EP3251077A1 - Procédé d'amélioration de la répartition des charges d'un réseau basse tension - Google Patents

Procédé d'amélioration de la répartition des charges d'un réseau basse tension

Info

Publication number
EP3251077A1
EP3251077A1 EP16701925.6A EP16701925A EP3251077A1 EP 3251077 A1 EP3251077 A1 EP 3251077A1 EP 16701925 A EP16701925 A EP 16701925A EP 3251077 A1 EP3251077 A1 EP 3251077A1
Authority
EP
European Patent Office
Prior art keywords
network
low
components
voltage
central computer
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.)
Ceased
Application number
EP16701925.6A
Other languages
German (de)
English (en)
Inventor
Tobias GAWRON-DEUTSCH
Alfred Einfalt
Jan Wieghardt
Yaroslav BARSUKOV
Jürgen Götz
Nicolas GÜMBEL
Ralf MOSSHAMMER
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.)
Siemens AG
Original Assignee
Siemens AG
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 Siemens AG filed Critical Siemens AG
Publication of EP3251077A1 publication Critical patent/EP3251077A1/fr
Ceased legal-status Critical Current

Links

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
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • 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

Definitions

  • the invention relates to a method for improving the utilization of a low voltage network using a communication network between components of the
  • Outer conductor and the neutral conductor or 400 V (between the three outer conductors), but in any case only up to 1000 V.
  • Local grid transformers may vary depending on the destination grid planning of the respective distribution system operator, but are typically 250 or 400kVA for rural areas and 630 or 800kVA for inner city areas.
  • low-voltage network in the sense of this invention designates a part of the distribution network, ie one
  • Section that is powered by a particular local power transformer with electrical energy is powered by a particular local power transformer with electrical energy.
  • Components of the low-voltage network can be:
  • Generators eg photovoltaic systems, Small wind turbines
  • storage eg batteries, heat pumps
  • flexible consumers eg electric storage heaters, buildings with and without building automation system and
  • actuators converters or drive elements, convert electrical energy into mechanical motion or other physical quantities (eg pressure or temperature)) and network resources (transformers, lines,
  • Fuses measuring devices such as smart meters, .
  • the classical grid operation in the electricity supply is due to the increasing penetration of decentralized, usually renewable, power generation plants (DEA, usually in the power range from 3 to 100 kW) before large
  • the smart grid or intelligent power network includes the communicative networking and control of power generators, storage, electrical consumers and network resources in energy transmission and power
  • smart buildings also referred to as smart homes or smart buildings
  • components such as fluctuating generators (e.g.
  • Building automation encompasses the entirety of monitoring, control, and control systems
  • Characteristic feature is the continuous networking by means of a bus system.
  • Building automation systems must therefore optimize their own requirements for electrical and thermal energy for the individual components of the building, create local (building-related) forecasts and have flexible tariff specifications that have market- or network-specific proportions.
  • Combined heat and power plant generates electrical energy and heat for a district heating network and / or it is in addition to Water treatment used.
  • any intervention of the distribution network operator of the electrical network is blind (with regard to, for example, the combined heat and power plant), so that unwanted cascades can arise. So can about the
  • Cogeneration plant prescribe a reduction in the supply of electrical energy, with the result that less district heating is supplied, but by the operator of the
  • a low voltage network has various active components that are used in the
  • VPP Virtual Power Plants
  • the inverter is equipped with a P / Q feed-in limitation which prevents too much power from being fed into the low-voltage grid in the event of a local limit violation.
  • P / Q feed-in limitation which prevents too much power from being fed into the low-voltage grid in the event of a local limit violation.
  • Component is sufficient, nor that not too strong
  • the individual components in particular the generators, can only be in the green state, where there are no restrictions from the network view and all market mechanisms can be used without restriction, or in the state red, where the network constraints demand hard requirements for the supply and thus local market mechanisms for a limited time are restricted, work.
  • the yellow state within the network boundary conditions, a market-based
  • Low-voltage grid or the energy supplied to the individual market participants (for example VPP, ONS) with regard to the currently valid energy price.
  • the aim of the present invention is to provide the technical
  • the fulfillment of the technical task includes compliance with the network constraints and the guarantee of the permanent power supply of the
  • the economic aspect implies compliance with the utilization of the low-voltage grid (for example by the VPP, producers or consumers) so that the individual components are as economical and efficient as possible
  • controllable components are based on the
  • Network state forecast change their load profile.
  • controllable components are so-called
  • VPP Virtual Power Plants
  • photovoltaic systems and their storage, small wind turbines, smart meters or smart buildings.
  • a kind of pre-stage network protection can be achieved, which essentially consists of a central computer
  • (computerized system) e.g. is housed in a distribution station of the low voltage network, with a
  • Communication unit exists. Firstly, it supports the distribution system operator in predicting the network situation in the future by collecting production and consumption forecasts of the controllable producers and taxable consumers connected to the low-voltage grid. Secondly, it may prevent the taxable producers and consumers connected to the low - voltage grid from future intervention of the
  • Distribution system operator warn. Producers and consumers can then assess the consequences of such an intervention and take timely countermeasures. If e.g. of the
  • Distribution system operator wants to throttle the supply of energy via the transformer of the low-voltage network in the superimposed medium-voltage network at a given time, can from this point on more energy from producers in the low-voltage network or from storage in the Low-voltage network can be fed, and / or the
  • the network state forecast may be e.g. as a result, the states of the low voltage network provide similar to the network traffic lights: the network may be in the green state, where there are no restrictions from the network view, or in the state red, where in some or all network nodes there are injuries
  • Network state forecast a red state in the future.
  • a network state forecast consists e.g. be used from a set of network nodes for each existing time series or created by substitution value generation based on available data time series. The most important time series are the load curve (feed-in power and / or consumption), the expected voltage and the traffic light levels. If required, other time series such as e.g. Current and thermal load of the cables / cables are included in the grid condition prognosis.
