CN110648252A - Building thermoelectric scheduling method based on flexible dynamic heat balance - Google Patents
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Abstract
The application belongs to the technical field of energy utilization, and particularly relates to a building thermoelectric scheduling method based on flexible dynamic thermal balance. The Combined Heat and Power (CHP) unit has much higher energy utilization efficiency than a unit which generates heat or electricity alone due to its cogeneration mode. However, the building thermoelectric scheduling of the CHP unit has the problems of poor accuracy, low efficiency and resource waste. The application provides a building thermoelectric scheduling method based on flexible dynamic thermal balance, once every delta t scheduling, be similar to the frequency conversion effect, can make CHP unit and outdoor ambient temperature in the actual conditions highly cooperate, avoid the wasting of resources when having satisfied the demand of building heat supply, have more economic nature, this application makes the mass flow rate scheduling of CHP unit natural gas consumption more accurate, practice thrift the cost while more friendly to the environment, be suitable for popularization and application in industry.
Description
Technical Field
The application relates to the technical field of energy utilization, in particular to a building thermoelectric scheduling method based on flexible dynamic thermal balance.
Background
The Combined Heat and Power (CHP) unit has much higher energy utilization efficiency than a unit which generates heat or electricity alone due to its cogeneration mode. Therefore, a CHP unit is taken as a core, a distributed comprehensive energy system is constructed, and the requirements of regional heat supply and partial power supply are met, so that a feasible energy supply popularization scheme is formed. The core is a combined heat and power dispatching method and a reasonable combined heat and power dispatching method, so that the heat and power supply requirements are met, fossil energy can be saved, and good environmental benefits and economic benefits are achieved.
The comprehensive energy system is complex in composition, many in coupling elements, the differences of research methods, time scales, system inertia and the like among all energy subsystems are obvious, and the combined scheduling difficulty is high. In the current research of the combined heat and power optimization scheduling, the heat load is generally assumed to be known, and most of the heat load is estimated in actual operation; however, in the existing research, a physical model of a specific heat load and a change relation between the heat load and the external environment temperature are not elaborated in detail, which is not favorable for the accuracy of the scheduling result of the thermal-electrical joint optimization.
Considering the comfortable indoor temperature expected by a human body, based on a static heat balance equation, by adopting a smaller simulation time length and considering the heat dissipation caused by the difference between the indoor temperature and the outdoor temperature of the building, a dynamic heat balance model of the building is provided to reflect the dynamic change process of the heat load and certain heat storage characteristics of the building, the heat storage characteristics can provide certain flexibility for the combined heat and power dispatching, and the supply and demand of heat energy and electric energy are cooperatively optimized and unified in an optimization framework on the basis. So as to solve the problems of poor accuracy and low efficiency of the existing combined heat and power dispatching scheme.
Disclosure of Invention
The application provides a building thermoelectric scheduling method based on flexible dynamic thermal balance, and aims to solve the problems of poor accuracy and low efficiency of the existing thermoelectric combined scheduling scheme.
