferred scheme of the invention, the objective function of the multi-interest subject is as follows:
wherein: pi p The benefit function of the cooperative alliance formed by the energy supply side comprehensive energy service provider and the energy storage operator is represented, and is a difference value between income obtained by selling energy to a user at a demand side and expenses such as equipment investment cost, operation cost and the like;
representing energy supply side energy selling benefit;
the annual average investment cost of equipment on the energy supply side is represented;
representing the cost of energy purchase from an external network on the energy supply side;
representing annual operation and maintenance cost of energy supply side equipment;
wherein s is the typical day; s is a typical number of days, representing several typical days with obvious seasonality in a year (summer/transition season/winter typical days); d s Days, days of the s typical day; t is a scheduling period, and 24h is taken; delta t is a scheduling time interval and is taken as 1h; p is a radical of e,t 、p h,t Respectively representing unit electricity price and heat price, yuan/kWh, of energy sold by the energy supply side to industrial enterprise users; w e ,t 、W h,t Respectively representing the actual electric load and the actual heat load, kW, of the industrial enterprise user;
wherein, the initial investment cost of the equipment is converted to each year through an annual equal investment conversion coefficient; k is the equipment type owned by the comprehensive energy service provider and the energy storage operator; k is the number of device types; alpha is alpha k Is the unit capacity installation cost of equipment k, yuan/kW;
is the installation capacity of the equipment k, kW; r is annual rate,%; y is k The operating life of the equipment k is year;
wherein p is g Expressing the price per unit of natural gas, yuan/m 3 ；
Representing an integrated energy facilitatorTotal intake power per unit time period, m 3 /h；
The time-of-use electricity price of the power distribution network is expressed, yuan/kWh;
indicating that the power supply side distributes the electric power purchased by the power grid, kW;
represents the heat rate of the heat net, yuan/kWh;
power, kW, representing the power at which the energy supply side purchased heat to the hot wire;
wherein the content of the first and second substances,
respectively representing the unit capacity operation and maintenance cost, yuan/kWh, of the CHP unit, the gas boiler and the distributed photovoltaic power generation of the comprehensive energy service provider;
respectively representing the operation and maintenance costs of a storage battery, a heat storage tank and an electric boiler of an energy storage operator, unit/kWh;
respectively show the output of comprehensive energy service provider CHP unit, gas boiler and distributed photovoltaic equipment, kW.
As a preferred scheme of the invention, the objective function of the industrial enterprise user is as follows:
wherein, F u A utility function for industrial enterprise users;
wherein: ae. be respectively represents preference constants of the electric energy consumption of the industrial enterprise users; ah. bh respectively represents preference constants of heat energy consumption of industrial enterprise users; these constants are associated with the performance characteristics of different users and can affect the demand response capabilities of the users.
As a preferred scheme of the invention, the non-cooperative game constraint conditions comprise an electric balance constraint, a thermal balance constraint, a demand response constraint, an energy storage device operation constraint and a user transaction price constraint:
the electrical balance constraints include:
wherein:
indicating that the power is directly sold to a user part in the power purchasing of the power grid, namely kW;
indicating that the power grid purchases electricity for selling to an energy storage operator part, namely kW;
the thermal equilibrium constraints include:
the demand response constraints include:
wherein:
representing the fixed electrical load of the user, i.e. the electrical load required to maintain the normal operation of the user, kW;
representing that a user can translate the load in a time period t, and adjusting based on the real-time energy price, kW;
a numerical upper limit, kW, representing the user's translatable electrical load;
representing the total amount of the translatable electric load, kW, in the T period of the user;
the energy storage device operational constraints include:
wherein:
representing that the electricity purchasing power is used for a storage battery charging part, kW;
if t is in the valley period, then there are:
if t is in the peak time period, the energy storage operator does not purchase electricity to the power distribution network, then:
the energy trading price constraints include:
wherein:
respectively representing minimum and maximum value constraints of electricity price sold to users by the energy supply side, yuan/kWh;
represents the upper limit of the average electricity price, yuan/kWh.
As a preferred solution of the present invention, the cooperative game constraint conditions are:
according to the cooperative game idea, the interest appeal of the main body participating in the industrial enterprise comprehensive energy system is divided into an individual rationality part and a collective rationality part: for a cooperative alliance with distributed profit, the overall profit of the cooperative alliance is not less than the sum of individual profits before the alliance, namely, the collective rationality; the benefit of individuals participating in the cooperation must be better than the individual benefit before cooperation, i.e., individuality. If and only if each participant in the cooperative alliance S meets the above requirements, the cooperative alliance can be established; accordingly, the constraint conditions of the cooperative game of the comprehensive energy service provider and the energy storage operator are as follows:
wherein: v (i) represents the revenue, element, allocated by the participating principal i in the cooperative federation G; u (i) represents revenue, dollars, for participating in the independent operation of principal i;
wherein: u shape CO Representing the total revenue of the cooperative alliance; n represents the number of participating agents.