  • the central computer notifies all controllable
  • the mesh condition forecast can be of varying complexity
  • non-controllable components from the central computer for further, non-controllable components a - especially generic - load profile created and this in the
  • Net State Forecast is recorded. This can also "non-intelligent" components, such as households or buildings without smart meter, to be considered in the grid condition forecast.
  • Components is created, supplemented by forecasts based on weather data and / or historical data. This makes it possible to refine the grid condition forecast.
  • Network topology is taken into account, this has the advantage that much more selective individual controllable components can be selected for the solution of the network bottleneck.
  • the power loss in the network can be considered.
  • the central computer is for a low voltage network
  • the virtualization computer is located at a network-topologically useful node, such as in a substation.
  • the control units are located for all connected
  • controllable components e.g., the building management system or the building management system
  • Network state prognosis are calculated, with the time intervals best correspond to the times in which experience has shown that it must respond to changes in the low-voltage network.
  • the time intervals are preferably in the range of 15 minutes to one hour. A higher clocking brings the need for more powerful computers in the
  • Time interval of less than 15 minutes only a comparatively little improvement in the overall system. The longer it takes to re-evaluate the situation, the more drifting forecasts and actual conditions drift apart and decisions based on outdated information are made.
  • the invention also relates to a system for carrying out the method according to the invention, comprising
  • the invention realizes a first
  • each feed-in node may have its profit
  • the network protection according to the invention is regional, since it is a small part of a low-voltage distribution network
  • the invention is a pre-stage network protection, which the
  • Components of the low-voltage network From the central computer can with the network state forecast also the
  • Network edge conditions e.g., the nominal load capacity
  • Components are sent so that they can be taken into account by the components, so are not exceeded.
  • FIG. 1 is a schematic representation of two conventional
  • Fig. 2 is a schematic representation of two
  • Fig. 1 shows an example of the scheme of two similar low-voltage networks 1, 2, which are supplied via an energy distribution network 3 and each a local power transformer 4 with electrical energy.
  • Each low-voltage grid 1, 2 has non-controllable components, such as buildings 5 or households, and controllable components, such as smart buildings 6 (intelligent buildings - both residential and
  • Low-voltage network 1, 2 are connected via electrical lines 10 with each other and with the local power transformer 4.
  • the electrical lines 10 themselves can also for
  • Smart Buildings 6 have an energy management system that generally coordinates the procurement, conversion, distribution and use of energy, in this case electrical energy. Coordination is foresighted, organized, systematic and taking into account environmental and economic objectives. It includes organizational and information structures including the necessary technical measures such as Software.
  • Energy management system therefore includes according to the invention at least one computer or a PLC with energy management software as well as data connections (eg data lines) to information sources, measuring devices and the to be controlled
  • FIG. 1 two virtual power plants VPP1, VPP2 are provided, each with
  • Components of various low-voltage networks 1, 2 are connected, namely in this example with decentralized power generators (photovoltaic 7, wind turbines 8,
  • a virtual power plant is an interconnection of decentralized - generally relatively small - power generation units, such as photovoltaic systems, small hydropower plants and biogas plants, but also small wind turbines and mini or micro combined heat and power plants to a network that can provide demand-driven electrical power.
  • the power plant is called virtual because it has more than one location.
  • VPP1, VPP2 are interconnected via their own data links 11.
  • the controllable local power transformer 4 is first adjusted to the lowest level. In the example, this is not enough and the distribution system operator must prescribe a reduction of the feed-in power to the systems that can receive the signals (Smart Buildings 6 in this example).
  • the central computer 12 is connected by a communication network 13 to the individual components of the low-voltage network 1, 2
  • the communication network 13 may be in a
  • Low-voltage network 1, 2 exist, so that a power line communication (PLC) is realized.
  • PLC power line communication
  • separate data connections can be made or other existing data connections (for example from smart meters) can be used.
  • the smart buildings 6 and generating plants 7, 8, 21 report their timetables, which they have negotiated with the respective VPP operators of the virtual power plants VPP1, VPP2, to the central computer 12 in the respective local network station. For example, at 11am, the buildings and power plants send the
  • Infeed timetable for the next day (0-24h). This consists, for example, of a feed-in power in watts for each 15-minute time window (ie 96 values). In the case of buildings, the value can also be negative - the building then draws energy from the grid. To get a more complete picture will not be pre-announced for all
  • Each newly created network state forecast is transmitted to the buildings 6 and generating plants 7, 8, 21 in a timely manner.
  • the inventive method can as follows in the
  • Low-voltage network are here in power generator 7, 8, 21, electric vehicles or their charging stations 9, energy storage Divided 19 and 22 and flexible consumers 14. They are all controlled or controlled via control and regulation units 15, which are controlled by a higher-level control 16 (an object manager, eg an energy management system of a
  • information about energy price and / or amount of energy can be exchanged and the controller 16 or the control and regulation units 15 send correspondingly different control commands to the controllable components.
  • information about energy price and / or electrical power can be exchanged and the controller 16 or the control and regulation units 15 send correspondingly different control commands to the controllable components.
  • Power or load (continuous arrow) sends control commands that also run on the central computer 12 according to the invention and from this now according to the
  • Control 16 and the control and regulation units 15 are forwarded. Only control signals of
  • Safety device 18 with high priority are without interference by the central computer 12 directly to the controller 16 and the control and
  • VPP1 first virtual power plant (Virtual Power Plant)
  • VPP2 Second Virtual power plant (Virtual Power Plant)

