CN109064062B - User-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction - Google Patents
User-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction Download PDFInfo
- Publication number
- CN109064062B CN109064062B CN201811057762.XA CN201811057762A CN109064062B CN 109064062 B CN109064062 B CN 109064062B CN 201811057762 A CN201811057762 A CN 201811057762A CN 109064062 B CN109064062 B CN 109064062B
- Authority
- CN
- China
- Prior art keywords
- energy
- user
- energy system
- comprehensive energy
- heat
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000003993 interaction Effects 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims abstract description 36
- 230000008878 coupling Effects 0.000 title claims abstract description 32
- 238000010168 coupling process Methods 0.000 title claims abstract description 32
- 238000005859 coupling reaction Methods 0.000 title claims abstract description 32
- 238000012502 risk assessment Methods 0.000 title claims description 14
- 238000006243 chemical reaction Methods 0.000 claims abstract description 40
- 230000005540 biological transmission Effects 0.000 claims abstract description 33
- 238000011156 evaluation Methods 0.000 claims abstract description 9
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 238000000342 Monte Carlo simulation Methods 0.000 claims abstract description 4
- 238000004088 simulation Methods 0.000 claims abstract description 4
- 230000005611 electricity Effects 0.000 claims description 13
- 238000005485 electric heating Methods 0.000 claims description 12
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000010438 heat treatment Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 12
- 239000007789 gas Substances 0.000 description 9
- 239000003345 natural gas Substances 0.000 description 6
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000005057 refrigeration Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for evaluating the running risk of a user-side comprehensive energy system by considering multi-energy coupling interaction, which adopts Monte Carlo method simulation, comprehensively considers the energy supply and the demand of the user-side comprehensive energy system and establishes a collaborative analysis model of the user-side comprehensive energy interaction system; calculating the operation risk evaluation index of the comprehensive energy system at the user side by combining the outage rate parameters of each energy transmission and conversion element; the method can more accurately evaluate the operation risk of the user side comprehensive energy system, and can improve the flexibility and the safety and the stability of the user side energy utilization strategy.
Description
Technical Field
The invention belongs to the technical field of power systems, and relates to a method for evaluating operation risks of a user-side comprehensive energy system by considering multi-energy coupling interaction.
Background
With the advance of the reformation process of the electric power market, the comprehensive energy system becomes an important trend of future energy development. Compared with the traditional power distribution network function mode, the user side comprehensive energy system can provide various energy sources such as electricity, heat, cold and gas for the user, and the flexibility of the user side energy utilization strategy is improved by utilizing the bidirectional interaction potential of different energy sources. However, the complex energy conversion mechanism of the user-side integrated energy system brings risks to safe and stable power supply, and the conventional power system risk assessment method cannot meet the requirements, so that a user-side integrated energy system operation risk assessment method considering multi-energy coupling interaction is urgently needed.
Disclosure of Invention
The invention aims to provide a method for evaluating the operation risk of a comprehensive energy system at a user side by considering multi-energy coupling interaction, which considers the influence of the coupling interaction relation of various energy sources on the transmission and conversion on the system and can more accurately evaluate the operation risk of the comprehensive energy system at the user side.
Therefore, the invention adopts the following technical scheme:
a user side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction adopts Monte Carlo method simulation, and comprises the following steps:
step 1, initializing energy supply and demand of a user side comprehensive energy system, and establishing a user side comprehensive energy interaction system collaborative analysis model;
step 2, initializing shutdown rate parameters of all elements of the comprehensive energy system;
step 3, randomly generating real-time states of all elements according to the shutdown rate parameters of all energy transmission and conversion elements;
step 4, updating the energy transmission/transformation matrix parameters based on the real-time states of all the elements;
step 5, calculating an operation risk evaluation index of the user-side comprehensive energy system;
and 6, judging whether the risk assessment index meets the convergence condition, if not, returning to the step 3, and if so, ending and outputting the risk assessment index value.