As a preferred scheme of the present invention, the solving of the non-cooperative game based on the KKT-BM method includes:
the KKT-BM conversion method is characterized in that a target function of a user is converted into a constraint condition of an energy supply side, so that double-layer optimization conversion is based on nonlinear programming of a KKT condition, and a specific expression is as follows:
wherein: l is GU A Lagrangian function representing an industrial enterprise user construct; theta e, theta esu and mu e respectively represent dual variables introduced by a KKT condition, wherein theta e and theta esu respectively represent Lagrange multipliers corresponding to inequality constraints, and mu e represents Lagrange multiplication corresponding to equality constraintsCounting; "a ≠ b" means a ≧ 0, b ≧ 0, a × b =0;
because complementary constraints are nonlinear, all convex optimization is needed, and the original nonlinear expression is converted into mixed integer linear programming constraints by introducing a variable of 0-1 by using a Big-M transformation method, which is specifically represented as the following formula:
wherein: beta is a θe 、β θesu Representing a variable from 0 to 1, wherein M is a positive number which is large enough, and the constraint linearization of the type can be realized by using a large M method, so that a linear single-layer model of the non-cooperative game is finally obtained;
at the same time, the user can select the desired position,
according to the KKT condition, the dual variable is used for converting the dual variable into a secondary term, and the secondary term is specifically shown as the following formula:
after the conversion, the nonlinear terms in the game are only secondary terms, a KKT-BM method is utilized to equivalently convert a double-layer game model into a single-layer mixed integer nonlinear programming problem, and the equipment capacity and the transaction price of the comprehensive energy system are solved and determined.
As a preferred aspect of the present invention, the allocating benefits to each participating subject in the cooperative alliance based on the sharley value method includes:
wherein:
representing the benefit that participant i should be allocated; (| G | -1) |! Ranking aggregate when representing coalition of participantsA number where G represents the number of partial participants, and the remaining (n-G) participants are ordered by (n-G |)! In the method for preparing the seed coating,
dividing different sorting combinations representing the participation of each participant in the cooperation by the random sorting of n participants to obtain the weight occupied by each participant; v (G) represents the benefit of federation G when participant i participates in the collaboration; v (G \ i }) represents the benefit of federation G in removing participant i; v (G) -v (G \ i }) represents the marginal contribution of participant i participating in the creation of a different federation G.
Compared with the prior art, the invention has the following beneficial effects:
the optimization planning method for the industrial enterprise comprehensive energy system based on the multi-interest-subject game is provided, multi-subject interest interaction is considered, benefits of all participating subjects are improved, the renewable energy consumption capability is enhanced, stable energy supply can be provided for users, the problem that only a single energy supply operator is considered for supplying energy to the users in the prior art is solved, the industrial enterprise comprehensive energy system based on the multi-interest-subject game is considered, and therefore the optimal equipment configuration scheme for the industrial enterprise comprehensive energy system considering multi-interest fairness is achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor. Wherein:
FIG. 1 is a multi-benefit agent interaction diagram of a method for optimizing and planning an industrial enterprise integrated energy system according to an embodiment of the present invention;
fig. 2 is a diagram of a multi-interest-subject game model of an industrial enterprise integrated energy system according to an embodiment of the present invention;
fig. 3 is a time-by-time thermoelectric load diagram of a typical day of an industrial enterprise according to an embodiment of the present invention;
fig. 4 is a model solution flowchart of an industrial enterprise integrated energy system optimization planning method according to an embodiment of the present invention;
fig. 5 is a diagram illustrating a typical summer solar power output balance under the optimal operation of the system of the method for optimizing and planning an industrial enterprise comprehensive energy system according to an embodiment of the present invention;
fig. 6 is a typical daily electricity output balance diagram in a transition season under the optimal operation of the system of the industrial enterprise integrated energy system optimization planning method according to an embodiment of the present invention;
fig. 7 is a diagram illustrating typical daily output balance in winter under optimal operation of the system of the method for optimally planning the integrated energy system of the industrial enterprise according to an embodiment of the present invention;
fig. 8 is a time-of-use electricity price chart of an industrial user of the method for optimizing and planning an industrial enterprise integrated energy system according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and it will be readily apparent to those of ordinary skill in the art that the present invention may be practiced without departing from the spirit and scope of the present invention.
Furthermore, the references herein to "one embodiment" or "an embodiment" refer to a particular feature, structure, or characteristic that may be included in at least one implementation of the present invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention.
Example 1:
referring to fig. 1 and fig. 2, the invention provides an optimization planning method for an industrial enterprise integrated energy system, comprising the following steps:
s1, collecting relevant data of equipment of an industrial enterprise comprehensive energy system, and analyzing annual electricity and heat load of a user;
it should be noted that: the system comprises annual power and heat load data of industrial enterprise users, gas turbine performance parameters, gas boiler performance parameters, photovoltaic equipment performance parameters, power storage device performance parameters, heat storage device performance parameters, power boiler performance parameters, power grid time-of-use electricity price, heat grid time-of-use heat price and gas purchase cost, wherein 1 typical daily load data in each quarter is selected as key load analysis when the annual power and heat load of the industrial enterprise users is analyzed.
