CN111401713A - Multi-energy system complementary optimization configuration method based on multi-level energy hub model - Google Patents
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Abstract
A multi-energy system complementary optimization configuration method based on a multi-energy hub model is characterized in that a multi-energy hub model of the multi-energy system is established, a two-stage planning model comprising a connection relation planning between each stage of configuration equipment planning and two adjacent stages of configuration equipment planning is provided, a universal planning model suitable for any multi-energy system is realized, the system structure and the equipment capacity can be planned simultaneously, the planning cost is minimized, the problem that the current research is limited to a single planning structure or equipment capacity is solved, the single planning takes account factors incompletely, the planning cost is high easily, and the high energy utilization efficiency advantage of the multi-energy system cannot be fully played.
Description
Technical Field
The invention relates to a technology applied to a multi-energy system, in particular to a multi-energy system complementary optimization configuration method based on a multi-level energy hub model.
Background
The configuration planning of the existing multi-energy system aims at planning the capacity of equipment under the condition that the system structure and the equipment type are known, and a research method for the structure planning of the multi-energy system is limited to an enumeration method, cannot be applied to a scene of simultaneously planning the comprehensive energy system structure and the equipment capacity, and cannot solve the problems that the multi-energy system meets different load requirements of electricity, heat, cold and the like, and the energy production equipment, the energy storage equipment and the energy conversion equipment in the system are various and the system structure is complex. Therefore, it is necessary to provide a general multi-energy system planning model, which can plan the structure and the equipment capacity of the system at the same time and is suitable for the complex multi-energy system planning problem.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a multi-energy system complementary optimization configuration method based on a multi-level energy hub model.
The invention is realized by the following technical scheme:
the method comprises the steps of firstly establishing a multi-level energy hub general model taking a directed acyclic graph as a topological structure, and then carrying out double-stage planning on the multi-energy system based on the multi-level energy hub general model to obtain the structure and equipment capacity of the multi-energy system for realizing the multi-energy system planning.
The general model of the multi-stage energy hub is characterized in that system elements in the energy hub structure are divided into three stages: the first stage is a production equipment element containing photothermal, wind power and photovoltaic; the second stage is an energy conversion device element containing electric refrigeration, electric heating and thermal refrigeration; the third stage is an energy storage device element containing heat and electricity storage. Based on graph theory, the system elements therein are used as vertices (vertex), and the energy flows between the system elements are used as directed edges (directed edge), so that the whole energy hub model is used as a Directed Acyclic Graph (DAG).
The energy junction structure is as follows: the multi-port network comprises multiple inputs and multiple outputs, and multiple energies are converted, distributed and stored in the network.
The energy hub model is constructed by abstracting a multi-energy system into a multi-port network with multiple inputs and multiple outputs, wherein multiple input ends of the multi-energy system are directly connected with an energy network so as to input corresponding energy, for example, the input ends of the energy hub are connected with a power grid, a natural gas grid and a heating power grid to input electricity, gas and heat; the energy sources such as a plurality of output electricity, heat and cold can meet the requirements of various loads, and the electricity, the gas, the heat and the cold can be converted, distributed and stored in the energy hub through the energy conversion device and the energy storage device.
The directed acyclic graph has the property of topological hierarchy, that is, all the vertexes can be divided into different levels, and the directed edges after the hierarchy all point to high levels from low levels. And carrying out topology classification on the typical energy hub according to the property, and establishing a general topology classification model of the energy hub. In a graded directed acyclic graph, directed edges connecting two adjacent layers are short edges, and the rest are long edges. To avoid the appearance of a long edge, a virtual vertex can be introduced to divide the long edge into several short edges. These virtual vertices are named placeholder connection components. It should be noted that the place-occupying connecting element is a virtual vertex, divides a long side into a plurality of short sides, facilitates the construction of a model, and does not represent a real transmission line or a real pipeline, so as to realize the topology classification strategy of the energy hub. A general model of a multi-level energy hub with placeholder connection elements is shown in fig. 1.
