EP3759785A1 - Procédé de régulation en temps réel d'un système d'alimentation et de distribution d'énergie - Google Patents

Procédé de régulation en temps réel d'un système d'alimentation et de distribution d'énergie

Info

Publication number
EP3759785A1
EP3759785A1 EP19711341.8A EP19711341A EP3759785A1 EP 3759785 A1 EP3759785 A1 EP 3759785A1 EP 19711341 A EP19711341 A EP 19711341A EP 3759785 A1 EP3759785 A1 EP 3759785A1
Authority
EP
European Patent Office
Prior art keywords
energy
control system
operating
control
simulation
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.)
Withdrawn
Application number
EP19711341.8A
Other languages
German (de)
English (en)
Inventor
Sebastian UTZ
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Innofas GmbH
Original Assignee
Innofas GmbH
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Innofas GmbH filed Critical Innofas GmbH
Publication of EP3759785A1 publication Critical patent/EP3759785A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in networks by storage of energy
    • H02J3/32—Arrangements for balancing of the load in networks by storage of energy using batteries or super capacitors with converting means
    • H02J3/322—Arrangements for balancing of the load in networks by storage of energy using batteries or super capacitors with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38—Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38—Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
    • H02J3/46—Controlling the sharing of generated power between the generators, sources or networks
    • H02J3/466—Scheduling or selectively controlling the operation of the generators or sources, e.g. connecting or disconnecting generators to meet a demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2101/00—Supply or distribution of decentralised, dispersed or local electric power generation
    • H02J2101/20—Dispersed power generation using renewable energy sources
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2103/00—Details of circuit arrangements for mains or AC distribution networks
    • H02J2103/30—Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/20—Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Definitions