S2, determining equipment configuration of the comprehensive energy system based on a multi-party participation subject of the industrial enterprise comprehensive energy system; the participation main body of the industrial enterprise comprehensive energy system comprises an energy storage operator, a comprehensive energy operator and an industrial enterprise user, and the energy storage operator and the comprehensive energy operator form a cooperative union to serve as a multi-benefit main body;
the equipment configuration is related to the subject attributes, and the comprehensive energy operator is an energy producer and consists of a Combined Heat and Power (CHP) unit, a gas boiler and a photovoltaic panel; the energy storage operator is also an energy producer and consists of a hybrid energy storage system, and the hybrid energy storage system specifically comprises an electricity storage device (a storage battery), a heat storage device (a heat storage tank) and an electric boiler; industrial enterprise users are energy consumers and are not equipped with energy supply equipment.
S3, establishing each equipment model and equipment capacity constraint based on the equipment configuration of the comprehensive energy system;
wherein, the equipment model includes:
(1) Combined Heat and Power (CHP) unit
Wherein the content of the first and second substances,
the total power, kW, generated after the CHP unit burns natural gas is represented; h g The average low heat value of the natural gas is expressed, and 9.97 kW.h/m is taken 3 ；
Represents the intake power of the CHP unit, m 3 /h；
Respectively representing the power generation and heat generation of the CHP unit, kW;
represents the electrical efficiency of the CHP unit,%;
represents the thermoelectric ratio of the CHP unit; eta HE Represents heat exchanger efficiency,%;
(2) Gas boiler
Wherein the content of the first and second substances,
is the power of a gas boiler, kW; eta GB Efficiency of gas boiler,%;
for the inlet power of a gas boiler, m 3 /h；
(3) Photovoltaic panel
Wherein the content of the first and second substances,
expressing the output of photovoltaic power generation, kW; g t Representing hourly solar radiation, kW/m 2 (ii) a λ represents the photovoltaic module power generation efficiency,%; a is the area of the photovoltaic panel, m 2 ；
(4) Electricity storage equipment (accumulator)
Wherein the content of the first and second substances,
representing the storage energy of the storage battery during the period t, kWh;
respectively charging and discharging the energy efficiency of the battery by percent;
battery charging power and discharging power, kW, respectively; Δ t represents a unit time period, h;
(5) Heat-storage equipment (Heat storage pot)
Wherein the content of the first and second substances,
representing the heat storage quantity of the heat storage tank during the time period t, kWh;
the heat storage efficiency and the heat release efficiency,%, of the heat storage tank are respectively expressed;
respectively representing heat storage power and heat release power of the heat storage tank, kW; Δ t represents a unit time period, h;
(6) Electric boiler
Wherein the content of the first and second substances,
the power of the electric boiler is kW; eta EB Represents the electric heat conversion efficiency of the electric boiler,%;
indicating the power consumption of the electric boiler, kW.
The device capacity constraints include:
(1) Comprehensive energy operator
Wherein the content of the first and second substances,
respectively representing the upper limit and the lower limit of the output electric power of the CHP unit, kW;
respectively representing the upper limit and the lower limit of the output force of the gas boiler, kW;
respectively representing the upper limit and the lower limit, kW, of the output electric power of the distributed photovoltaic equipment;
(2) Energy storage operator
Wherein the content of the first and second substances,
the capacity of energy storage equipment at the starting time and the ending time of battery scheduling is respectively represented, and kWh is equal to the capacity of the energy storage equipment at the starting time and the ending time of the battery scheduling, so that the continuity of scheduling is ensured;
the upper limit and the lower limit of the capacity of the power storage equipment, kWh;
respectively representing the upper limit, kW, of the charging and discharging power of the power storage system;
and
0-1 variable respectively representing charging and discharging states of the energy storage system;
represents the charge-discharge power of the electricity storage system, positive represents discharge, negative represents charge, kW;
wherein the content of the first and second substances,
respectively representing the capacities of energy storage equipment at the dispatching starting time and the dispatching finishing time of the heat storage tank, wherein the balance between the capacities is the continuity of dispatching;
respectively representing the upper and lower limits of the capacity of the heat storage equipment, kWh;
respectively representing the upper limits of the heat storage power and the heat release power of the heat storage system, kW;
and
the variable is 0-1 respectively representing the heat storage and release states of the energy storage system;
the heat storage system stores and releases heat, positive means releases heat, negative means stores heat, kW;
wherein the content of the first and second substances,
indicating the rated capacity of the electric boiler, kW.