In order to construct a mathematical model describing the topological hierarchy of the energy hub, a m × n-dimensional matrix is introduced
Wherein: m isRepresenting the number of stages of the energy hub, n representing the total number of system elements, all elements in the matrix Y being a variable from 0 to 1: when the system component j is at the ith stage of the energy hub, then yij1, otherwise yij0; a topological hierarchy strategy for an energy hub corresponds one-to-one to a matrix Y.
For each time interval and each energy form, two groups of m × n-dimensional matrixes are introduced to express input and output powers of system elements, and the input power and the output power of the ith-stage system element j of the energy junction are expressed by the input power and the output power of the ith-stage system element j of the energy junction in the t time interval in terms of the energy form k (e, g, h, c, cold)
Output power
Wherein: pij k,in(t) and Pij k,out(t) represents the sum of the input powers of the ith-stage system element j of the energy hub in the time period t with respect to the energy form k (e, g, h, c, cold), respectively
The energy hub comprises: energy conversion element, placeholder connection element, energy storage element and distributed renewable energy element, wherein:
① when the input and output energy forms of the energy conversion element j are k1 and k2, respectively, the input and output power relationships of the energy conversion element satisfy:
wherein ηjIs the energy conversion efficiency or coefficient of performance of the system element j; correspondingly, the energy conversion element input or output satisfies:
wherein:
and
respectively represent systemThe system element j has lower and upper limits on the input power of the energy form k 1.
② when the system element j is a placeholder for the energy form k, the input and output power of the placeholder element satisfies:
correspondingly, the input or output of the placeholder connection element satisfies:
wherein: m is a larger positive constant.
③ the energy storage element is a single input single output element, the energy storage element j input output power relation satisfies:
wherein: sj(t) represents the state of charge (SOC) of system element j during time t, ηj inAnd ηj outRespectively representing the charging and discharging efficiencies of the system element j; Δ t represents the time span of a single time segment; ejRepresents the storage capacity of system element j; correspondingly, the input and output of the energy storage element satisfy:
the SOC of the energy storage element satisfies: sjmin≤Sj(t)≤Sjmax，Sj(0)＝Sj(T), wherein: sjminAnd SjmaxThe lower and upper limits of SOC for system element j, respectively; t is the total number of time segments within a day.
④ distributed renewable energy element as a zero input single output element, whose output is affected by natural resources (such as wind, light), the output of the distributed renewable energy element j satisfies:
wherein: pk，out jmax(t) represents the maximum output power of distributed renewable energy element j during time t.
The two-phase planning comprises: planning the type of each stage of configuration equipment and planning the connection relation between two adjacent stages of configuration equipment, wherein: the device type planning of each stage of configuration means: setting and solving a planning model to obtain system elements of each level of the energy hub, and further planning the connection relation among the system elements of each level of the energy hub on the basis of obtaining the planned elements of each level of the energy hub, namely, under the condition of not influencing the feasibility and the optimality of the first-step planning optimization result, deleting redundant connection edges on the basis of connecting input and output ports with the same energy form in adjacent layers of the energy hub to obtain the optimal element connection relation.
The planning model of the device type configured at each stage is as follows:
decision variables: hierarchical strategy matrix Y, energy input power Pk,in(t) power of energy output Pk,out(t)；
An objective function: the initial investment cost and the operation cost of the multi-energy system are the lowest, wherein the operation cost refers to the electricity purchasing cost of the slave power distribution main network;
constraint conditions are as follows: energy hub constraint
Meaning that the input power of the layer after the t period with respect to energy form k is equal to the output power of the previous layer with respect to energy form k,
the output power of the last layer in the period t with respect to the energy form k is equal to the load demand in the period t with respect to the energy form k, wherein:
the load demand for the energy form k is the period t.
The optimal element connection relation is obtained through the following planning model:
decision variables: connection relation matrix
Energy flow matrix
Wherein n isl,nl+1Indicates the number of devices of the l-th stage and the l + 1-th stage,
representing the power in energy form k that class i device flows into class i +1 device j.