  • the invention relates to a method for optimized real-time control of a power supply and distribution system.
  • a 1000 kW power supply and distribution system consisting of z.
  • a PV system As a PV system, a buffer memory, two charging stations for charging and recovery of energy from an energy storage of a vehicle, a network connection for feeding and extracting energy from the public network and a central control considered.
  • a plant planner it is initially completely indefinable how he should interpret the individual components and a corresponding system with regard to system configuration, capacities and dimensioning.
  • unknown factors are added, such as
  • Feed-in tariff electricity costs, power consumption behavior in the day / post-cycle, etc.
  • the system designer has to consider many To make unknowns that are more or less accurately estimated in practice, taking into account certain assumptions.
  • a respective safety reserve is determined on the basis of consumption values and, based on this, the components thus designed are combined to form an overall system. So z.
  • the PV system is planned oversized and, regardless of the configuration of the charging stations, the known variables such as the roof pitch, the location, the orientation and, in particular, the desired output are included in the planning and design of the PV system. Since additional reserves are also calculated, the system is typically not dimensioned optimally. Within the meaning of the present invention, the optimum is understood to mean a state in which, in particular, the cost / benefit ratio is as low as possible, which means that it is possible to remove the respectively required services from the system with a minimum outlay on equipment and costs.
  • the invention is therefore based on the object of providing a method for optimally operating a power supply and distribution system with real-time control.
  • a basic idea of the invention is to provide a two-stage process in order to arrive at an optimal real-time control.
  • a simulation system with means for generating and / or processing simulation data of a simulation target space proposed in which a number of energy-generating, energy-storing and energy-consuming system components are as a plurality of elements, wherein between at least two elements an energy flow takes place in order to represent a simulation target space; Evaluation and / or calculating means for calculating a power factor relating to every two or more elements of the plurality of elements, taking into account their prioritization on the basis of the simulation data; Evaluation means for evaluating the performance data that will be provided or consumed by each element using the factors determined to determine therefrom the system components for which a variable efficiency value results in an optimum.
  • an energy bus can be provided, to which energy consumers and energy producers are connected.
  • conventional bus interfaces such as TCP, CAN or other bus systems may be provided.
  • the energy bus is relevant when the physical model is decoupled and replaced by the real variables.
  • a second and essential aspect of the present invention relates to the design of a regulator. From the simulation model, a controller is designed according to the invention, wherein the input variables of each participant of the bus system are incorporated as a relevant rule size. Input variables such as minimum and maximum current, minimum and maximum voltage, energy content, SOC, temperature, weather data, costs such as
  • Feed-in tariffs and electricity costs and the like are included.
  • a method for optimized real-time operation of a power distribution and supply system consisting of a plurality of energy-generating, energy-storing and energy-consuming system components (SYSi) using suitable means for detecting, processing, storing operating data and simulation data with the following steps: a. Means for selecting energy-producing, energy-storing and energy-consuming system components (SYSi) of the energy distribution and supply system; b. Creation of a simulation model for the operation of the power distribution and supply system with the selected system components nents, wherein the simulation model depicts a multiplicity of operating situations, which differ from one another through a variation of respectively controllable operating parameters of the system components; c. Designing a control system or control conditions based on data obtained from the simulation model and currently acquired operating data or operating parameters, d. Design a regulatory concept for the regulatory system.
  • control concept designed a control loop, so that the currently detected operating data or operating parameters and their influence is compared to an operating variable to be optimized is determined with the data of the simulation model and depending on the size of the deviation, if the power distribution and supply system in at least this Operating variable or a lot of operating variables in an operating optimum is operated and, if necessary, a regulatory adjustment must be made.
  • control system constantly adjusts the operating optimum after each reactivation itself, depending on the operating parameters of the current NEN and connected system components. This ensures that the system in each case when logging in and out of a participant speak a system component such as an electric vehicle, independently depending on the new situation regulates. According to the invention, it can also be provided that a user optimum is regulated.
  • a user optimum can be achieved, for example, by prioritizing the speed the charging process.
  • a user who can access the system (for example a user of an electric vehicle) can predetermine user-specific boundary conditions in the system. Thus, for example, it can be specified as a boundary condition that a maximum energy charge flow reaches the vehicle in a given time, since it is intended to attempt to charge the on-board battery for example in one hour.
  • an optimized price for the removal of electrical energy can be preselected, so that the charging process starts when the system offers the user a certain price of electricity (for example, night electricity). It would also be conceivable that electrical energy is fed from the vehicle battery, and only a residual charge capacity is to be kept in order to drive a be certain driving distance can.
  • control system recognizes the new subscriber and can then adjust a new optimized operating point depending on the simulation data and the actual operating data by means of the control concept.
  • the method according to the invention can be applied equally to industrial plants as well as to HEMS systems and to combinations thereof.
  • a fuzzy control system for this purpose is a static nonlinear control system which uses sharp input variables of a complex process forms fuzzified control variables and sharp defuzzified value signals, which are defined in an unclear manner according to the rules of a rule base.
  • a fuzzification of a sharp physical input variable is the quantification by fuzzy definitions with linguistic terms or other parameters.
  • graphical trapezoidal or triangular fuzzy sets are used to determine the degrees of membership from the discrete input signals within the basic quantities (variables). In the present case, however, this is done differently than in classical fuzzification on the basis of the simulation model and the optimization carried out there.
  • neural networks are used in addition to or in addition to the FUZZY logic.
  • control system can test the power distribution and supply system in a simulation using the control concept.
  • control system for controlling the operating optimum in particular detects the respective current energy consumption and / or the respective current energy entry in the power distribution and supply system and taken into account.
  • the dynamic behavior of the real system is taken into account when participants change their operating behavior, at the sys- log on or off, tariff changes occur at a specific time, or other system changes occur without manual intervention.
  • the communication of the system components and means in the system are via interfaces CAM, TCP, serial interface or other conventional communication interfaces. This ensures that communication can take place with conventional communication systems or the method according to the invention can be integrated into existing systems.
  • a computer-readable program code preferably a C-code
  • one aspect of the present invention is to generate from the fuzzification to determine the optimum operating a C-code in order to use these executable systems that process C-code.
  • the generated computer-readable program code, in particular C code is integrated on a microcontroller, also Labview or Canoe. As a result, it is also possible that the integrated on a microcontroller C code in applications of various devices can be used.
  • control system determines the optimized operating conditions under consideration of system-specific boundary conditions, these being stored as setpoint values in a setpoint memory or operating memory of the control system.
  • control system for using a method as described above.
  • control system comprises a controller and an input unit for inputting operating parameters and / or variables used in the control.
  • control system has a computing unit which is designed to perform a fuzzification on the basis of the values, operating parameters and / or variables of the system components.
  • controller has interfaces in order to process input data of the simulation layer.
  • the efficiency value is provided as a function of n variables, an optimum of the efficiency value representing a local extreme position of this function, preferably determined by the partial derivatives of the function and resulting therefrom resulting maximum value conditions or
  • the evaluation unit uses simulation modules for the system components, which at least have their performance data can be parameterized.
  • the simulation modules are designed so that they simulate the system component in the overall system according to a simulation model.
  • FIG. 1 shows an exemplary representation of a power distribution and supply system
  • Fig. 2 is a simplified schematic representation for explaining the
  • FIG. 1 shows an exemplary representation of a power distribution and supply system 10.
  • the power distribution and supply system 10 consists of a large number of energy-generating, energy-storing and energy-consuming system components SYSi.
  • the arrows on the connecting lines show the possible energy flow.
  • the controller can thereby implement the energy flow according to a system-specific prioritization.
  • the battery B1 as exclusively energy-storing system components SYSi allows z. B. a bi-directional energy flow when loading in Direction of the battery and when discharging from the battery out to a consumer or in the network to generate a feed-in remuneration at z.
  • variable electricity tariff as a variable VAR the public network.
  • two charging stations LK with a charging capacity of 350 kW each with coupled electric vehicles F are shown, in each of which a battery B2 or B3 is installed.
  • the battery B1 can be stored or power can be fed into the public grid via the grid connection N, if it makes sense in the macroeconomic perspective.
  • z. B. also electrical energy from the battery B2 of a vehicle F in the battery B3 of the other vehicle F are transmitted directly via a charging station management.
  • FIG. 2 schematically illustrates the idea of such a control system.
  • an energy bus system 20 is shown schematically.
  • the energy bus system 20 is exemplary with a
  • a Fuzzy control based on the individual parameters is performed by means of a FUZZY control.
  • a system simulation is carried out. Different scenarios are simulated and optimized for the system components. The result is used to design the controller 30 (lower part of the figure of Figure 2).
  • the optimal calculation of the real system can be carried out on the basis of the magnitude of the deviation.
  • conventional control means and control means are used to adapt the system or the system components closed thereto according to their performance by the controller 30.
  • the invention is not limited in its execution to the above-mentioned preferred embodiments. Rather, a number of variants is conceivable, which makes use of the illustrated solution even with fundamentally different types of use.