In the above method for evaluating the operation risk of the integrated energy system at the user side considering the multi-energy coupling interaction, the supply of the integrated energy system in step 1 can be obtained by a system day-ahead and day-time scheduling plan; the demand of the comprehensive energy system can be obtained through load prediction; the implementation of step 1 comprises:
the user-side comprehensive energy interaction system collaborative analysis model fully considers the coupling interaction relation of the comprehensive energy system in transmission and conversion of various energy sources. The user-side comprehensive energy system adopts an energy hub model, and the specific description of the model is as follows:
(1) in the formula, Le、Lh、Lc、LgRespectively representing the requirements of electricity, heat, cold and gas of a user; pe、Ph、Pc、PgRespectively representing the supply of electricity, heat, cold and gas of the comprehensive energy system; v represents the distribution coefficient of the energy, eta represents the transmission/conversion efficiency of the system energy, the subscripts of the two represent the transmission and conversion direction of the energy, such as ee represents the electric energy for the electric load, eh represents the electric energy for the heating, ec represents the electric energy for the refrigeration, eg represents the electric energy for the natural gas production, and gh represents the natural gas for the heating. Other energy conversion modes from low-grade energy (heat and cold) to high-grade energy (electricity and gas), such as the mode of converting he heat energy into electric energy, the mode of converting hg heat energy into natural gas, and the mode of converting ce and cg, have extremely low efficiency or are difficult to realize technically, so the energy conversion modes are not considered in the user-side integrated energy interaction system, and the energy distribution coefficients and the energy transmission/conversion efficiency are set to be 0. Using electric energy for heating, vehExpressing the distribution coefficient, eta, of heat energy converted from electric energyehEnergy efficiency ratio representing system integrated electric heating:
(2) in the formula QiThe input electric quantity of the ith electric heating equipment is represented, and K represents the total number of electric-to-heat equipment, including an air conditioner, a heat pump, a thermoelectric unit and the like. The other subscripts are calculated similarly.
In the above method for evaluating the operation risk of the integrated energy system at the user side considering the multi-energy coupling interaction, the outage rate parameter of the integrated energy system component in step 2 can be obtained from historical statistical data;
in the above method for evaluating the operation risk of the user-side integrated energy system considering the multi-energy coupling interaction, the step 3 can be implemented by generating the real-time state (normal and shutdown) of the element according to the component shutdown rate through a computer;
in the above method for assessing the operational risk of the user-side integrated energy system considering the multi-energy coupling interaction, the step 4 is implemented by:
in the method for evaluating the risk of the integrated energy system, the considered risk evaluation period is short, the distribution coefficient v is kept unchanged, the energy transmission/conversion efficiency eta is related to the real-time state of the integrated energy system equipment, and the expected energy transmission/conversion efficiency at a certain moment is calculated by taking the electricity-heat conversion efficiency as an example:
(3) in the formula piRepresenting the probability of the shutdown of the ith electric heating equipment; n represents the number of electric heating equipment outages;
in the above method for evaluating operation risk of a user-side integrated energy system considering multi-energy coupling interaction, the operation risk evaluation index in step 5 includes: the electric load loss, the heat load loss, the cold load loss and the air load loss.
In the above method for assessing operational risk of a user-side integrated energy system considering multi-energy coupling interaction, step 5 includes:
based on the updated energy transmission/conversion matrix in the step 4 and an energy supply matrix of the user-side comprehensive energy system, calculating by the following formula:
(4) in the formula, Le'、Lh'、Lc'、Lg' actual supply amounts of electricity, heat, cold, and gas to the user, respectively; eta' represents the integrated energy transmission/conversion efficiency of the system in the real-time state.
The calculation method of the four indexes of the electric load loss, the heat load loss, the cold load loss and the air load loss is as follows:
wherein L isx＝Le,Lh,Lc,Lg。
In the above method for evaluating the operation risk of the integrated energy system at the user side considering the multi-energy coupling interaction, the convergence condition in step 6 is:
wherein M represents the number of cycles of step 3 to step 6; e (Δ L)x) Represents Δ LxThe mean value of (a); σ (Δ L)x) Represents Δ LxStandard deviation of (2).
The invention has the following beneficial effects:
the method is an evaluation method which fully considers the influence of user behaviors on the operation risk of the comprehensive energy system under the background of the multi-energy coupling interaction relationship of the comprehensive energy system at the user side; the operation risk assessment method considers the influence of the coupling interaction relation of various energy sources on transmission and conversion on the system, can more accurately assess the operation risk of the user side comprehensive energy system, and can improve the flexibility and the safety and the stability of the user side energy utilization strategy.
Detailed Description
The invention relates to a method for evaluating the operation risk of a comprehensive energy system at a user side by considering multi-energy coupling interaction, which adopts Monte Carlo method simulation and comprises the following steps:
step 1, initializing energy supply and demand of a user side comprehensive energy system, and establishing a user side comprehensive energy interaction system collaborative analysis model;
step 2, initializing shutdown rate parameters of all elements of the comprehensive energy system;
step 3, randomly generating real-time states of all elements according to the shutdown rate parameters of all energy transmission and conversion elements;
step 4, updating the energy transmission/transformation matrix parameters based on the real-time states of all the elements;
step 5, calculating an operation risk evaluation index of the user-side comprehensive energy system;
and 6, judging whether the risk assessment index meets the convergence condition, if not, returning to the step 3, and if so, ending and outputting the risk assessment index value.