An objective function: minimum number of connecting lines
Constraint conditions are as follows: adjacent level system element connection relationship constraints
Wherein:
represents the power of the l-th level device i flowing into the l + 1-th level device j with respect to the energy form k,
representing the total output power of the l-th stage device i with respect to the energy form k,
representing the total input power of the l +1 th stage device j with respect to the energy form k.
The optimal element connection relationship is obtained by introducing n for each time interval, each two adjacent stages and each energy forml×nl+1Dimension matrix
Describing the energy flow between system elements, wherein: n islRepresenting the number of system elements of the l-level construction; when P is presentkThe ith row of (t) corresponds to the ith energy hubSystem elements u (i) of stages, and PkThe jth column of (t) corresponds to the system element v (j) of stage l +1 of the energy hub; then P isk ij(t) represents the power delivered by system element u (i) to system element v (j) for time period t in terms of energy form k; pk(t) the row of the ith row and i.e. the amount of output power of the system element u (i) with respect to the energy form k (i.e. P) equal to the time period tk,out lu(i)(t))，Pk(t) the column sum of the jth column, i.e. equal to the input power magnitude of the system element v (j) with respect to the energy form k (i.e. P) during the time period tk,in l+1v(j)(t)), wherein all nl、nl+1、Pk,out lu(i)(t) and Pk,in l+1v(j)(t) have all been obtained by stage 1; similarly, for every two adjacent layers and every energy form, one n is introducedl×nl+1Dimension matrix
Describing a connection relationship between system elements, wherein: b isk(t) is illustrated with respect to energy form k with the l-th and l + 1-th layers.
Technical effects
The invention integrally solves the problem of the combined planning of the structure and the equipment capacity of the multi-energy system; compared with the prior art, the method and the system can realize the universal planning of any multi-energy system, simultaneously plan the structure and equipment capacity of the multi-energy system and minimize the planning cost. The invention constructs a multi-energy system into a topological form of a multi-stage directed acyclic graph, and quantitatively describes the conversion relation among various energy sources such as electricity-to-heat, heat-to-cold, electricity-to-cold and the like. The content of the optimized configuration not only comprises the type of the equipment (such as energy production equipment, energy storage equipment and energy conversion devices) to be configured at each level, but also comprises the connection relationship between the equipment configured at each two adjacent levels, thereby realizing the user-defined mode. The method can be applied both to extension planning and to preliminary planning starting from scratch.
Drawings
FIG. 1 is a diagram of a generalized model of a multi-stage energy hub including placeholder connecting elements;
FIG. 2 is a two-stage layout.
Detailed Description
The embodiment relates to a system for realizing a complementary optimal configuration method of a multi-energy system, which comprises the following steps: the device comprises a device parameter input unit, a planning unit for each stage of configuration device, a planning unit for connection relationship between two adjacent stages of configuration devices and a planning result output unit, wherein: the equipment parameter input unit is connected with the equipment planning unit of each stage of configuration and the connection relation planning unit between two adjacent stages of configuration equipment and transmits the installation cost and efficiency information of the equipment, the equipment planning unit of each stage of configuration is connected with the connection relation planning unit between two adjacent stages of configuration equipment and transmits the input power and output power information of each stage of equipment, and the connection relation planning unit between the equipment planning unit of each stage of configuration and the two adjacent stages of configuration equipment is connected with the planning result output unit and transmits the planning result information.
The system of this embodiment performs complementary optimal configuration of the multi-energy system according to the specific load and the output condition of the renewable energy, including: the device configuration of each stage in the multi-stage energy hub and the determination of the connection relationship between adjacent stages, namely the multi-energy transfer path, realize the simultaneous planning of the multi-energy system structure and the device capacity, rather than the independent planning of the structure or the capacity.
The load in the complementary optimal configuration of the multi-energy system comprises three loads of electricity, heat and cold, and the given alternative equipment parameters are as follows:
and solving the two-stage planning model based on the multi-stage energy hub model by adopting Matlab.
