CN109670730A - A kind of integrated energy system economic load dispatching method a few days ago - Google Patents
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Abstract
A kind of integrated energy system of the invention economic load dispatching method a few days ago can solve existing analysis method and consider the insufficient technical problem for keeping comprehensive energy utilization efficiency not high to heat, electricity, gas multipotency coupling.The following steps are included: S100, foundation is using maximization of economic benefit as the energy efficiency model of target, come meet under the equilibrium of supply and demand and operation constraint condition different user to electrically and thermally the needs of；S200, model objective function is established；Objective function is turned to gross profit maximum, that is, sells energy income and subtracts system synthesis sheet, totle drilling cost includes the operating cost, start-up cost and shutdown cost of power supply, heat supply and gas supply；S300, model constraint condition is established；Model need to meet the constraint of two classes: system operation constraint and the operation of each equipment constrain；S400, linearisation conversion is carried out to model.The piece-wise linearization that the present invention uses carries out conversion solution to it, obtains better effects, and the integrated energy system Optimized Operation that market-oriented environment can be adapted to for research provides important guidance.
Description
Technical Field
The invention relates to the field of comprehensive energy systems, in particular to a day-ahead economic dispatching method of a comprehensive energy system.
Background
In 2013, a reform committee issued 'temporary approach to distributed power generation management', which points out the active development of on-site consumption of natural gas combined heat, power and cold supply; in 2016, the development and improvement committee jointly issues implementation opinions about promoting the construction of the multi-energy complementary integration optimization demonstration project with the national energy agency, accelerates the promotion of the construction of the multi-energy complementary integration optimization demonstration project, realizes overall optimization and improves efficiency. The method has the advantages that the mode of Energy interconnection with multi-Energy coordination and complementation is promoted, and the construction of an Integrated Energy System (IES) is accelerated, so that the direction of future Energy development in China is the direction, and the research of the cold-heat-electricity-gas-storage multi-Energy coupling optimization scheduling with a power distribution network as a link and electricity as a center is particularly necessary.
At present, the calculation of the optimal power flow is relatively mature, but the research of the optimal power flow of the IES with multi-energy coupling is relatively deficient. Document [ Sahin C, Shahidehpour M, Erkmen i.generation establishment in vollatile conditions with, hydro, and native gas units [ J ]. Applied Energy, 2012, 96: 4-11] electric power risk assessment considering natural gas pipeline operation constraints, and analyzing interaction influence between American natural gas and an electric power system; literature [ Kamalinia S, Wu L, Shahidehpor m.stochastic midmeter registration of hydro and natural gas flexibilities for wire energy integration [ J ]. IEEE transfer Power Systems, 2014, 5 (4): 1070-; however, the above research is biased to the electric/gas energy transmission network, and the consideration for the multi-energy coupling effect of heat, electricity, gas and the like is insufficient. A hierarchical optimization model based on an energy hub is provided in documents [ Hauran, Aiqian, Juyu, and the like ] regional comprehensive energy system hierarchical optimization scheduling [ J ] electric power automation equipment, 2017, 37(6): 171-; the research of IES optimization also relates to thermal energy demand side response, multi-stage planning, robust random optimization scheduling, optimal power flow and the like, but the research on the equipment energy efficiency model is lack.
Typical IES equipment energy efficiency curves (reflecting the relation between capacity and energy consumption under different load rates of equipment) of Combined Heating and Power systems (CHP), gas steam boilers and the like are nonlinear, and most of researches adopt a mechanism model to reflect an input-output relation, but the configuration parameters of the model in actual engineering are difficult to configure accurately. In addition, the IES optimization model is nonlinear and contains start-stop state variables of a controllable unit, and is a typical mixed integer nonlinear programming (MINLP) problem, and documents [ wave, Sun-Heng-Henan, item-Zengchun, and the like ] adopt tabu search and particle swarm algorithm to solve a comprehensive energy system planning design method [ J ]. power construction, 2016, 37(2):78-84], but the method is difficult to obtain stable results, has poor interpretability and limits the engineering popularization.