S4, establishing a multi-subject game model, wherein a non-cooperative game is performed between multi-benefit subjects and industrial enterprise users in the multi-subject game model, and a cooperative game is performed between the multi-benefit subjects;
in the multi-party participation main body of the comprehensive energy system, the interaction mechanism of the multi-party participation main body is as follows:
in the comprehensive energy system, each main body has the capability of autonomous selection and autonomous regulation in the transaction process. Different energy conversion devices and market trading bodies, and the energy management mechanism and the information sharing and other elements in the trading process form a multi-body interaction mechanism of the system. The types of market exchange subjects include two categories, energy producer attributes and energy consumer attributes: energy producers reasonably make energy quotations according to the energy demands of users; energy consumers reasonably arrange own energy consumption strategies according to energy quotations of all parties;
in the integrated energy system, an integrated energy service provider and an energy storage operator, namely an energy producer, cooperate and play among the integrated energy service provider and the energy storage operator to form a cooperation alliance, and a uniform energy selling price is formulated to supply energy to energy consumers, namely industrial enterprise users. And the final benefits of the cooperation game of the comprehensive energy service provider and the energy storage operator are distributed by a Shapley value method. The industrial enterprise users are energy consumers, and complete information dynamic games are played between energy producers and energy consumers, namely master-slave games, wherein the producers are leaders and the consumers are followers. The producer carries out pricing according to the load demand of the consumer, then the consumer makes the energy ordering strategy according to the energy price and the objective function to the maximum, and the energy supply side adjusts the equipment capacity according to the energy ordering condition of the user to carry out reasonable planning, thereby achieving the optimal benefit. And (3) carrying out non-cooperative game on the producer and the consumer, solving the non-cooperative game by a KKT-BM method to obtain the capacity and the energy transaction price of each device, and further obtaining the specific outsourcing energy quantity and the output condition of each device.
Therefore, in the established multi-principal game model, the non-cooperative game between the multi-principal and the industrial enterprise users and the cooperative game between the multi-principal are established. The multi-principal game model comprises objective functions of multi-principal interests, objective functions of industrial enterprise users, non-cooperative game constraint conditions and cooperative game constraint conditions.
Firstly, performing master-slave game balance existence certification:
the cooperation alliance formed by the multi-interest bodies is a leader in a non-cooperation game, has the pricing right of energy and is an energy supply side, namely a supply side; the industrial enterprise user is a follower, and adjusts own energy utilization strategy for a demand side, also called an energy utilization side, according to the energy price published by an energy supply side. In the primary and secondary games, solving the Nash equilibrium solution is the final purpose of the non-cooperative game and is also the theoretical verification of the research result. The equilibrium solution means that when all participants obtain the equilibrium solution strategy, any participant cannot promote self interest by only changing own strategy, namely, the equilibrium strategy is the strategy that each rational participant benefits the most under a certain environment.
When Nash equilibrium exists in the game model, the definition of Nash equilibrium indicates that (h) * ,z * ) The game model is an equilibrium solution of the game model, namely an equilibrium solution H on the energy supply side and a strategy Z on the user side. The benefits of both parties can reach the optimum value of Nash equilibrium meaning. Let H, Z be the tight subset of the metric space, and Z be the non-null convex set of the metric space, it can be known that when the master-slave game satisfies the following conditions at the same time, the game equilibrium exists:
(1)π u is a continuous convex function with respect to policy set Z;
(2)π u is about W e,t A quasi-convex function of (a);
(3)π p is a continuity function with respect to policy set H;
firstly, conditions (1) and (3) are proved, because the objective function of the energy supply side is the difference value between income and expenditure, the benefit function of an industrial enterprise user is calculated according to the utility function and the objective function, the continuity of the two variables is obvious, nash equilibrium is proved to exist, and whether the second condition is met or not is mainly proved.
By definition "a function pi (x) is defined in the open interval W, if
With pi [ rx ] 1 +(1-r)x 2 ]≤rπ(x 1 )+(1-r)π(x 2 ) Then, it is called pi (x) to be a convex function or a downward convex function in the interval W. "by deductive calculation,. Pi u Satisfy the convex function characteristic in the definition, with respect to W e,t A quasi-convex function of (a).
In conclusion, the demand side users have unique optimal response to the energy price, and all strategy sets participating in the game are non-empty and compact, so that a master-slave game equilibrium solution for energy transaction between the energy supply side users and the demand side users exists.
(1) The objective function for the multi-benefit agent is:
wherein: pi p The benefit function of the cooperative alliance formed by the energy supply side comprehensive energy service provider and the energy storage operator is represented, and is a difference value between income obtained by selling energy to a user at a demand side and expenses such as equipment investment cost, operation cost and the like;
representing energy supply side energy selling benefit;
the annual average investment cost of equipment on the energy supply side is represented;
representing the cost of energy purchase from an external network on the energy supply side;
representing annual operation and maintenance cost of energy supply side equipment;
wherein s is the typical day; s is a typical number of days, representing several typical days with obvious seasonality in a year (summer/transition season/winter typical days); d s Days, of the s typical day; t is a scheduling period, and 24h is taken; delta t is a scheduling time interval and is taken as 1h; p is a radical of e,t 、p h,t Respectively representing unit electricity price and heat price, yuan/kWh, of energy sold by an energy supply side to industrial enterprise users; w e ,t 、W h,t Respectively representing the actual electric load and the actual heat load, kW, of the industrial enterprise user;
wherein, the initial investment cost of the equipment is converted to each year through an annual equal investment conversion coefficient; k is the equipment type owned by the comprehensive energy service provider and the energy storage operator; k is the number of device types; alpha is alpha k Is the unit capacity installation cost of equipment k, yuan/kW;
is the installation capacity of the equipment k, kW; r is annual rate,%; y is k Is the operating life of the equipment k, years;
wherein p is g Expressing the price per unit of natural gas, yuan/m 3 ；
Represents the total intake power m of the integrated energy service provider in unit time period 3 /h；
Representing the time-of-use electricity price of the power distribution network, yuan/kWh;
indicating that the power supply side distributes the electric power purchased by the power grid, kW;
represents the heat rate of the heat net, yuan/kWh;
indicating heat purchase from the side of the energy supply to the hot-wirePower, kW;
wherein the content of the first and second substances,
respectively representing the unit capacity operation and maintenance cost, yuan/kWh, of the CHP unit, the gas boiler and the distributed photovoltaic power generation of the comprehensive energy service provider;
respectively representing the operation and maintenance costs of a storage battery, a heat storage tank and an electric boiler of an energy storage operator, unit/kWh;
and the output power, kW, of the CHP unit, the gas boiler and the distributed photovoltaic equipment of the comprehensive energy service provider is respectively expressed.