Through simulation experiments, the first level of an energy hub of the multi-energy system comprises a 400kW fan and a 300kW cogeneration unit, because the installation cost of the fan is far lower than that of a photovoltaic, and in order to avoid high electricity price during a load peak period, the cogeneration unit using natural gas as an energy source is selected; the second stage contains 200kW electric cooling and 400kW electric heating because the efficiency of electric cooling is much greater than that of thermal cooling; the third stage contains a 1000kWh cold storage device and a 3000kWh heat storage device, since the installation costs of the heat and cold storage devices are much lower than the electricity storage devices. The method provided by the invention realizes the simultaneous planning of the multi-energy system structure and the equipment capacity, meets the requirement of minimizing the planning cost, and is applicable to actual engineering.
Compared with the prior art, the method has the advantages that the multi-stage energy hub model of the multi-energy system is established, the two-stage planning model comprising the connection relation planning between each stage of configuration equipment planning and the adjacent two stages of configuration equipment planning is provided, the universal planning model suitable for any multi-energy system is realized, the system structure and the equipment capacity can be planned at the same time, the planning cost is minimized, the problem that the current research is limited to a single planning structure or equipment capacity is solved, the single planning is not comprehensive in consideration, the planning cost is high easily, and the high energy utilization efficiency advantage of the multi-energy system cannot be fully played.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (9)
1. A multi-energy system complementary optimization configuration method based on a multi-level energy hub model is characterized in that a multi-level energy hub general model taking a directed acyclic graph as a topological structure is established, and then a multi-energy system is subjected to two-stage planning based on the multi-level energy hub general model to obtain the structure and equipment capacity of the multi-energy system for realizing the multi-energy system planning;
the general model of the multi-stage energy hub is characterized in that system elements in the energy hub structure are divided into three stages: the first stage is a production equipment element containing photothermal, wind power and photovoltaic; the second stage is an energy conversion device element containing electric refrigeration, electric heating and thermal refrigeration; the third stage is an energy storage device element containing heat and electricity storage; based on the graph theory, the system elements are used as vertexes, and the energy flow between the system elements is used as a directed edge, so that the whole energy hub model is used as a directed acyclic graph.
2. The method of claim 1, wherein the energy terminal structure is: the multi-port network comprises multiple inputs and multiple outputs, and multiple energies are converted, distributed and stored in the network;
the energy hub model is constructed by abstracting a multi-energy system into a multi-port network with multiple inputs and multiple outputs, wherein multiple input ends of the multi-energy system are directly connected with an energy network so as to input corresponding energy, for example, the input ends of the energy hub are connected with a power grid, a natural gas grid and a heating power grid to input electricity, gas and heat; the energy sources such as a plurality of output electricity, heat and cold can meet the requirements of various loads, and the electricity, the gas, the heat and the cold can be converted, distributed and stored in the energy hub through the energy conversion device and the energy storage device.
3. The method of claim 1, wherein for constructing the energy hub describing model, a m × n dimensional matrix is introduced
Wherein: m represents the number of stages of the energy hub, n represents the total number of system elements, and all elements in the matrix Y are variables from 0 to 1: when the system component j is at the ith stage of the energy hub, then yij1, otherwise yij0; one topological classification strategy of one energy hub corresponds to one matrix Y one by one;
for each time interval and each energy form, two groups of m × n-dimensional matrixes are introduced to express input and output powers of system elements, and the input power and the output power of the ith-stage system element j of the energy junction are expressed by the input power and the output power of the ith-stage system element j of the energy junction in the t time interval in terms of the energy form k (e, g, h, c, cold)
Output power
Wherein: pij k,in(t) and Pij k,out(t) represents the sum of the input powers of the i-th stage system element j of the energy hub for the time period t, respectively, with respect to the energy form k (e, g, h, hot, c, cold).