Disclosure of Invention
The day-ahead economic dispatching method for the comprehensive energy system can solve the technical problem that the utilization efficiency of comprehensive energy is low due to the insufficient consideration of the multi-energy coupling effect of heat, electricity and gas in the existing analysis method.
In order to achieve the purpose, the invention adopts the following technical scheme:
a day-ahead economic dispatching method of an integrated energy system comprises the following steps:
s100: according to the research of the existing comprehensive energy system, the existing research advantages and disadvantages are discussed, and a comprehensive energy system day-ahead economic dispatching model considering the multi-energy coupling effects of heat, electricity, gas and the like is constructed;
s200, establishing a model objective function; establishing an energy efficiency model aiming at maximizing economic benefits to meet the requirements of different users on electricity and heat under the conditions of supply and demand balance and operation constraint; taking the maximization of the total profit as an objective function, namely subtracting the total cost of the system from the energy selling profit, wherein the total cost comprises the running cost, the starting cost and the shutdown cost of power supply, heat supply and gas supply;
s300, establishing a model constraint condition; the model needs to satisfy two types of constraints: system operating constraints and operating constraints of each device; the system constraints comprise system power balance constraints, system heat energy balance constraints and system tie line constraints; the operation constraints of the equipment comprise CHP operation safety and state coupling constraints, gas internal combustion engine operation safety and state coupling constraints, shutdown and state coupling constraints, initial state and startup and shutdown coupling constraints, photovoltaic inverter power generation constraints, energy storage battery charge and discharge power constraints, energy storage battery electric quantity constraints and the like;
s400: and (4) linear transformation.
Further, the objective function in step S200 is expressed as follows:
wherein,
cost of energy saleIncluding the cost of electricity sellingAnd cost of heat soldIn the formula, T is the number of scheduling time segments; the power selling quantity and the power selling price of the IES are respectively in the t period; ht、The heat supply amount and the heat supply price of the IES to the user in the t period are respectively;
cost of energy purchaseIncluding the cost of electricity purchaseAnd cost of gas purchaseIn the formula,the electricity purchasing quantity and the electricity purchasing price of the IES in the time period t are respectively;respectively the gas purchasing quantity and the gas purchasing price of the IES in the t period;
running cost Cop＝CCHP+CGSB+CBAT+CPVIncluding CHP operating cost CCHPGas internal combustion engine operating cost CGSBAnd the operation and maintenance cost of the storage battery CBATSum light cost CPV；
Wherein NCHP, NGSB, NBAT and NPV are CHP, steam gas boiler, steam turbine, etc,The number of energy storage cells and photovoltaic power sources; respectively the state variables of the ith CHP and the steam gas-fired boiler in the t period; for the corresponding operating cost; and starting and shutdown variables of the ith CHP and the steam gas boiler in the t period respectively; and the starting-up cost and the shutdown cost of the ith CHP and the steam gas-fired boiler in the t period respectively;the charge and discharge maintenance cost is the unit charge and discharge maintenance cost of the ith energy storage battery;is the charge and discharge power; k is a light abandoning penalty coefficient;andactual output and upper limit of the ith photovoltaic inverter in the t period are respectively;
further, the constraint conditions in step S300 include system operation constraints and operation constraints of each device;
wherein the system operation constraints include:
and (3) system power balance constraint:
and (3) system heat energy balance constraint:
system tie line constraint:
in the formula,is the electrical load of the system for a period t;andthe charging power and the discharging power of the ith energy storage battery are respectively in the time t; htIs the thermal load of the system for a period t;andthe heating power of the ith steam gas-fired boiler and the CHP in the t period respectively;·andrespectively are the upper limit and the lower limit of a variable,P gridandpower purchase/sale restrictions for the system to the grid;
the equipment operating constraints include:
CHP operational safety and state coupling constraints:
the CHP combined heat and power generation efficiency can reach more than 70 percent, and the combined heat and power mode is generally adopted in the actual production, so that the following constraints are met:
in the formula, θ represents a thermoelectric ratio.