(2) The objective function of the industrial enterprise user is as follows:
wherein, F u A utility function for industrial enterprise users;
wherein: ae. be respectively represents preference constants of the electric energy consumption of the industrial enterprise users; ah. bh respectively represents preference constants of heat energy consumption of industrial enterprise users; these constants are associated with the performance characteristics of different users and can affect the demand response capabilities of the users.
(3) The non-cooperative game constraint conditions comprise an electric balance constraint, a thermal balance constraint, a demand response constraint, an energy storage device operation constraint and a user transaction price constraint:
the electrical balance constraints include:
wherein:
indicating that the power is directly sold to a user part in the power purchasing of the power grid, namely kW;
indicating that the power grid purchases power and sells the power to an energy storage operator part, namely kW;
the thermal equilibrium constraints include:
the demand response constraints include:
wherein:
representing the user's identityDetermining the electric load, namely maintaining the electric load, kW, required by normal operation of a user;
representing that a user can translate the load in a time period t, and adjusting based on real-time energy price, kW;
a numerical upper limit, kW, representing the user's translatable electrical load;
representing the total amount of the translatable electric load, kW, in the T period of the user;
energy storage device operational constraints include:
wherein:
indicating that the electricity purchasing power is used for a storage battery charging part, kW;
if t is in the valley period, then there are:
if t is in the peak time period, the energy storage operator does not purchase electricity from the power distribution network, and the following steps are performed:
the energy trading price constraints include:
wherein:
respectively representing minimum and maximum value constraints of electricity price sold to users by the energy supply side, yuan/kWh;
represents the upper limit of the average electricity price, yuan/kWh.
(4) The constraint conditions of the cooperative game are as follows:
according to the cooperative game idea, the interest appeal of the main body participating in the industrial enterprise comprehensive energy system is divided into an individual rationality part and a collective rationality part: for a cooperative alliance with distributed profit, the overall profit of the cooperative alliance is not less than the sum of individual profits before the alliance, namely, the collective rationality; the benefit of individuals participating in the cooperation must be better than the individual benefit before cooperation, i.e., individuality. If and only if each participant in the cooperative alliance S meets the above requirements, the cooperative alliance can be established; accordingly, the constraint conditions of the cooperative game of the comprehensive energy service provider and the energy storage operator are as follows:
wherein: v (i) represents the revenue, element, allocated by the participating principal i in the cooperative federation G; u (i) represents revenue, dollars, for participating in the independent operation of principal i;
wherein: u shape CO Representing the total revenue of the cooperative alliance; n represents the number of participating agents.
S5, solving a non-cooperative game in the multi-main-body game model based on a KKT-BM method, and determining the equipment capacity and the transaction price of the comprehensive energy system;
it should be noted that: solving the non-cooperative game based on a KKT-BM method to obtain the capacity of each device, wherein the energy transaction price of the result can be taken as an influence factor to obtain the specific outsourcing energy quantity of an energy supply side and the output condition of the device in unit time;
the KKT-BM conversion method is characterized in that a target function of a user is converted into a constraint condition of an energy supply side, so that double-layer optimization conversion is based on nonlinear programming of a KKT condition, and a specific expression is as follows:
wherein: l is a radical of an alcohol GU A Lagrangian function representing an industrial enterprise user construct; theta e, theta esu and mu e respectively represent dual variables introduced by a KKT condition, wherein the theta e and the theta esu respectively represent Lagrange multipliers corresponding to inequality constraints, and the mu e represents Lagrange multipliers corresponding to equality constraints; "a ≠ b" means a ≧ 0, b ≧ 0, a × b =0;
because complementary constraints are nonlinear, all convex optimization is needed, and the original nonlinear expression is converted into mixed integer linear programming constraints by introducing a variable of 0-1 by using a Big-M transformation method, which is specifically represented as the following formula:
wherein: beta is a θe 、β θesu Represents a variable of 0 to 1, M is oneThe positive number is large enough, the type can be subjected to constraint linearization by using a large M method, and a linear single-layer model of the non-cooperative game is finally obtained;
at the same time, the user can select the desired position,
according to the KKT condition, the dual variable is used for converting the dual variable into a secondary term, and the secondary term is specifically shown as the following formula:
after the conversion, the nonlinear terms in the game are only secondary terms, a KKT-BM method is utilized to equivalently convert a double-layer game model into a single-layer mixed integer nonlinear programming problem, and the equipment capacity and the transaction price of the comprehensive energy system are solved and determined.