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  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Economics (AREA)
  • Power Engineering (AREA)
  • Human Resources & Organizations (AREA)
  • Health & Medical Sciences (AREA)
  • Strategic Management (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Marketing (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Water Supply & Treatment (AREA)
  • Public Health (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

L'invention concerne un procédé permettant d'optimaliser un fonctionnement en temps réel d'un système d'alimentation et de distribution d'énergie (10), constitué d'une pluralité de composants (SYSi) produisant, stockant et consommant de l'énergie, lequel procédé fait appel à des moyens appropriés pour l'acquisition, le traitement et l'enregistrement de données de fonctionnement et de données de simulation.
EP19711341.8A 2018-05-03 2019-03-14 Procédé de régulation en temps réel d'un système d'alimentation et de distribution d'énergie Withdrawn EP3759785A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102018110628.9A DE102018110628A1 (de) 2018-05-03 2018-05-03 Verfahren zur Echtzeitregelung eines Energieversorgungs- und verteilersystems
PCT/EP2019/056475 WO2019211034A1 (fr) 2018-05-03 2019-03-14 Procédé de régulation en temps réel d'un système d'alimentation et de distribution d'énergie

Publications (1)

Publication Number Publication Date
EP3759785A1 true EP3759785A1 (fr) 2021-01-06

Family

ID=65802101

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19711341.8A Withdrawn EP3759785A1 (fr) 2018-05-03 2019-03-14 Procédé de régulation en temps réel d'un système d'alimentation et de distribution d'énergie

Country Status (3)

Country Link
EP (1) EP3759785A1 (fr)
DE (1) DE102018110628A1 (fr)
WO (1) WO2019211034A1 (fr)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111489037B (zh) * 2020-04-14 2023-04-18 青海绿能数据有限公司 一种基于需求预测的新能源风机备件储备策略优化方法
CN111915028B (zh) * 2020-05-22 2024-12-10 中国电器科学研究院股份有限公司 一种直流充电桩的环境适应性分析方法
CN118281917B (zh) * 2024-03-28 2025-02-11 南京工程学院 计及驱动因素的配电网源-储协同规划方法、系统、设备和介质

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US20120029897A1 (en) * 2010-07-29 2012-02-02 Spirae, Inc. Dynamic distributed power grid control system

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US8527252B2 (en) * 2006-07-28 2013-09-03 Emerson Process Management Power & Water Solutions, Inc. Real-time synchronized control and simulation within a process plant
US9690312B2 (en) * 2012-05-04 2017-06-27 Viridity Energy, Inc. Facilitating revenue generation from wholesale electricity markets using an engineering-based energy asset model
EP2858015A1 (fr) * 2013-10-04 2015-04-08 Building Research Establishment Ltd Système et procédé de simulation, commande et surveillance des performances de systèmes d'énergie
EP3089305A1 (fr) * 2015-04-30 2016-11-02 GridSystronic Energy GmbH Dispositif permettant de faire fonctionner un réseau intelligent
US10585468B2 (en) * 2016-08-18 2020-03-10 Virtual Power Systems, Inc. Datacenter power management using dynamic redundancy

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Publication number Priority date Publication date Assignee Title
US20120029897A1 (en) * 2010-07-29 2012-02-02 Spirae, Inc. Dynamic distributed power grid control system

Also Published As

Publication number Publication date
DE102018110628A1 (de) 2019-11-07
WO2019211034A1 (fr) 2019-11-07

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