Gas internal combustion engine operation safety and state coupling constraint
On-off and state coupling constraints
Introducing startup and shutdown variables into the target, bringing startup cost and shutdown cost into a model, and considering the coupling relation of the startup and shutdown of the equipment and each time period of the equipment state:
in the formula, and starting and shutdown variables (0-1 variable) of the ith CHP and the steam internal combustion engine in the t period respectively;
initial state and on-off coupling constraints
Considering the initial start-stop state of the equipment before optimization, the additional constraints of the start-stop state and the running state of the equipment and the first optimization period are as follows:
photovoltaic inverter generated power constraint
Energy storage battery charge and discharge power constraint
Taking into account charging variablesAnd discharge variableCoupling constraints with charging and discharging power variables:
in the formula,andmaximum charge-discharge power limit;
energy storage battery power constraint
SOCi,T＝SOCi,1(21)
In the formula, SOCtThe stored energy of the storage battery is represented by the formula (21), wherein the stored energy is represented by the stored energy of the storage battery at the beginning and the end of the period t, α is the charge/discharge coefficientWeighing constraint;
further, the linear transformation of step S400 specifically includes:
energy efficiency curves of CHP (chemical vapor deposition), gas steam boilers and other equipment are nonlinear, most researches adopt mechanism models to reflect input-output relations, but the defects that mechanism model configuration parameters are difficult to accurately acquire and configure exist in actual engineering. Considering that the detailed device principle modeling has high requirements on engineering data acquisition, the patent adopts a black box model, namely an energy efficiency model for directly driving the device through historical data.
For a CHP, gas-fired steam boiler, the fuel consumption x as a function of the output y can be expressed as a non-linear equation:
y＝f(x)+ε (22)
wherein f (x) is a non-linear function; ε is the error.
For the nonlinear programming problem, many researches adopt intelligent algorithms to solve, but the method is difficult to obtain a stable optimal solution and has poor interpretability, so that the online application and popularization of the method are limited. The invention adopts the nonlinear energy efficiency curve of the N-segment broken line description formula (22), and when the number of segments is enough, the requirement on precision can be considered to be met.
The SOS2 method is an additional constraint method based on ordered variables, has wide application in solving the MINLP problem, and adopts the following conversion method to carry out linear conversion on the day-ahead economic dispatching model of the comprehensive energy system.
In the formula,to ensure non-zero ziAdjacent to each other.
According to the technical scheme, the invention provides a day-ahead economic dispatching method of the comprehensive energy system, the total profit maximization is taken as an objective function, namely the total cost of the system is subtracted from the energy selling profit, the total cost comprises the operation cost, the starting cost and the shutdown cost of power supply, heat supply and gas supply, and an optimization model with the aim of maximizing the economic benefit is established on the premise of meeting the operation constraint of the system and the operation constraint of each device. The day-ahead economic dispatching of the comprehensive energy system is a nonlinear and multi-constraint high-dimensional mathematical optimization problem, and the method adopts piecewise linearization to carry out conversion solution on the comprehensive energy system, so that a better effect is achieved. The invention can provide important guidance for researching the comprehensive energy system optimization scheduling suitable for the marketized environment.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a block diagram of the integrated energy system of the present invention;
FIG. 3 is a schematic diagram of the piecewise linearization of the energy efficiency curve of the equipment of the present invention;
FIG. 4 is a predicted photovoltaic and electrothermal load output of the present invention;
FIG. 5 is a graph of the scheduled output of the controllable power supply of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention.
