CN111027786B - Micro-grid operation optimization and energy efficiency management system - Google Patents
Micro-grid operation optimization and energy efficiency management system Download PDFInfo
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- CN111027786B CN111027786B CN201911399281.1A CN201911399281A CN111027786B CN 111027786 B CN111027786 B CN 111027786B CN 201911399281 A CN201911399281 A CN 201911399281A CN 111027786 B CN111027786 B CN 111027786B
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- 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
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention provides a micro-grid operation optimization and energy efficiency management system, which comprises: the prediction algorithm is used for establishing a distributed prediction architecture and algorithm combining offline parameter optimization and online power prediction, and decomposing a complex optimization process and online rapid prediction; optimizing and modeling, namely establishing a user side micro-grid optimizing operation model on the basis of a prediction algorithm, maximizing clean energy utilization, minimizing daily electricity cost in a conventional mode, and maximizing the power supply duration of a key load in an emergency mode; user energy efficiency management, according to user comfort level setting, deciding the working state of temperature control type controllable load, calculating energy consumption of temperature control equipment, and carrying out optimization operation modeling and scheduling strategy; and a scheduling strategy, modeling according to the optimized operation, adopting a scheduling driver intelligence of a rolling time domain for upper-layer energy management, and adopting an event-triggered scheduling driving mechanism for lower-layer energy management. The invention realizes the maximum management of energy sources and reduces the running cost.
Description
Technical Field
The invention belongs to the technical field of micro-grids, and particularly relates to a micro-grid operation optimization and energy efficiency management system.
Background
The micro-grid energy management technology is a key technology for maximizing the operation benefit of the micro-grid on the basis of stable and reliable operation of the micro-grid by taking the optimized operation of the micro-grid as a target and formulating a reasonable energy management control strategy based on the power supply, load and environmental resource data of the micro-grid.
The existing micro-grid operation has high operation cost and poor adaptability, can not realize the maximum utilization of energy sources in energy efficiency management, and can not realize the minimization of daily electricity cost for users.
Disclosure of Invention
The invention aims to provide a micro-grid operation optimization and energy efficiency management system, which realizes energy maximization management and reduces operation cost.
The invention provides the following technical scheme:
a microgrid operation optimization and energy efficiency management system comprising:
the prediction algorithm is used for establishing a distributed prediction architecture and algorithm combining offline parameter optimization and online power prediction, decomposing a complex optimization process with online rapid prediction, calculating resource constraint, updating prediction model parameters regularly, and extracting brand new characteristic indexes;
optimizing and modeling, namely establishing a user side micro-grid optimizing operation model on the basis of a prediction algorithm, maximizing clean energy utilization, minimizing daily electricity cost in a conventional mode, and maximizing the power supply duration of a key load in an emergency mode;
user energy efficiency management, according to user comfort level setting, deciding the working state of temperature control type controllable load, calculating energy consumption of temperature control equipment, and carrying out optimization operation modeling and scheduling strategy;
and a scheduling strategy, modeling according to the optimized operation, adopting a scheduling driver intelligence of a rolling time domain for upper-layer energy management, and adopting an event-triggered scheduling driving mechanism for lower-layer energy management.
Preferably, the prediction model comprises a micro-grid load prediction model and a distributed photovoltaic power prediction model, both the optimizing process and the on-line rapid prediction decomposition are conducted, regional free weather forecast is introduced, and the prediction result is calculated.
Preferably, the optimization modeling comprises a single-layer architecture and a user side micro-grid optimization operation model of a double-layer architecture, under the single-layer architecture, clean energy is utilized to the maximum extent in a conventional mode, daily electricity cost is minimized, and in an emergency mode, the power supply duration of a key load is maximized; under the double-layer architecture, the upper layer operators maximize clean energy utilization, maximize daily operation benefits, and minimize daily electricity cost for lower layer users.