S6, solving a cooperative game in the multi-subject game model based on a Shapley value method, and performing benefit distribution on an energy storage operator and a comprehensive energy operator, specifically comprising the following steps:
wherein:
representing the benefit that participant i should be allocated; (| G | -1) |! Represents the total number of ranks each participant engaged in the coalition, where | G | represents the number of partial participants and the remaining (n- | G |) participants have ranks of (n- | G |) |. In the method for preparing the seed coating,
dividing different sequencing combinations for representing the participation of each participant in the cooperation by the random sequencing of n participants to obtain the weight occupied by each participant; v (G) represents the benefit of federation G when participant i participates in the collaboration; v (S \ i }) represents the benefit of federation G in removing participant i; v (G) -v (G \ i }) represents that participant i participates in the marginal tributes created by different alliances GA document is presented.
Example 2:
in order to verify and explain the technical effect of the method, the embodiment selects load data of an industrial enterprise to perform simulation modeling so as to verify the real effect of the method.
In this embodiment, a certain industrial enterprise in the sea is a research object, and a configuration planning analysis is performed on the comprehensive energy system of the multi-benefit-subject game based on the established model, the electricity price of the comprehensive energy system adopts the time-of-use electricity price of a single system of general industry and commerce, the electricity price has the power price in summer and non-summer, a thermoelectric load curve of the industrial enterprise on a typical day is shown in fig. 3, specific equipment parameters are shown in table 1, and equipment investment cost and maintenance cost are specifically shown in table 2.
Table 1: device technology parameter table.
Table 2: equipment investment and operation and maintenance costs.
| Device | Investment cost (Yuan/kW) | Operation and maintenance cost (Yuan/kW. H) |
| Cogeneration of heat and electricity | 8000 | 0.2079 |
| Gas boiler | 800 | 0.08 |
| Photovoltaic device | 6300 | 0.06 |
| |
1000 | 0.04 |
| Storage battery | 1400 | 0.029 |
| Heat storage tank | 35 | 0.00536 |
3 typical scenes are set in the case, wherein the scene 1 is that a comprehensive energy service provider independently supplies energy to industrial enterprises, and an energy storage operator does not participate in energy supply; scenario 2 is that an energy storage operator independently supplies energy to an industrial enterprise, and a comprehensive energy service provider does not participate in energy supply; scenario 3 is that the comprehensive energy service provider and the energy storage operator form a cooperative union to supply energy to the industrial enterprises. The specific solving flow of the model is shown in fig. 4.
Based on the parameter setting, the optimization model constructed by the invention is applied to establish the configuration of the equipment at the supply side under 3 typical scenes, and the planning capacity and the optimal benefit of the equipment under different scenes are obtained by operation, which is specifically shown in table 3. From table 3, it is apparent that the net profit of the supply-side cooperative alliance is larger than the profit of the sum of the independent energy supply operation, the cooperative alliance is established, and further benefit distribution is performed by the sharley value method, so that the net profit of the IEO (integrated energy service provider) in the cooperative alliance is 251.04 ten thousand yuan, the net profit of the ESO (energy storage provider) is 3.60 ten thousand yuan, and the growth rates are 5.99% and 5.88%, respectively.
Table 3: and (4) optimizing configuration of equipment and a benefit result table under different scenes.
Based on the system configuration, the cooperation of the supply sides can bring greater benefits, and although the equipment investment is obviously increased compared with the other two scenarios, the benefit brought by the investment is also obviously increased. As can be seen from the typical daily electric balance diagrams in fig. 5 to fig. 7, the electric load of the industrial enterprise does not change much all the year around, the demand is relatively stable, and the demand response is not obvious because the fixed load ratio required by the industrial enterprise to maintain normal operation is large. Accordingly, the power transaction between the supply and demand sides is a time-sharing power selling price close to the power distribution network, as shown in fig. 8.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. An optimization planning method for an industrial enterprise comprehensive energy system is characterized by comprising the following steps:
collecting equipment related data of the industrial enterprise comprehensive energy system;
determining the equipment configuration of the comprehensive energy system based on a multi-party participating main body of the industrial enterprise comprehensive energy system, wherein the participating main body comprises an energy storage operator, a comprehensive energy operator and an industrial enterprise user, and the energy storage operator and the comprehensive energy operator form a cooperative union to serve as a multi-benefit main body;
establishing equipment models and equipment capacity constraints based on the equipment configuration of the comprehensive energy system;
establishing a multi-subject game model, wherein a non-cooperative game is performed between multi-subject and industrial enterprise users in the multi-subject game model, and a cooperative game is performed between the multi-subject;
solving a non-cooperative game in the multi-main-body game model based on a KKT-BM method, and determining the equipment capacity and the transaction price of the comprehensive energy system;
and solving the cooperative game in the multi-main-body game model based on a Shapley value method, and performing benefit distribution on the energy storage operator and the comprehensive energy operator.