4. A method according to claim 1, 2 or 3, wherein the energy hub comprises: energy conversion element, placeholder connection element, energy storage element and distributed renewable energy element, wherein:
① when the input and output energy forms of the energy conversion element j are k1 and k2, respectively, the input and output power relationships of the energy conversion element satisfy:
wherein ηjIs the energy conversion efficiency or coefficient of performance of the system element j; correspondingly, the energy conversion element input or output satisfies:
wherein:
and
represents the lower and upper input power limits of the system element j with respect to the energy form k1, respectively;
② when the system element j is a placeholder for the energy form k, the input and output power of the placeholder element satisfies:
correspondingly, occupy spaceThe input or output of the connecting element satisfies:
wherein: m is a larger normal number;
③ the energy storage element is a single input single output element, the energy storage element j input output power relation satisfies:
wherein: sj(t) represents the state of charge (SOC) of system element j during time t, ηj inAnd ηj outRespectively representing the charging and discharging efficiencies of the system element j; Δ t represents the time span of a single time segment; ejRepresents the storage capacity of system element j; correspondingly, the input and output of the energy storage element satisfy:
the SOC of the energy storage element satisfies: sjmin≤Sj(t)≤Sjmax，Sj(0)＝Sj(T), wherein: sjminAnd SjmaxThe lower and upper limits of SOC for system element j, respectively; t is the total number of time segments within a day;
④ distributed renewable energy element as a zero input single output element, whose output is affected by natural resources (such as wind, light), the output of the distributed renewable energy element j satisfies:
wherein: pk,out jmax(t) represents the maximum output power of distributed renewable energy element j during time t.
5. The method of claim 1, wherein said two-phase planning comprises: planning the type of each stage of configuration equipment and planning the connection relation between two adjacent stages of configuration equipment, wherein: the device type planning of each stage of configuration means: setting and solving a planning model to obtain system elements of each level of the energy hub, and further planning the connection relation among the system elements of each level of the energy hub on the basis of obtaining the planned elements of each level of the energy hub, namely, under the condition of not influencing the feasibility and the optimality of the first-step planning optimization result, deleting redundant connection edges on the basis of connecting input and output ports with the same energy form in adjacent layers of the energy hub to obtain the optimal element connection relation.
6. The method as claimed in claim 5, wherein the device type planning model for each configuration level is:
decision variables: hierarchical strategy matrix Y, energy input power Pk,in(t) power of energy output Pk,out(t)；
An objective function: the initial investment cost and the operation cost of the multi-energy system are the lowest, wherein the operation cost refers to the electricity purchasing cost of the slave power distribution main network;
constraint conditions are as follows: energy hub constraint
Meaning that the input power of the layer after the t period with respect to energy form k is equal to the output power of the previous layer with respect to energy form k,
the output power of the last layer in the period t with respect to the energy form k is equal to the load demand in the period t with respect to the energy form k, wherein:
the load demand for the energy form k is the period t.
7. The method of claim 5, wherein the optimal component connection relationship is obtained by the following planning model:
decision variables: connection relation matrix
Energy flow matrix
Wherein n isl,nl+1Indicates the number of devices of the l-th stage and the l + 1-th stage,
represents the power of the l < th > level device i flowing into the l +1 < th > level device j with respect to the energy form k;
an objective function: minimum number of connecting lines
Constraint conditions are as follows: adjacent level system element connection relationship constraints
Wherein:
represents the power of the l-th level device i flowing into the l + 1-th level device j with respect to the energy form k,
representing the total output power of the l-th stage device i with respect to the energy form k,
representing the total input power of the l +1 th stage device j with respect to the energy form k.
8. A method according to claim 5 or 7, wherein said optimum component connection is achieved by introducing an n for each time interval, each two adjacent stages and each energy forml×nl+1Dimension matrix
Describing the energy flow between system elements, wherein: n islRepresenting the number of system elements of the l-level construction; when P is presentkThe ith row of (t) corresponds to the system element u (i, and P) of the ith stage of the energy hubkThe jth column of (t) corresponds to the system element v (j) of stage l +1 of the energy hub; then P isk ij(t) represents the power delivered by system element u (i) to system element v (j) for time period t in terms of energy form k; pk(t) the row of the ith row and is equal to the output power level of the system element u (i) with respect to the energy form k, i.e. P, for the period tk,out lu(i)(t)，Pk(t) the column sum of the jth column, i.e. equal to the input power level of the system element v (j) with respect to the energy form k, i.e. P, during the time period tk,in l+1v(j)(t) wherein all nl、nl+1、Pk,out lu(i)(t) and Pk,in l+1v(j)(t) have all been obtained by stage 1;
similarly, for every two adjacent layers and every energy form, one n is introducedl×nl+1Dimension matrix
Describing a connection relationship between system elements, wherein: b isk(t) is illustrated with respect to energy form k with the l-th and l + 1-th layers.