Preferably, the user energy efficiency management user sets a comfort level range, and according to outdoor or indoor temperature, the working state of the equipment is determined by considering the light power and the electricity price, and the energy consumption of the temperature control equipment is calculated, so that the energy efficiency management is performed.
Preferably, the rolling time domain mechanism is multi-time scale scheduling, and the timing root scheduling scheme is used for real-time processing of prediction errors; the event triggering mechanism adopts implementation scheduling, dynamically updates a scheduling scheme according to the influence degree of random events, reduces the CPU occupancy rate and reduces the calculated amount.
The beneficial effects of the invention are as follows: the system adopts a prediction framework to realize the organic balance of calculation resource constraint and prediction precision, ensures the adaptability to the electricity habit change and the photovoltaic random dust coverage, and reduces the system operation cost; the system realizes the maximum utilization of clean energy through optimizing modeling, and simultaneously minimizes daily electricity cost; the energy efficiency management and scheduling strategy comprehensively considering the controllable load has real-time performance, and the stability and the economy of the operation of the micro-grid engineering are improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic diagram of a microgrid load prediction model of the present invention;
FIG. 3 is a schematic diagram of a distributed photovoltaic power prediction model of the present invention;
FIG. 4 is a single-layer user-side microgrid optimization run model of the present invention;
FIG. 5 is a schematic diagram of an energy efficiency management process according to the present invention.
Detailed Description
As shown in fig. 1, a micro-grid operation optimization and energy efficiency management system includes:
the prediction algorithm is used for establishing a distributed prediction architecture and algorithm combining offline parameter optimization and online power prediction, decomposing a complex optimization process with online rapid prediction, calculating resource constraint, updating prediction model parameters regularly, and extracting brand new characteristic indexes;
optimizing and modeling, namely establishing a user side micro-grid optimizing operation model on the basis of a prediction algorithm, maximizing clean energy utilization, minimizing daily electricity cost in a conventional mode, and maximizing the power supply duration of a key load in an emergency mode;
user energy efficiency management, according to user comfort level setting, deciding the working state of temperature control type controllable load, calculating energy consumption of temperature control equipment, and carrying out optimization operation modeling and scheduling strategy;
and a scheduling strategy, modeling according to the optimized operation, adopting a scheduling driver intelligence of a rolling time domain for upper-layer energy management, and adopting an event-triggered scheduling driving mechanism for lower-layer energy management.
As shown in fig. 2 and 3, the prediction model comprises a micro-grid load prediction model and a distributed photovoltaic power prediction model, and both the optimizing process and the online rapid prediction are decomposed, so that the organic balance of calculation resource constraint and prediction precision is realized, the prediction model parameters are updated regularly, and the adaptability to the electricity habit change and the photovoltaic random dust coverage is ensured; the brand new characteristic indexes are extracted, so that the random fluctuation problem can be solved; and regional free weather forecast is introduced, so that the running cost of the system is reduced.
As shown in fig. 4, the optimization modeling includes a single-layer architecture and a double-layer architecture of a user-side micro-grid optimization operation model, under the single-layer architecture, in a conventional mode (grid connection), clean energy is utilized to the maximum extent, daily electricity cost is minimized, in an emergency mode (isolated grid), the power supply duration of a key load is maximized, the micro-grid with a single-layer structure can be used as a decision object of distributed power supply, energy storage and load, and most of user types are buildings, families and factories; under the double-layer architecture, the upper layer operators maximize clean energy utilization, maximize daily operation benefit, lower layer users minimize daily electricity cost, the micro-grid with the double-layer structure and an upper layer decision object: shared distributed power supply, controllable coincidence, energy storage and the like, and the lower layer decision object is that the user has own resources, and the user type is a district or a park.
As shown in fig. 5, the user energy efficiency management user sets a comfort range, determines an equipment working state according to outdoor or indoor temperature in consideration of light power and electricity price, calculates energy consumption of the temperature control equipment, and thus performs energy efficiency management. Referring to industry rules of energy-saving services, energy efficiency changes are generally measured according to unit output value comprehensive energy consumption change amounts of enterprises, and resident users do not have production purposes, so that energy efficiency changes of resident users are defined as comprehensive energy efficiency change amounts on the premise of not affecting life quality.