2. The method according to claim 1, wherein the equipment model is:
wherein the content of the first and second substances,
representing the total power generated by the CHP unit after natural gas combustion; h g Represents the average lower heating value of natural gas;
representing the inlet air power of the CHP unit;
respectively representing electricity generation power and heat generation power of the CHP unit;
representing the electrical efficiency of the CHP unit;
representing the thermoelectric ratio of the CHP unit; eta HE Represents the heat exchanger efficiency;
wherein the content of the first and second substances,
is the gas boiler power; eta GB To gas boiler efficiency;
the gas inlet power of the gas boiler is obtained;
wherein the content of the first and second substances,
representing the output of photovoltaic power generation; g t Representing time-wise solar radiation; lambda represents the generating efficiency of the photovoltaic module; a is the area of the photovoltaic panel;
wherein the content of the first and second substances,
representing the energy storage capacity of the storage battery in the t period;
respectively charging and discharging the energy of the battery;
charging power and discharging power for the battery respectively; Δ t represents a unit time period;
wherein the content of the first and second substances,
representing the heat storage quantity of the heat storage tank in the time period t;
respectively representing the heat storage efficiency and the heat release efficiency of the heat storage tank;
respectively representing the heat storage power and the heat release power of the heat storage tank; Δ t represents a unit time period;
wherein, the first and the second end of the pipe are connected with each other,
representing the heat production power of the electric boiler; eta EB The electric heat conversion efficiency of the electric boiler is shown;
representing the consumed electrical power of the electrical boiler.
3. The method of claim 1, wherein the equipment capacity constraint comprises:
wherein the content of the first and second substances,
respectively representing the upper limit and the lower limit of the output electric power of the CHP unit;
respectively representing the upper limit and the lower limit of the output force of the gas boiler;
respectively representing the upper limit and the lower limit of the output electric power of the distributed photovoltaic equipment;
wherein, the first and the second end of the pipe are connected with each other,
respectively representing the capacities of energy storage equipment at the starting time and the ending time of battery scheduling;
respectively the upper limit and the lower limit of the capacity of the power storage equipment;
respectively representing the upper limits of the charging power and the discharging power of the power storage system;
and
0-1 variable respectively representing charging and discharging states of the energy storage system;
represents the charge-discharge power of the electricity storage system, positive represents discharge, and negative represents charge;
wherein the content of the first and second substances,
respectively representing the capacities of the energy storage equipment at the dispatching starting time and the dispatching ending time of the heat storage tank;
respectively representing the upper limit and the lower limit of the capacity of the heat storage equipment;
respectively representing the upper limit of the heat storage power and the upper limit of the heat release power of the heat storage system;
and
the variable is 0-1 respectively representing the heat storage and release states of the energy storage system;
the heat storage system is used for storing and releasing heat, positive represents heat release, and negative represents heat storage;
wherein the content of the first and second substances,
indicating the rated capacity of the electric boiler.
4. The method of claim 1, wherein the multi-principal gaming model comprises objective functions of multi-principals, objective functions of industrial enterprise users, non-cooperative gaming constraints, and cooperative gaming constraints.
5. The method of claim 4, wherein the objective function of the multi-benefit agent is:
wherein: pi p The benefit function of the multi-interest-subject cooperative alliance formed by the energy supply side comprehensive energy service provider and the energy storage operator is represented and is the difference value of income and expenditure obtained by selling energy to the user of the demand side industrial enterprise;
representing energy sale income of the energy supply side;
the annual average investment cost of equipment on the energy supply side is represented;
representing the payment of energy purchased by the energy supply side from the external network;
representing annual operation and maintenance cost of equipment on the energy supply side;
wherein s is the typical day; s is the typical number of days; d s Day of the s typical dayCounting; t is a scheduling period; Δ t is a scheduling time interval; p is a radical of e,t 、p h,t Respectively representing unit electricity price and heat price of the energy sold by the energy supply side to the industrial enterprise users; w e,t 、W h,t Respectively representing the actual electric load and the heat load of the industrial enterprise user;
wherein: k is the equipment type owned by the comprehensive energy service provider and the energy storage operator; k is the number of device types; alpha is alpha k The installed cost per unit volume of equipment k;
is the installed capacity of device k; r is annual interest rate; y is k Is the operating life of the device k;
wherein p is g Represents the price per unit of natural gas;
the total intake power of the comprehensive energy service provider in unit time period is represented;
representing the time-of-use electricity price of the power distribution network;
representing the power purchased by the power supply side power distribution network;
representing the heat price of the heat supply network;
power representing the energy supply side purchasing heat to the heat network;
wherein the content of the first and second substances,
respectively representing the unit capacity operation and maintenance costs of the CHP unit, the gas boiler and the distributed photovoltaic power generation of the comprehensive energy service provider;
respectively representing the operation and maintenance costs of a storage battery, a heat storage tank and an electric boiler of an energy storage operator;
respectively representing the output of the CHP unit of the comprehensive energy service provider, the gas boiler and the distributed photovoltaic equipment.