9. A system for implementing the complementary optimal configuration method of the multi-energy system according to any one of claims 1 to 8, comprising: the device comprises a device parameter input unit, a planning unit for each stage of configuration device, a planning unit for connection relationship between two adjacent stages of configuration devices and a planning result output unit, wherein: the equipment parameter input unit is connected with the equipment planning unit of each stage of configuration and the connection relation planning unit between two adjacent stages of configuration equipment and transmits the installation cost and efficiency information of the equipment, the equipment planning unit of each stage of configuration is connected with the connection relation planning unit between two adjacent stages of configuration equipment and transmits the input power and output power information of each stage of equipment, and the connection relation planning unit between the equipment planning unit of each stage of configuration and the two adjacent stages of configuration equipment is connected with the planning result output unit and transmits the planning result information.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159407A (en) * | 2021-04-14 | 2021-07-23 | 北京交通大学 | Multi-energy storage module capacity optimal configuration method based on regional comprehensive energy system |
| CN116050760A (en) * | 2022-12-31 | 2023-05-02 | 上海交通大学 | Multi-energy-source junction collaborative planning method and equipment based on internal structure layering |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2016101350A4 (en) * | 2016-08-02 | 2016-09-15 | Cooper, James MR | Distributed energy hub powered by reneweable ammonia |
| CN107528337A (en) * | 2016-11-21 | 2017-12-29 | 六安市科宇专利技术开发服务有限公司 | A kind of electric automobile charging station with energy-storage system |
| CN109859072A (en) * | 2019-03-06 | 2019-06-07 | 华北电力大学 | A kind of colleges and universities' integrated energy system planing method |
| CN110266004A (en) * | 2019-06-28 | 2019-09-20 | 西安交通大学 | A kind of standardization construction method of integrated energy system energy hinge model |
| CN110766238A (en) * | 2019-10-30 | 2020-02-07 | 中国电力科学研究院有限公司 | Hierarchical planning method and system for alternating current-direct current hybrid power distribution system |
-
2020
- 2020-03-09 CN CN202010159733.5A patent/CN111401713A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2016101350A4 (en) * | 2016-08-02 | 2016-09-15 | Cooper, James MR | Distributed energy hub powered by reneweable ammonia |
| CN107528337A (en) * | 2016-11-21 | 2017-12-29 | 六安市科宇专利技术开发服务有限公司 | A kind of electric automobile charging station with energy-storage system |
| CN109859072A (en) * | 2019-03-06 | 2019-06-07 | 华北电力大学 | A kind of colleges and universities' integrated energy system planing method |
| CN110266004A (en) * | 2019-06-28 | 2019-09-20 | 西安交通大学 | A kind of standardization construction method of integrated energy system energy hinge model |
| CN110766238A (en) * | 2019-10-30 | 2020-02-07 | 中国电力科学研究院有限公司 | Hierarchical planning method and system for alternating current-direct current hybrid power distribution system |
Non-Patent Citations (1)
| Title |
|---|
| 黄武靖等: "多能源网络与能量枢纽联合规划方法", 《中国电机工程学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159407A (en) * | 2021-04-14 | 2021-07-23 | 北京交通大学 | Multi-energy storage module capacity optimal configuration method based on regional comprehensive energy system |
| CN113159407B (en) * | 2021-04-14 | 2023-12-19 | 北京交通大学 | Multi-energy storage module capacity optimal configuration method based on regional comprehensive energy system |
| CN116050760A (en) * | 2022-12-31 | 2023-05-02 | 上海交通大学 | Multi-energy-source junction collaborative planning method and equipment based on internal structure layering |
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