In the scheduling strategy, a rolling time domain mechanism is multi-time scale scheduling, and a timing root scheduling scheme is used for real-time processing of prediction errors; the event triggering mechanism adopts implementation scheduling, dynamically updates a scheduling scheme according to the influence degree of random events, reduces the CPU occupancy rate and reduces the calculated amount.
The system provides a general micro-grid energy management control strategy based on a prediction algorithm and optimization modeling, realizes the energy management control strategy under different energy management optimization targets, provides a mature micro-grid energy management strategy for planning and designing micro-grid projects, and is beneficial to improving the stability and economy of micro-grid engineering operation.
The foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. A microgrid operation optimization and energy efficiency management system, comprising:
the prediction algorithm is used for establishing a distributed prediction architecture and algorithm combining offline parameter optimization and online power prediction, decomposing a complex optimization process with online rapid prediction, calculating resource constraint, updating prediction model parameters regularly, and extracting brand new characteristic indexes;
optimizing and modeling, namely establishing a user side micro-grid optimizing operation model on the basis of a prediction algorithm, maximizing clean energy utilization, minimizing daily electricity cost in a conventional mode, and maximizing the power supply duration of a key load in an emergency mode; the optimization modeling comprises a single-layer architecture and a user side micro-grid optimization operation model of a double-layer architecture, under the single-layer architecture, clean energy is utilized to the maximum extent under a conventional mode, daily electricity cost is minimized, and in an emergency mode, the power supply duration of a key load is maximized; under the double-layer architecture, the upper layer operators maximize clean energy utilization, maximize daily operation benefits, and minimize daily electricity cost for lower layer users;
user energy efficiency management, according to user comfort level setting, deciding the working state of temperature control type controllable load, calculating energy consumption of temperature control equipment, and carrying out optimization operation modeling and scheduling strategy;
and a scheduling strategy, modeling according to the optimized operation, adopting a scheduling driver intelligence of a rolling time domain for upper-layer energy management, and adopting an event-triggered scheduling driving mechanism for lower-layer energy management.
2. The micro-grid operation optimization and energy efficiency management system according to claim 1, wherein the prediction model comprises a micro-grid load prediction model and a distributed photovoltaic power prediction model, the optimizing process and the online rapid prediction are decomposed, and regional free weather forecast is introduced to calculate a prediction result.
3. The micro grid operation optimizing and energy efficiency managing system according to claim 1, wherein the user energy efficiency managing user sets a comfort range, determines the equipment working state according to the outdoor or indoor temperature in consideration of the light power and the electricity price, and calculates the energy consumption of the temperature control equipment, thereby performing energy efficiency management.
4. The micro-grid operation optimization and energy efficiency management system according to claim 1, wherein the rolling time domain mechanism is a multi-time scale scheduling and timing root scheduling scheme for real-time processing of prediction errors; the event triggering mechanism adopts implementation scheduling, dynamically updates a scheduling scheme according to the influence degree of random events, reduces the CPU occupancy rate and reduces the calculated amount.
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| CN112146228B (en) * | 2020-09-27 | 2021-11-23 | 珠海格力电器股份有限公司 | Control method and device of air conditioner and storage medium |
| CN113379160A (en) * | 2021-07-06 | 2021-09-10 | 国网江苏省电力有限公司营销服务中心 | Building side comprehensive energy system optimal scheduling method based on building heat energy flow |
| CN113487242A (en) * | 2021-08-19 | 2021-10-08 | 浙江华云清洁能源有限公司 | Energy efficiency management method, system, equipment and storage medium |
| CN116307295B (en) * | 2023-05-22 | 2023-08-04 | 南京宝能科技有限公司 | Intelligent energy digital management system and method applied to cloud platform |
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