The technical scheme adopted by the application is as follows:
a building thermoelectric scheduling method based on flexible dynamic heat balance comprises the following steps:
setting a scheduling time interval delta T and setting the indoor temperature T of the buildingin,t0+nΔt(n is 0, 1, …), and the building outdoor temperature T is setout,t0+nΔt(n is 0, 1, …), the comfort temperature T is setinWherein, in the step (A), andlower and upper comfortable temperature limits, respectively;
according to the indoor temperature T of the buildingin,t0+nΔtAnd building outdoor temperature Tout,t0+nΔtSolving the heat dissipation power of the building, wherein the formula is as follows:
Ph_out,t0+nΔt=KS(Tin,t0+nΔt-Tout,t0+nΔt)β(n=0,1,…)
in the formula, Ph_out,t0+nΔtIs composed oft0+nΔtThe heat dissipation power of the building at the moment, K is the heat transfer coefficient of the fence structure, S is the area of the fence structure, and beta is a dissipation correction coefficient;
solving the output of the CHP unit according to the equality relation between the dynamic heat required by the change of the indoor temperature of the building between two time intervals delta t and the heat power output by the CHP unit and the heat dissipation power consumed by the buildingThermal power P ofchp_h,t0+nΔtThe formula is as follows:
in the formula, CM is the product of equivalent specific heat capacity and mass of the building;
according to the relation between the natural gas consumed by the CHP unit with the fixed thermoelectric ratio and the generated electric power and thermal power:
K1MNG,t0+nΔt=aPchp_e,t0+nΔt+b (n=0,1,···)
K2Pchp_e,t0+nΔt=Pchp_h,t0+nΔt (n=0,1,···)
in the formula, K1(MWs/kg) is the heat value of unit natural gas, a and b are the energy conversion coefficient of CHP unit, K2Is a fixed thermoelectric ratio of the unit, Pchp_e,t0+nΔt(kW) and Pchp_h,t0+nΔt(kW) is respectively the electric power and the thermal power output by the CHP unit at the moment of t0+ n delta t, and the mass flow rate M of the natural gas consumption of the CHP unit is solvedNG,t0+nΔt(kg/s), the mass flow rate range for CHP unit natural gas consumption at time t0+ n Δ t is found as follows:
alternatively, if the CHP unit produces more electrical power than the building consumes, the CHP unit operates at the mass flow rate of natural gas consumptionOperating, if the CHP unit produces less electrical power than the building consumes, the CHP unit operates at a mass flow rate of natural gas consumptionOperating, if the electrical power consumed by the building is within the range of electrical power generated by the CHP unit, the CHP unit operates with the same electrical power generated as the electrical power consumed by the buildingAnd (6) rows.
Optionally, the time scale of the scheduling time interval Δ t is in the order of minutes.
Optionally, the scheduling time interval Δ t is 10 minutes.
Optionally, the building outdoor temperature Tout,t0+nΔtAnd predicting the outdoor temperature for the short-term weather forecast in the time period from t0+ n delta t to t0+ n delta t + delta t.
Optionally, the scheduling time interval Δ t is 30 s.
Optionally, the CM is the product of the equivalent building specific heat capacity and mass, and the equivalent building includes the building itself and the air inside the building.
The technical scheme adopted by the application has the following beneficial effects:
according to the method, the dispatching time interval delta t is set, and the dispatching is performed once every delta t, so that the resource waste caused by fixed CHP unit operation parameters is avoided; according to the indoor temperature of the building and the outdoor predicted temperature of the building, as the outdoor predicted temperature of the building is always changed in the day, the CHP unit operation parameters required by the indoor comfortable temperature of the building can be accurately measured through a relational expression between the heat required by the dynamic change of the indoor temperature of the building, the input heat power of the CHP unit and the heat dissipation power consumed by the building, so that the thermoelectric scheduling of the building can be more efficiently completed. Because the indoor comfortable temperature is a temperature interval, the CHP unit operating parameters also have an adjusting interval or an adjusting window, and the flexibility and the elasticity of the thermal load are embodied; and determining the optimal operation parameters of CHP unit scheduling, namely determining the mass flow rate of natural gas consumption of the CHP unit, by comparing and constraining the sizes of the electric power generated by the CHP unit and the electric power consumed by the building. According to the CHP unit operation parameter scheduling method and device, the CHP unit operation parameters are scheduled once at every interval delta t, the frequency conversion effect is similar, the outdoor temperature can be dynamically matched with that in the real situation, resource waste is avoided while the building heat supply requirement is met, the economy is improved, and the quality flow rate scheduling of the CHP unit natural gas consumption is more accurate.
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In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block flow diagram of an embodiment of the present application;
fig. 2 is a schematic scheduling diagram according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following examples do not represent all embodiments consistent with the present application. But merely as exemplifications of systems and methods consistent with certain aspects of the application, as recited in the claims.
Reference is made to fig. 1 and 2 for ease of understanding the technical solutions of the embodiments of the present application described below.
The application provides a building thermoelectric scheduling method based on flexible dynamic heat balance, which comprises the following steps:
s101, setting a scheduling time interval delta T and setting the indoor temperature T of the buildingin,t0+nΔt(n is 0, 1, …), and the building outdoor temperature T is setout,t0+nΔt(n is 0, 1, …), the comfort temperature T is setinWherein, in the step (A), andlower and upper comfortable temperature limits, respectively;
s102, according to the indoor temperature T of the buildingin,t0+nΔtAnd building outdoor temperature Tout,t0+nΔtSolving the heat dissipation power of the building, wherein the formula is as follows:
Ph_out,t0+nΔt=KS(Tin,t0+nΔt-Tout,t0+nΔt)β(n=0,1,…)
in the formula, Ph_out,t0+nΔtIs composed oft0+nΔtThe heat dissipation power of the building at the moment, K is the heat transfer coefficient of the fence structure, S is the area of the fence structure, and beta is a dissipation correction coefficient;
s103, solving the thermal power P output by the CHP unit according to the equality relation between the dynamic heat required by the indoor temperature of the building changing between two time intervals delta t and the thermal power output by the CHP unit and the building heat dissipation powerchp_h,t0+nΔtThe formula is as follows:
in the formula, CM is the product of equivalent specific heat capacity and mass of the building;
s104, according to the relation among natural gas consumed by the fixed thermoelectric ratio CHP unit, generated electric power and thermal power:
K1MNG,t0+nΔt=aPchp_e,t0+nΔt+b (n=0,1,···)
K2Pchp_e,t0+nΔt=Pchp_h,t0+nΔt (n=0,1,···)
in the formula, K1(MWs/kg) is the heat value of unit natural gas, a and b are the energy conversion coefficient of CHP unit, K2Is a fixed thermoelectric ratio of the unit, Pchp_e,t0+nΔt(kW) and Pchp_h,t0+nΔt(kW) is respectively the electric power and the thermal power output by the CHP unit at the moment of t0+ n delta t, and the mass flow rate M of the natural gas consumption of the CHP unit is solvedNG,t0+nΔt(kg/s), the mass flow rate range for CHP unit natural gas consumption at time t0+ n Δ t is found as follows:
in this embodiment, the scheduling time window is set at intervals of Δ t, which is different from the conventional technical scheme of using fixed scheduling parameters, and the scheduling parameters are usually set only once in the field at present, and the environmental temperature is often constantly changing in one day, and a large amount of resources are wasted when the CHP unit is operated by using the fixed parameters. Therefore, in this embodiment, the scheduling scheme is adjusted once every Δ t, that is, the operation parameters of the CHP unit are adjusted, so as to adapt to the ambient temperature that changes constantly in a day, when the ambient temperature outside the building is higher, the mass flow rate of the natural gas in the operation parameters of the CHP unit is appropriately reduced, when the ambient temperature outside the building is lower, the mass flow rate of the natural gas in the operation parameters of the CHP unit is correspondingly increased, so that the temperature inside the building is always within the temperature range that the human body feels comfortable, in addition, the temperature value that the human body feels comfortable has a range within which the temperature fluctuates, so that the human body feels comfortable, and therefore, the temperature that the human body feels comfortable has certain elasticity.
It is to be understood that in the present embodiment, there is a precondition that at time t0, the temperature of the building room has been defaulted to be within a temperature range in which the human body feels comfortable. In fact, in the present application, there is a precondition that the temperature in the building is defaulted to a temperature range in which the human body feels comfortable, regardless of the time node.
Alternatively, if the CHP unit produces more electrical power than the building consumes, the CHP unit operates at the mass flow rate of natural gas consumptionOperating, if the CHP unit produces less electrical power than the building consumes, the CHP unit operates at a mass flow rate of natural gas consumptionAnd if the electric power consumed by the building is in the electric power range generated by the CHP unit, the CHP unit operates to generate the same electric power as the electric power consumed by the building.
In this embodiment, cogeneration (also called cogeneration)Raw, English: cogeneration, combined heat and power, abbreviation: CHP) is the simultaneous generation of electricity and useful heat using a heat engine or power plant. The CHP unit in the application uses natural gas as fuel, generates heat energy and electric energy by burning the natural gas, and generates heat power and electric power respectively as Pchp_h,t0+nΔt(kW) and Pchp_e,t0+nΔt(kW). Since the CHP units in this application are primarily intended to supply heat, even if the building maintains a comfortable temperature for the human body, the electrical energy generated at the same time is used for power consumption in the building. In this embodiment, considering the electrical power consumed by the building, the CHP unit is operated at the lowest cost natural gas mass flow rate: if the CHP unit generates more electric power than the building consumes, the CHP unit will use the mass flow rate of the natural gas consumptionThe power consumption of the building is low at the moment, and the electric energy generated by the CHP unit can be completely met, so that the temperature and power consumption requirements of the building can be met only by operating the CHP unit at the lowest value of the comfortable temperature of the human body; similarly, if the CHP unit produces less electrical power than the building consumes, the CHP unit will operate at the mass flow rate of natural gas consumptionThe operation is carried out, and at the moment, insufficient electric energy is purchased from the power grid, so that the economic requirement can be met; if the electric power consumed by the building is in the electric power range generated by the CHP unit, the CHP unit operates by generating the same electric power as the electric power consumed by the building, at the moment, the electric energy generated by the CHP unit is equal to the electric energy consumed by the building, and meanwhile, the generated heat energy keeps the temperature in the building in the temperature range comfortable for human bodies.
Optionally, the time scale of the scheduling time interval Δ t is in the order of minutes.
In the embodiment, the time scale of the scheduling time interval delta t is further limited to be in the minute level, so that the scheduling is more frequent, the fluctuation of the external environment temperature is more sensitive, the intelligence of the method is also embodied, the adjustment is more accurate and timely, the consumption of natural gas is further reduced, and the cost is saved.
Optionally, the scheduling time interval Δ t is 10 minutes.
In this embodiment, the scheduling time interval Δ t is set to 10 minutes, and is adjusted six times per hour, which is convenient for scheduling and is simpler and more convenient in the actual operation process.
Optionally, the building outdoor temperature Tout,t0+nΔtAnd predicting the outdoor temperature for the short-term weather forecast in the time period from t0+ n delta t to t0+ n delta t + delta t.
In this embodiment, in order to guide and provide a standard for scheduling, the outdoor predicted temperature in the time period from T0+ n Δ T to T0+ n Δ T + Δ T needs to be known, and T is known through short-term weather forecastout,t0+nΔtAnd data support is provided for a scheduling scheme, so that scheduling is more consistent with the rule of outdoor temperature change in one day, the indoor temperature is always kept at the comfortable temperature of a human body, and resources are saved to the maximum extent.
Optionally, the scheduling time interval Δ t is 30 s.
In this embodiment, the scheduling time interval Δ t is set to 30 seconds, so as to further shorten the scheduling time interval, and since the 30-second time interval is very short, the CHP unit can be operated in real time and can adapt to the ambient temperature very quickly, thereby achieving the effect of adjusting the indoor temperature of the building to the comfortable temperature of human body.
Optionally, the CM is the product of the equivalent building specific heat capacity and mass, and the equivalent building includes the building itself and the air inside the building.
In the embodiment, the CM is the product of the equivalent specific heat capacity and the mass of the building, the effect of influencing the heat storage of the building is also considered to exist in the air in the building, when the building physics is thought to be the equivalent building operation parameter, the air in the building is also added into the equivalent building model parameter, the operation can be more accurate, the scheduling is more in line with the actual situation, the accurate scheduling is realized, and the temperature in the building is further ensured to be in the comfortable temperature range of the human body.
According to the method, the dispatching time interval delta t is set, and the dispatching is performed once every delta t, so that the resource waste caused by fixed CHP unit operation parameters is avoided; according to the indoor temperature of the building and the outdoor predicted temperature of the building, as the outdoor predicted temperature of the building is always changed in the day, the CHP unit operation parameters required by the indoor comfortable temperature of the building can be accurately measured through a relational expression between the heat required by the dynamic change of the indoor temperature of the building, the input heat power of the CHP unit and the heat dissipation power consumed by the building, so that the thermoelectric scheduling of the building can be more efficiently completed. Because the indoor comfortable temperature is a temperature interval, the CHP unit operating parameters also have an adjusting interval or an adjusting window, and the flexibility and the elasticity of the thermal load are embodied; and determining the optimal operation parameters of CHP unit scheduling, namely determining the mass flow rate of natural gas consumption of the CHP unit, by comparing and constraining the sizes of the electric power generated by the CHP unit and the electric power consumed by the building. According to the CHP unit operation parameter scheduling method and device, the CHP unit operation parameters are scheduled once at every interval delta t, the frequency conversion effect is similar, the outdoor temperature can be dynamically matched with that in the real situation, resource waste is avoided while the building heat supply requirement is met, the economy is improved, and the quality flow rate scheduling of the CHP unit natural gas consumption is more accurate.
The embodiments provided in the present application are only a few examples of the general concept of the present application, and do not limit the scope of the present application. Any other embodiments extended according to the scheme of the present application without inventive efforts will be within the scope of protection of the present application for a person skilled in the art.
Claims (7)
1. A building thermoelectric scheduling method based on flexible dynamic heat balance is characterized by comprising the following steps:
setting a scheduling time interval delta T and setting the indoor temperature T of the buildingin,t0+nΔtTin,t0+nΔt(n is 0, 1, …), and the building outdoor temperature T is setout,t0+nΔt(n is 0, 1, …), the comfort temperature T is setinWherein, in the step (A), andlower and upper comfortable temperature limits, respectively;
according to the indoor temperature T of the buildingin,t0+nΔtAnd building outdoor temperature Tout,t0+nΔtSolving the heat dissipation power of the building, wherein the formula is as follows:
Ph_out,t0+nΔt=KS(Tin,t0+nΔt_Tout,t0+nΔt)β(n=0,1,…)
in the formula, Ph_out,t0+nΔtThe heat dissipation power of the building at the time t0+ n delta t, K is the heat transfer coefficient of the fence structure, S is the area of the fence structure, and beta is the dissipation correction coefficient;
solving the thermal power P output by the CHP unit according to the equality relation between the dynamic heat required by the change of the indoor temperature of the building between two time intervals delta t and the thermal power output by the CHP unit and the building heat dissipation powerchp_h,t0+nΔtThe formula is as follows:
in the formula, CM is the product of equivalent specific heat capacity and mass of the building;
according to the relation between the natural gas consumed by the CHP unit with the fixed thermoelectric ratio and the generated electric power and thermal power:
K1MNG,t0+nΔt=aPchp_e,t0+nΔt+b(n=0,1,…)
K2Pchp_e,t0+nΔt=Pchp_h,t0+nΔt(n=0,1,…)
in the formula, K1(MWs/kg) is the heat value of unit natural gas, a and b are the energy conversion coefficient of CHP unit, K2Is a fixed thermoelectric ratio of the unit, Pchp_e,t0+nΔt(kW) and Pchp_h,t0+nΔt(kW) is respectively the electric power and the thermal power output by the CHP unit at the moment of t0+ n delta t, and the mass flow rate M of the natural gas consumption of the CHP unit is solvedNG,t0+nΔt(kg/s), the mass flow rate range for CHP unit natural gas consumption at time t0+ n Δ t is found as follows:
2. the building thermoelectric scheduling method based on flexible dynamic heat balance of claim 1,
if the CHP unit generates more electric power than the building consumes, the CHP unit will use the mass flow rate of the natural gas consumptionOperating, if the CHP unit produces less electrical power than the building consumes, the CHP unit operates at a mass flow rate of natural gas consumptionAnd if the electric power consumed by the building is in the electric power range generated by the CHP unit, the CHP unit operates to generate the same electric power as the electric power consumed by the building.
3. The building thermoelectric scheduling method based on flexible dynamic thermal balance of claim 1 wherein the time scale of the scheduling time interval Δ t is in the order of minutes.
4. The flexible dynamic heat balance based building thermoelectric scheduling method of claim 1 wherein the scheduling time interval Δ t is 10 minutes.
5. The building thermoelectric scheduling method based on flexible dynamic heat balance of claim 1, wherein the building outdoor temperature Tout,t0+nΔtAnd predicting the outdoor temperature for the short-term weather forecast in the time period from t0+ n delta t to t0+ n delta t + delta t.
6. The building thermoelectric scheduling method based on flexible dynamic thermal balance of claim 1, wherein the scheduling time interval Δ t is 30 s.
7. The flexible dynamic heat balance based building thermoelectric scheduling method of claim 1 wherein the CM is an equivalent building specific heat capacity multiplied by mass, the equivalent building comprising the building itself and the air inside the building.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112524749A (en) * | 2020-12-04 | 2021-03-19 | 武汉舒适易佰科技有限公司 | Energy consumption controller |
CN116128163A (en) * | 2023-04-13 | 2023-05-16 | 国网天津静海供电有限公司 | Comprehensive energy optimization method and device considering green hydrogen production and storage and user satisfaction |
Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105207205A (en) * | 2015-09-16 | 2015-12-30 | 国网天津市电力公司 | Distributed energy system energy optimization regulation and control method fusing demand side response |
CN105931136A (en) * | 2016-04-25 | 2016-09-07 | 天津大学 | Building micro-grid optimization scheduling method with demand side virtual energy storage system being fused |
CN106960272A (en) * | 2017-02-28 | 2017-07-18 | 天津大学 | Building microgrid Multiple Time Scales Optimization Scheduling containing virtual energy storage |
CN106998079A (en) * | 2017-04-28 | 2017-08-01 | 东南大学 | A kind of modeling method of combined heat and power Optimal Operation Model |
CN107464008A (en) * | 2016-06-02 | 2017-12-12 | 南京理工大学 | A kind of Optimization Scheduling of large buildings cooling heating and power generation system |
CN107642772A (en) * | 2017-09-11 | 2018-01-30 | 国家电网公司 | Cogeneration cooling heating system meets workload demand progress control method simultaneously |
CN108151132A (en) * | 2017-11-27 | 2018-06-12 | 国网北京市电力公司 | Control method, device and system and the air source heat pump of air source heat pump |
CN108229025A (en) * | 2018-01-04 | 2018-06-29 | 东南大学 | A kind of more microgrid active distribution system economic optimization dispatching methods of supply of cooling, heating and electrical powers type |
CN109255560A (en) * | 2018-11-20 | 2019-01-22 | 成都大学 | A kind of CCHP system evaluation optimization method based on cool and thermal power load proportion |
CN109284939A (en) * | 2018-10-26 | 2019-01-29 | 南方电网科学研究院有限责任公司 | Thermoelectric combined random production simulation method, device and equipment of comprehensive energy system |
CN109301871A (en) * | 2018-11-13 | 2019-02-01 | 中国科学院广州能源研究所 | The wisdom energy adjustment system of garden distributed energy microgrid |
CN109376912A (en) * | 2018-09-29 | 2019-02-22 | 东南大学 | Cooling heating and power generation system running optimizatin method based on civil building thermal inertia |
CN109711601A (en) * | 2018-11-28 | 2019-05-03 | 国网浙江省电力有限公司电力科学研究院 | The hot integrated energy system distributed optimization dispatching method of electric-gas-and device |