Landscapes

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

Abstract

L'invention concerne un procédé d'amélioration de la répartition des charges d'un réseau basse tension (1, 2) au moyen d'un réseau de communication (13) entre des éléments du réseau basse tension, - des éléments (4, 6-11) contrôlables créent de manière répétée des prévisions de charges et les délivrent à un ordinateur central (12), - à partir desdites prédictions de charge, l'ordinateur central (12) crée une prédiction d'état de réseau et l'envoie aux éléments (4, 6-11) contrôlables, et - les éléments (4, 6-11) contrôlables modifient leur profil de charge sur la base de la prédiction d'état de réseau.
EP16701925.6A 2015-01-29 2016-01-26 Procédé d'amélioration de la répartition des charges d'un réseau basse tension Ceased EP3251077A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
AT500702015 2015-01-29
PCT/EP2016/051526 WO2016120248A1 (fr) 2015-01-29 2016-01-26 Procédé d'amélioration de la répartition des charges d'un réseau basse tension

Publications (1)

Publication Number Publication Date
EP3251077A1 true EP3251077A1 (fr) 2017-12-06

Family

ID=55262788

Family Applications (1)

Application Number Title Priority Date Filing Date
EP16701925.6A Ceased EP3251077A1 (fr) 2015-01-29 2016-01-26 Procédé d'amélioration de la répartition des charges d'un réseau basse tension

Country Status (2)

Country Link
EP (1) EP3251077A1 (fr)
WO (1) WO2016120248A1 (fr)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102018208883A1 (de) * 2018-06-06 2019-12-12 Audi Ag Verfahren zum Ermitteln eines Auslastungszustands zumindest eines Teils eines Stromnetzes, insbesondere zur Steuerung eines steuerbaren Verbrauchers, und Kommunikationssystem
CN109102110B (zh) * 2018-07-23 2022-03-22 云南电网有限责任公司临沧供电局 一种径流式小水电短期出力预测方法和装置
CN110154816A (zh) * 2019-05-16 2019-08-23 盐城品迅智能科技服务有限公司 一种用于自动引导小车的充电管理系统及方法

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2695269B2 (fr) * 2011-04-08 2017-10-25 SMA Solar Technology AG Gestion optimisée de charge
DE102013222277A1 (de) * 2013-03-15 2014-09-18 Cbb Software Gmbh Steuerung von dezentralen Energieerzeugern und/oder Verbrauchern in einem elektrischen Verbundnetz

Also Published As

Publication number Publication date
WO2016120248A1 (fr) 2016-08-04

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