In the above method for evaluating the operation risk of the integrated energy system at the user side considering the multi-energy coupling interaction, the supply of the integrated energy system in step 1 can be obtained by a system day-ahead and day-time scheduling plan; the demand of the comprehensive energy system can be obtained through load prediction; the implementation of step 1 comprises:
the user-side comprehensive energy interaction system collaborative analysis model fully considers the coupling interaction relation of the comprehensive energy system in transmission and conversion of various energy sources. The user-side comprehensive energy system adopts an energy hub model, and the specific description of the model is as follows:
(1) in the formula, Le、Lh、Lc、LgRespectively representing the requirements of electricity, heat, cold and gas of a user; pe、Ph、Pc、PgRespectively representing the supply of electricity, heat, cold and gas of the comprehensive energy system; v represents the distribution coefficient of the energy, eta represents the transmission/conversion efficiency of the system energy, the subscripts of the two represent the transmission and conversion direction of the energy, such as ee represents the electric energy for the electric load, eh represents the electric energy for the heating, ec represents the electric energy for the refrigeration, eg represents the electric energy for the natural gas production, and gh represents the natural gas for the heating. Other forms of conversion from low-grade energy (hot, cold) to high-grade energy (electricity, gas), such as he heat energy for generating electric energy, hg heat energy for generating natural gas, ce, cg energy conversion, are extremely inefficient or technically difficult to implement, and therefore are not considered in the user-side integrated energy interactive system according to the present invention, and these energy distribution coefficients and energy transmission/conversion efficiencies are set to 0. Using electric energy for heating, vehExpressing the distribution coefficient, eta, of heat energy converted from electric energyehEnergy efficiency ratio representing system integrated electric heating:
(2) in the formula QiThe input electric quantity of the ith electric heating equipment is represented, and K represents the total number of electric-to-heat equipment, including an air conditioner, a heat pump, a thermoelectric unit and the like.
In the above method for evaluating the operation risk of the integrated energy system at the user side considering the multi-energy coupling interaction, the outage rate parameter of the integrated energy system component in step 2 can be obtained from historical statistical data;
in the above method for evaluating the operation risk of the user-side integrated energy system considering the multi-energy coupling interaction, the step 3 can be implemented by generating the real-time state (normal and shutdown) of the element according to the component shutdown rate through a computer;
in the above method for assessing the operational risk of the user-side integrated energy system considering the multi-energy coupling interaction, the step 4 is implemented by:
in the method for evaluating the risk of the integrated energy system, the considered risk evaluation period is short, the distribution coefficient v is kept unchanged, the energy transmission/conversion efficiency eta is related to the real-time state of the integrated energy system equipment, and the expected energy transmission/conversion efficiency at a certain moment is calculated by taking the electricity-heat conversion efficiency as an example:
(3) in the formula piRepresenting the probability of the shutdown of the ith electric heating equipment; n represents the number of electric heating equipment outages;
in the above method for evaluating operation risk of a user-side integrated energy system considering multi-energy coupling interaction, the operation risk evaluation index in step 5 includes: the electric load loss, the heat load loss, the cold load loss and the air load loss.
In the above method for assessing operational risk of a user-side integrated energy system considering multi-energy coupling interaction, step 5 includes:
based on the updated energy transmission/conversion matrix in the step 4 and an energy supply matrix of the user-side comprehensive energy system, calculating by the following formula:
(4) in the formula, Le'、Lh'、Lc'、Lg' actual supply amounts of electricity, heat, cold, and gas to the user, respectively; eta' represents the integrated energy transmission/conversion efficiency of the system in the real-time state.
The calculation method of the four indexes of the electric load loss, the heat load loss, the cold load loss and the air load loss is as follows:
wherein L isx＝Le,Lh,Lc,Lg。
In the above method for evaluating the operation risk of the integrated energy system at the user side considering the multi-energy coupling interaction, the convergence condition in step 6 is:
wherein M represents the number of cycles of step 3 to step 6; e (Δ L)x) Represents Δ LxThe mean value of (a); σ (Δ L)x) Represents Δ LxStandard deviation of (2).