6. The method according to claim 5, wherein the objective function of the industrial enterprise user is:
wherein, F u A utility function for industrial enterprise users;
wherein: ae. be respectively represents preference constants of the electric energy consumption of the industrial enterprise users; ah. bh respectively represent preference constants for the thermal energy consumption of the industrial enterprise users.
7. The method of claim 5, wherein the non-cooperative game constraints include electrical balance constraints, thermal balance constraints, demand response constraints, energy storage device operation constraints, and user transaction price constraints:
the electrical balance constraints include:
wherein:
the part of the power grid which is directly sold to industrial enterprise users in power purchasing is shown;
the part of the energy storage operator is shown to purchase the electricity from the power grid;
the thermal equilibrium constraints include:
the demand response constraints include:
wherein:
representing a fixed electrical load of an industrial enterprise user;
indicating that the industrial enterprise user can translate the load in the t period;
a numerical upper limit representing the translatable electrical load of an industrial enterprise user;
representing the total amount of the translatable electric loads in the period T of the industrial enterprise users;
the energy storage device operating constraints include:
wherein:
indicating that the electricity purchasing power is used for a storage battery charging part;
if t is in the valley period, then there are:
if t is in the peak time period, the energy storage operator does not purchase electricity to the power distribution network, then:
the energy trading price constraints include:
wherein:
respectively representing the minimum value and the maximum value of the price of electricity sold by the energy supply side to the users of the industrial enterprise
Value constraint;
represents the upper limit of the average electricity rate.
8. The optimization planning method for the integrated energy system of the industrial enterprise according to claim 4, wherein the cooperation game constraint conditions are as follows:
wherein: v (i) represents the revenue that the participating principal i allocated in the cooperative alliance G; u (i) represents revenue for participating in the independent operation of subject i;
wherein: u shape CO Representing the total profit of the cooperative union; n represents the number of participating agents.
9. The method for optimizing and planning the industrial enterprise integrated energy system according to claim 7, wherein solving the non-cooperative game based on the KKT-BM method comprises:
converting an objective function of an industrial enterprise user into a constraint condition of an energy supply side, and converting double-layer optimization into nonlinear programming based on a KKT condition, wherein the specific expression is as follows:
wherein: l is GU A Lagrangian function representing an industrial enterprise user construct; theta e, theta esu and mu e respectively represent dual variables introduced by a KKT condition, wherein the theta e and the theta esu respectively represent Lagrange multipliers corresponding to inequality constraints, and the mu e represents Lagrange multipliers corresponding to equality constraints; "a ≧ b" means a ≧ 0, b ≧ 0, a × b =0;
converting the original nonlinear expression into a mixed integer linear programming constraint by introducing a variable of 0-1 by using a Big-M transformation method, wherein the mixed integer linear programming constraint is specifically represented as the following formula:
wherein: beta is a θe 、β θesu Represents a variable of 0 to 1, M being a sufficiently large positive number;
at the same time, the user can select the desired position,
according to the KKT condition, the dual variable is used for converting the dual variable into a secondary term, and the secondary term is specifically shown as the following formula:
after the conversion, the nonlinear term is only a quadratic term, and the equipment capacity and the transaction price of the comprehensive energy system are solved and determined.
10. The method of claim 8, wherein the allocating benefits of each participating entity in the collaborative league based on the sharley value method comprises:
wherein:
represents the benefit that participant i should receive; (| G | -1) |! Represents the total number of ranks for each participant in the principal federation, where | G | represents the number of partial participants and the remaining (n- | G |) participants have ranks of (n- | G |) |. In the method for preparing the seed coating,
dividing different sorting combinations representing the participation of each participant in the cooperation by the random sorting of n participants to obtain the weight occupied by each participant;v (G) represents the benefit of federation G when participant i participates in the collaboration; v (G \ i }) represents the benefit of federation G when participant i is removed; v (G) -v (G \ i }) represents the marginal contribution of participant i in the creation of a different federation G.
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| CN116227755A (en) * | 2023-05-09 | 2023-06-06 | 华北电力科学研究院有限责任公司 | Method and device for deploying multi-energy coupling system |
| CN116957139A (en) * | 2023-06-28 | 2023-10-27 | 湖南大学 | Multi-comprehensive-energy microgrid optimal operation method and system considering carbon transaction among microgrids |
| CN117172815A (en) * | 2023-07-18 | 2023-12-05 | 南京工业大学 | Hybrid game method and system for active power distribution network of multiple water, electricity and gas energy subsystems |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116227755A (en) * | 2023-05-09 | 2023-06-06 | 华北电力科学研究院有限责任公司 | Method and device for deploying multi-energy coupling system |
| CN116227755B (en) * | 2023-05-09 | 2023-08-08 | 华北电力科学研究院有限责任公司 | Method and device for deploying multi-energy coupling system |
| CN116957139A (en) * | 2023-06-28 | 2023-10-27 | 湖南大学 | Multi-comprehensive-energy microgrid optimal operation method and system considering carbon transaction among microgrids |
| CN117172815A (en) * | 2023-07-18 | 2023-12-05 | 南京工业大学 | Hybrid game method and system for active power distribution network of multiple water, electricity and gas energy subsystems |
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