As shown in fig. 1, the method for day-ahead economic dispatch of an integrated energy system according to this embodiment includes:
s100, establishing an energy efficiency model aiming at maximizing economic benefits to meet the requirements of different users on electricity and heat under the conditions of supply and demand balance and operation constraint;
s200, establishing a model objective function; taking the maximization of the total profit as an objective function, namely subtracting the total cost of the system from the energy selling profit, wherein the total cost comprises the running cost, the starting cost and the shutdown cost of power supply, heat supply and gas supply;
s300, establishing a model constraint condition; the model needs to satisfy two types of constraints: system operating constraints and operating constraints of each device;
and S400, performing linear conversion on the model.
The above steps can be interpreted as:
firstly, according to the research of the existing comprehensive energy system, the existing research advantages and disadvantages are discussed, and a day-ahead economic dispatching model of the comprehensive energy system considering the multi-energy coupling effects of heat, electricity, gas and the like is provided.
Secondly, a model objective function is established. And establishing an energy efficiency model aiming at maximizing economic benefits to meet the requirements of different users on electricity and heat under the conditions of supply and demand balance and operation constraint. The overall profit maximization is taken as the objective function, i.e. the energy sales profit minus the total system cost, which includes the operating costs of power, heat and gas supply, start-up costs and shut-down costs.
Then, model constraints are established. The model needs to satisfy two types of constraints: system operational constraints and operational constraints of the devices. The system constraints include a system power balance constraint, a system thermal energy balance constraint, and a system tie line constraint. The operation constraints of the device comprise CHP operation safety and state coupling constraints, gas internal combustion engine operation safety and state coupling constraints, shutdown and state coupling constraints, initial state and startup and shutdown coupling constraints, photovoltaic inverter power generation constraints, energy storage battery charge and discharge power constraints, energy storage battery electric quantity constraints and the like.
And finally, the segmentation linearization is adopted to convert the data, so that a better effect is obtained.
The method of the embodiment of the invention comprises the following specific steps:
wherein, the objective function in step S200 is expressed as follows:
wherein,
cost of energy saleIncluding the cost of electricity sellingAnd cost of heat soldIn the formula, T is the number of scheduling time segments; the power selling quantity and the power selling price of the IES are respectively in the t period; ht、The heat supply amount and the heat supply price of the IES to the user in the t period are respectively;
cost of energy purchaseIncluding the cost of electricity purchaseAnd cost of gas purchaseIn the formula,the electricity purchasing quantity and the electricity purchasing price of the IES in the time period t are respectively;respectively the gas purchasing quantity and the gas purchasing price of the IES in the t period;
running cost Cop＝CCHP+CGSB+CBAT+CPVIncluding CHP operating cost CCHPGas internal combustion engine operating cost CGSBAnd the operation and maintenance cost of the storage battery CBATSum light cost CPV；
In the formula, NCHP, NGSB, NBAT and NPV are the number of CHP, steam gas boiler, energy storage battery and photovoltaic power supply respectively; respectively the state variables of the ith CHP and the steam gas-fired boiler in the t period; for the corresponding operating cost; and starting and shutdown variables of the ith CHP and the steam gas boiler in the t period respectively; and the starting-up cost and the shutdown cost of the ith CHP and the steam gas-fired boiler in the t period respectively;the charge and discharge maintenance cost is the unit charge and discharge maintenance cost of the ith energy storage battery;is the charge and discharge power; k is a light abandoning penalty coefficient;andactual output and upper limit of the ith photovoltaic inverter in the t period are respectively;
the constraint conditions in step S300 include system operation constraints and operation constraints of each device;
wherein,
system operational constraints include:
and (3) system power balance constraint:
and (3) system heat energy balance constraint:
system tie line constraint:
in the formula,is the electrical load of the system for a period t;andthe charging power and the discharging power of the ith energy storage battery are respectively in the time t; htIs the thermal load of the system for a period t;andthe heating power of the ith steam gas-fired boiler and the CHP in the t period respectively;·andrespectively are the upper limit and the lower limit of a variable,P gridandpower purchase/sale restrictions for the system to the grid;
the equipment operating constraints include:
CHP operational safety and state coupling constraints:
the CHP combined heat and power generation efficiency can reach more than 70 percent, and the combined heat and power mode is generally adopted in the actual production, so that the following constraints are met:
in the formula, θ represents a thermoelectric ratio.
Gas internal combustion engine operation safety and state coupling constraint
On-off and state coupling constraints
Introducing startup and shutdown variables into the target, bringing startup cost and shutdown cost into a model, and considering the coupling relation of the startup and shutdown of the equipment and each time period of the equipment state:
in the formula, and starting and shutdown variables (0-1 variable) of the ith CHP and the steam internal combustion engine in the t period respectively;
initial state and on-off coupling constraints
Considering the initial start-stop state of the equipment before optimization, the additional constraints of the start-stop state and the running state of the equipment and the first optimization period are as follows:
photovoltaic inverter generated power constraint
Energy storage battery charge and discharge power constraint
Taking into account charging variablesAnd discharge variableCoupling constraints with charging and discharging power variables:
in the formula,andmaximum charge-discharge power limit;
energy storage battery power constraint
SOCi,T＝SOCi,1(21)
In the formula, SOCtThe energy storage capacity of the time interval t, α is a charge/discharge coefficient, and formula (21) is the energy storage balance constraint of the storage battery at the beginning and the end of the period;
finally, the linear transformation of step S400 specifically includes:
as shown in fig. 3, for a CHP, gas-fired steam boiler, the fuel consumption x as a function of the output y can be expressed as a non-linear equation:
y＝f(x)+ε (22)
wherein f (x) is a non-linear function; ε is the error.
Since the SOS2 method is an additional constraint method based on ordered variables and has wide application in solving the MINLP problem, the embodiment adopts the following conversion method to perform linear conversion on the day-ahead economic dispatch model of the integrated energy system.
In the formula,to ensure non-zero ziAdjacent to each other.
The following is a specific application case of this embodiment:
the case of a project demonstrated by an integrated energy system is shown in fig. 2. The system comprises photovoltaic equipment, CHP equipment, a gas internal combustion engine, a storage battery and other types of equipment, wherein the CHP equipment operates in a combined heat and power mode. The optimized time period is 1 day, and the time interval is 1 hour. The time-of-use electricity price is adopted as shown in the table 1; the thermal load data and the predicted contribution of thermal load and the predicted contribution of photovoltaic were shown in fig. 4. The program code is written by using Python, and the computing environment is as follows: intel (R) core (TM) i5-7200U2.5GHz, 8.0GB RAM.
TABLE 1 electric network & user time-sharing price
The results of the calculations for the controllable power supply are shown in figure 5.
Analysis of computational performance
TABLE 2 comparison of calculated Properties
In order to compare the performances of different solving kernels of the PuLp modeling tool and a conventional intelligent algorithm, the Cplex kernel, the CBC kernel (CORN-OR Branch and Cut, CBC) and the Particle swarm algorithm (PSO) are respectively adopted in the embodiment to solve the economic scheduling problem of the integrated energy system. As can be seen from Table 2 of the PSO algorithm, the PSO method is very close to the MILP method, but the MILP method obtains more accurate results. Compared with a default CBC kernel of Pulp, the method based on the Cplex kernel is a more efficient and accurate solving method, and is an ideal method for solving the IES economic scheduling problem. However, the CBC kernel is free of open source, and the calculation precision and time can meet the requirements, so that the method is a better engineering implementation method.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (5)
1. A day-ahead economic dispatching method of a comprehensive energy system is characterized by comprising the following steps: the method comprises the following steps:
s100, establishing an energy efficiency model aiming at maximizing economic benefits to meet the requirements of different users on electricity and heat under the conditions of supply and demand balance and operation constraint;
s200, establishing a model objective function; taking the maximization of the total profit as an objective function, namely subtracting the total cost of the system from the energy selling profit, wherein the total cost comprises the running cost, the starting cost and the shutdown cost of power supply, heat supply and gas supply;
s300, establishing a model constraint condition; the model needs to satisfy two types of constraints: system operating constraints and operating constraints of each device;
and S400, performing linear conversion on the model.
2. The integrated energy system day-ahead economic dispatch method of claim 1, wherein: the system constraints in the step S300 include a system power balance constraint, a system heat energy balance constraint and a system tie line constraint;
the operation constraints of the device comprise CHP operation safety and state coupling constraints, gas internal combustion engine operation safety and state coupling constraints, shutdown and state coupling constraints, initial state and startup and shutdown coupling constraints, photovoltaic inverter power generation constraints, energy storage battery charge and discharge power constraints and energy storage battery electric quantity constraints.
3. The integrated energy system day-ahead economic dispatch method of claim 1, wherein: the objective function in step S200 is expressed as follows:
cost of energy saleIncluding the cost of electricity sellingAnd cost of heat soldIn the formula, T is the number of scheduling time segments;the power selling quantity and the power selling price of the IES are respectively in the t period; ht、The heat supply amount and the heat supply price of the IES to the user in the t period are respectively;
cost of energy purchaseIncluding the cost of electricity purchaseAnd cost of gas purchaseIn the formula,the electricity purchasing quantity and the electricity purchasing price of the IES in the time period t are respectively;respectively the gas purchasing quantity and the gas purchasing price of the IES in the t period;
running cost Cop＝CCHP+CGSB+CBAT+CPVIncluding CHP operating cost CCHPGas internal combustion engine operating cost CGSBAnd the operation and maintenance cost of the storage battery CBATSum light cost CPV；
In the formula, NCHP, NGSB, NBAT and NPV are the number of CHP, steam gas boiler, energy storage battery and photovoltaic power supply respectively;respectively the state variables of the ith CHP and the steam gas-fired boiler in the t period;for the corresponding operating cost;andstarting and shutdown variables of the ith CHP and the steam gas boiler in the t period respectively;andthe starting-up cost and the shutdown cost of the ith CHP and the steam gas-fired boiler in the t period respectively;the charge and discharge maintenance cost is the unit charge and discharge maintenance cost of the ith energy storage battery;is the charge and discharge power; k is a light abandoning penalty coefficient;andthe actual output and the upper limit of the ith photovoltaic inverter in the t period are respectively.
4. The integrated energy system day-ahead economic dispatch method of claim 2, wherein: the expressions of the system operation constraint and the device operation constraint in step S300 are as follows:
1) system operational constraints
System power balance constraints
System thermal energy balance constraints
System tie line constraints
In the formula,is the electrical load of the system for a period t;andthe charging power and the discharging power of the ith energy storage battery are respectively in the time t; htIs the thermal load of the system for a period t;andthe heating power of the ith steam gas-fired boiler and the CHP in the t period respectively;·andrespectively are the upper limit and the lower limit of a variable,P gridandpower purchase/sale restrictions for the system to the grid;
2) plant operating constraints
CHP operational safety and state coupling constraints
In the formula, theta is a thermoelectric ratio;
safety of operation and coupled-state constraints of gas engines
Startup and shutdown and State coupling constraints
Introducing startup and shutdown variables into the target, bringing startup cost and shutdown cost into a model, and considering the coupling relation of the startup and shutdown of the equipment and each time period of the equipment state:
in the formula,andstarting and shutdown changes of the ith CHP and the steam internal combustion engine respectively in the t periodQuantity, the value of the startup and shutdown variables is an integer of 0-1;
initial State and Start-stop coupled constraints
Considering the initial start-stop state of the equipment before optimization, the additional constraints of the start-stop state and the running state of the equipment and the first optimization period are as follows:
photovoltaic inverter generated power constraint
Energy storage battery charge and discharge power constraints
Taking into account charging variablesAnd discharge variableCoupling constraints with charging and discharging power variables:
in the formula,andmaximum charge-discharge power limit;
energy storage battery power constraint
SOCi,T＝SOCi,1(21)
In the formula, SOCtThe energy storage capacity of the time period t, α is the charge/discharge coefficient, and the formula (21) is the constraint of the energy storage balance of the storage battery at the beginning and the end of the period.
5. The integrated energy system day-ahead economic dispatch method of claim 1, wherein: the step S400 is to perform linear conversion on the model, and includes:
for a CHP, gas-fired steam boiler, the functional relationship between the fuel consumption x and the output y is expressed as a nonlinear equation:
y＝f(x)+ε (22)
wherein f (x) is a non-linear function; epsilon is the error;
the method comprises the following steps of performing linear conversion on a day-ahead economic dispatching model of the comprehensive energy system by adopting a conversion method as follows:
in the formula,to ensure non-zero ziAdjacent to each other.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537443A (en) * | 2015-01-08 | 2015-04-22 | 国家电网公司 | Co-generation type micro-grid economy coordination and optimization dispatching method |
| CN106372742A (en) * | 2016-08-19 | 2017-02-01 | 天津大学 | Power-to-gas multi-source energy storage type microgrid day-ahead optimal economic dispatching method |
| CN106447113A (en) * | 2016-10-08 | 2017-02-22 | 东南大学 | Multi-region integrated energy system operation method based on operation optimization model |
| CN108173282A (en) * | 2017-12-29 | 2018-06-15 | 国网山东省电力公司电力科学研究院 | A kind of consideration electricity turns gas operating cost integrated energy system Optimization Scheduling |
| CN108494012A (en) * | 2018-01-31 | 2018-09-04 | 浙江工业大学 | A kind of meter and the electric regional complex energy resource system method for on-line optimization for turning gas technology |
| CN108830743A (en) * | 2018-05-25 | 2018-11-16 | 天津大学 | Consider the garden integrated energy system Optimization Scheduling of a variety of cold-storage devices |
| CN108932560A (en) * | 2018-06-13 | 2018-12-04 | 天津大学 | Garden integrated energy system Optimization Scheduling based on Model Predictive Control |
-
2019
- 2019-01-11 CN CN201910028006.2A patent/CN109670730B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537443A (en) * | 2015-01-08 | 2015-04-22 | 国家电网公司 | Co-generation type micro-grid economy coordination and optimization dispatching method |
| CN106372742A (en) * | 2016-08-19 | 2017-02-01 | 天津大学 | Power-to-gas multi-source energy storage type microgrid day-ahead optimal economic dispatching method |
| CN106447113A (en) * | 2016-10-08 | 2017-02-22 | 东南大学 | Multi-region integrated energy system operation method based on operation optimization model |
| CN108173282A (en) * | 2017-12-29 | 2018-06-15 | 国网山东省电力公司电力科学研究院 | A kind of consideration electricity turns gas operating cost integrated energy system Optimization Scheduling |
| CN108494012A (en) * | 2018-01-31 | 2018-09-04 | 浙江工业大学 | A kind of meter and the electric regional complex energy resource system method for on-line optimization for turning gas technology |
| CN108830743A (en) * | 2018-05-25 | 2018-11-16 | 天津大学 | Consider the garden integrated energy system Optimization Scheduling of a variety of cold-storage devices |
| CN108932560A (en) * | 2018-06-13 | 2018-12-04 | 天津大学 | Garden integrated energy system Optimization Scheduling based on Model Predictive Control |
Non-Patent Citations (3)
| Title |
|---|
| HAICHAO WANGA,ET AL.: "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage", 《APPLIED ENERGY》 * |
| 何仲潇: "多能协同的综合能源系统协调调度方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 徐帆，等: "机组耗量特性的混合整数模型建立与分析", 《电力系统自动化》 * |
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