Claims (4)
1. A user-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction is characterized in that the method adopts Monte Carlo method simulation, and comprises the following steps:
step 1, initializing energy supply and demand of a user side comprehensive energy system, and establishing a user side comprehensive energy interaction system collaborative analysis model;
step 2, initializing shutdown rate parameters of all elements of the comprehensive energy system;
step 3, randomly generating real-time states of all elements according to the shutdown rate parameters of all energy transmission and conversion elements;
step 4, updating the energy transmission/transformation matrix parameters based on the real-time states of all the elements;
step 5, calculating an operation risk evaluation index of the user-side comprehensive energy system;
step 6, judging whether the risk assessment index meets the convergence condition, if not, returning to the step 3, and if so, ending and outputting a risk assessment index value;
the step 1 specifically comprises the following steps: initializing energy supply of the comprehensive energy system at the user side according to the day-ahead and day-time scheduling plans of the system, and initializing the demand of the comprehensive energy system through load prediction; the method comprises the following steps of taking coupling interaction relation of the comprehensive energy system in transmission and conversion of various energy sources into full consideration, establishing a user side comprehensive energy interaction system collaborative analysis model, wherein the user side comprehensive energy system adopts an energy hub model, and the model is specifically described as follows:
(1) in the formula, Le、Lh、Lc、LgRespectively representing the requirements of electricity, heat, cold and gas of a user; pe、Ph、Pc、PgRespectively representing the supply of electricity, heat, cold and gas of the comprehensive energy system; v represents the distribution coefficient of the energy, eta represents the energy transmission/conversion efficiency of the system, subscripts of the two represent the transmission conversion direction of the energy, and the conversion form from low-grade energy heat, cold to high-grade energy electricity and gas is not considered in the system because the efficiency is extremely low or is difficult to realize technically, and the application energy distribution coefficient and the energy transmission/conversion efficiency are set to be 0; using electric energy for heating, vehExpressing the distribution coefficient, eta, of heat energy converted from electric energyehEnergy efficiency ratio representing system integrated electric heating:
(2) in the formula QiThe input electric quantity of the ith electric heating equipment is represented, and K represents the total number of the electric-to-heat equipment; the rest subscripts are calculated in the same way;
the operation risk assessment index in step 5 comprises: the method comprises four indexes of electric load loss, heat load loss, cold load loss and air load loss;
based on the updated energy transmission/conversion matrix in the step 4 and an energy supply matrix of the user-side comprehensive energy system, calculating by the following formula:
(4) in the formula, Le'、Lh'、Lc'、Lg' actual supply amounts of electricity, heat, cold, and gas to the user, respectively; η' represents the desired overall energy transfer/conversion efficiency of the system at this real-time state;
four indexes of electric load loss, heat load loss, cold load loss and air load loss Delta LxThe calculation method of (2) is as follows:
wherein L isx＝Le,Lh,Lc,Lg。
2. The method for assessing operational risk of an integrated energy system on a user side considering multi-energy coupling interaction as claimed in claim 1, wherein the outage rate parameter of the integrated energy system component of step 2 is obtained from historical statistical data.
3. The method for assessing operational risk of a comprehensive energy system on the user side considering the multi-energy coupling interaction as claimed in claim 1, wherein the step 4 is implemented as follows: for a certain energy transmission and conversion direction, the distribution coefficient v is kept unchanged, the energy transmission/conversion efficiency eta is related to the real-time state of the integrated energy system equipment, and the expected energy transmission/conversion efficiency at a certain moment is calculated by taking the electricity-heat conversion efficiency as an example:
(3) in the formula piRepresenting the probability of the shutdown of the ith electric heating equipment; n represents the number of electric heating apparatus stoppages.