CN110188492A (en) * | 2019-06-04 | 2019-08-30 | 南通大学 | A kind of supply of cooling, heating and electrical powers microgrid Optimization Scheduling considering heat supply network characteristic |
CN110244566A (en) * | 2019-06-24 | 2019-09-17 | 燕山大学 | The cooling heating and power generation system capacity configuration optimizing method of meter and flexible load |
-
2019
- 2019-09-26 CN CN201910915190.2A patent/CN110648252A/en active Pending
Patent Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105207205A (en) * | 2015-09-16 | 2015-12-30 | 国网天津市电力公司 | Distributed energy system energy optimization regulation and control method fusing demand side response |
CN105931136A (en) * | 2016-04-25 | 2016-09-07 | 天津大学 | Building micro-grid optimization scheduling method with demand side virtual energy storage system being fused |
CN107464008A (en) * | 2016-06-02 | 2017-12-12 | 南京理工大学 | A kind of Optimization Scheduling of large buildings cooling heating and power generation system |
CN106960272A (en) * | 2017-02-28 | 2017-07-18 | 天津大学 | Building microgrid Multiple Time Scales Optimization Scheduling containing virtual energy storage |
CN106998079A (en) * | 2017-04-28 | 2017-08-01 | 东南大学 | A kind of modeling method of combined heat and power Optimal Operation Model |
CN107642772A (en) * | 2017-09-11 | 2018-01-30 | 国家电网公司 | Cogeneration cooling heating system meets workload demand progress control method simultaneously |
CN108151132A (en) * | 2017-11-27 | 2018-06-12 | 国网北京市电力公司 | Control method, device and system and the air source heat pump of air source heat pump |
CN108229025A (en) * | 2018-01-04 | 2018-06-29 | 东南大学 | A kind of more microgrid active distribution system economic optimization dispatching methods of supply of cooling, heating and electrical powers type |
CN109376912A (en) * | 2018-09-29 | 2019-02-22 | 东南大学 | Cooling heating and power generation system running optimizatin method based on civil building thermal inertia |
CN109284939A (en) * | 2018-10-26 | 2019-01-29 | 南方电网科学研究院有限责任公司 | Thermoelectric combined random production simulation method, device and equipment of comprehensive energy system |
CN109301871A (en) * | 2018-11-13 | 2019-02-01 | 中国科学院广州能源研究所 | The wisdom energy adjustment system of garden distributed energy microgrid |
CN109255560A (en) * | 2018-11-20 | 2019-01-22 | 成都大学 | A kind of CCHP system evaluation optimization method based on cool and thermal power load proportion |
CN109711601A (en) * | 2018-11-28 | 2019-05-03 | 国网浙江省电力有限公司电力科学研究院 | The hot integrated energy system distributed optimization dispatching method of electric-gas-and device |
CN110188492A (en) * | 2019-06-04 | 2019-08-30 | 南通大学 | A kind of supply of cooling, heating and electrical powers microgrid Optimization Scheduling considering heat supply network characteristic |
CN110244566A (en) * | 2019-06-24 | 2019-09-17 | 燕山大学 | The cooling heating and power generation system capacity configuration optimizing method of meter and flexible load |
Non-Patent Citations (2)
Title |
---|
孙龙印: "冷热电联供型微网优化调度的研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
尹宝泉: "绿色建筑多功能能源***集成机理研究", 《中国博士学位论文全文数据库工程科技II辑》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112524749A (en) * | 2020-12-04 | 2021-03-19 | 武汉舒适易佰科技有限公司 | Energy consumption controller |
CN116128163A (en) * | 2023-04-13 | 2023-05-16 | 国网天津静海供电有限公司 | Comprehensive energy optimization method and device considering green hydrogen production and storage and user satisfaction |
CN116128163B (en) * | 2023-04-13 | 2023-06-30 | 国网天津静海供电有限公司 | Comprehensive energy optimization method and device considering green hydrogen production and storage and user satisfaction |
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