4. The method for assessing risk of operation of a comprehensive energy system on a user side considering multi-energy coupling interaction according to claim 1, wherein the convergence condition in step 6 is:
wherein M represents the number of times steps 3 to 6 have been cycled; e (Δ L)x) Represents each load loss Δ LxThe mean value of (a); σ (Δ L)x) Represents Δ LxStandard deviation of (2).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811057762.XA CN109064062B (en) | 2018-09-11 | 2018-09-11 | User-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811057762.XA CN109064062B (en) | 2018-09-11 | 2018-09-11 | User-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109064062A CN109064062A (en) | 2018-12-21 |
| CN109064062B true CN109064062B (en) | 2021-08-06 |
Family
ID=64760245
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811057762.XA Active CN109064062B (en) | 2018-09-11 | 2018-09-11 | User-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109064062B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109494816B (en) * | 2018-12-28 | 2020-07-31 | 清华-伯克利深圳学院筹备办公室 | Risk assessment method and device for electric-thermal coupling multi-energy flow system |
| CN109993445B (en) * | 2019-04-04 | 2021-07-30 | 国家电网有限公司 | Comprehensive energy system vulnerability assessment method considering photovoltaic prediction error |
| CN110390476B (en) * | 2019-07-10 | 2021-12-10 | 浙江大学 | Self-scheduling operation reliability improving method of comprehensive energy equipment |
| CN110288411B (en) * | 2019-07-23 | 2023-06-20 | 贵州电网有限责任公司 | Information integration construction method of comprehensive energy system |
| CN111242406B (en) * | 2019-11-29 | 2023-10-24 | 国网浙江省电力有限公司 | User side energy outage risk processing method of comprehensive energy interactive system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102694844A (en) * | 2012-03-12 | 2012-09-26 | 李宗诚 | Internet EMK/ICT technology design basis |
| JP2013070497A (en) * | 2011-09-22 | 2013-04-18 | Hitachi Ltd | Electric power information management system |
| CN103259335A (en) * | 2013-04-11 | 2013-08-21 | 国家电网公司 | Intelligent demand response and demand side optimizing operation system |
| 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 |
| CN107910871A (en) * | 2017-11-30 | 2018-04-13 | 国网天津市电力公司 | A kind of energy internet is provided multiple forms of energy to complement each other control method |
-
2018
- 2018-09-11 CN CN201811057762.XA patent/CN109064062B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013070497A (en) * | 2011-09-22 | 2013-04-18 | Hitachi Ltd | Electric power information management system |
| CN102694844A (en) * | 2012-03-12 | 2012-09-26 | 李宗诚 | Internet EMK/ICT technology design basis |
| CN103259335A (en) * | 2013-04-11 | 2013-08-21 | 国家电网公司 | Intelligent demand response and demand side optimizing operation system |
| 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 |
| CN107910871A (en) * | 2017-11-30 | 2018-04-13 | 国网天津市电力公司 | A kind of energy internet is provided multiple forms of energy to complement each other control method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109064062A (en) | 2018-12-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109064062B (en) | User-side comprehensive energy system operation risk assessment method considering multi-energy coupling interaction | |
| Li et al. | Two-stage optimal operation of integrated energy system considering multiple uncertainties and integrated demand response | |
| Zhang et al. | Day-ahead scheduling of multi-carrier energy systems with multi-type energy storages and wind power | |
| CN108229025B (en) | Economic optimization scheduling method for cooling, heating and power combined supply type multi-microgrid active power distribution system | |
| Hao et al. | Aggregate flexibility of thermostatically controlled loads | |
| Yang et al. | Optimal dispatching of an energy system with integrated compressed air energy storage and demand response | |
| WO2022166114A1 (en) | Electro-hydrogen energy system scheduling method thst considers flexible hydrogen requirements | |
| CN109345012B (en) | Park energy Internet operation optimization method based on comprehensive evaluation indexes | |
| Huo et al. | Chance-constrained optimization for integrated local energy systems operation considering correlated wind generation | |
| CN114707289B (en) | Multi-objective optimization method of electrothermal coupling comprehensive energy system based on opportunity constraint | |
| CN112700094B (en) | Multi-time scale optimization scheduling method for comprehensive energy system based on MPC and LODDLC | |
| CN114358431A (en) | Multi-energy system optimal scheduling method and device considering supply and demand bidirectional demand response | |
| CN111738498B (en) | Robust planning method and system for comprehensive energy system | |
| CN102521673B (en) | A kind of method for optimizing power-failure plan based on genetic algorithm | |
| CN110620397A (en) | Peak regulation balance evaluation method for high-proportion renewable energy power system | |
| Mahmoudi et al. | Customer‐driven demand response model for facilitating roof‐top PV and wind power integration | |
| CN111274674A (en) | Distributed multi-energy scheduling method based on organic Rankine cycle system | |
| Wang et al. | Peer-to-peer electricity transaction decisions of the user-side smart energy system based on the SARSA reinforcement learning | |
| CN112668188A (en) | Distributed robust collaborative optimization scheduling method for multi-park comprehensive energy system | |
| CN113098036A (en) | Comprehensive energy system operation method based on hydrogen fuel cell | |
| CN110991764B (en) | Day-ahead rolling optimization method for comprehensive energy system | |
| Fang et al. | Energy management strategy based on energy storage equalization technology and transferable load | |
| CN113469430B (en) | Multi-energy complementary capacity configuration method for comprehensive energy park | |
| Mu et al. | A scenario-based optimal dispatch for joint operation of wind farms and combined heat and power plants considering energy flexibilities in heating networks | |
| CN113158547B (en) | Regional comprehensive energy system optimal configuration method considering economy and reliability |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |