Internet DRAFT - draft-chen-iot-energy-electricity
draft-chen-iot-energy-electricity
IoT L. Chen
Internet Draft B. Liu
Intended Status: Informational Huawei
Expires: June 26, 2018 December 23, 2017
Overview of Internet of Things
with Energy and Electricity Industries
draft-chen-iot-energy-electricity-00
Abstract
This document introduces general problems of energy and electricity
industries and discusses how these industries could benefit from
Internet of Things (IoT). Use cases are provided and potential
technical gaps and protocol needs in IETF are evaluated.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Acronyms and Terminology . . . . . . . . . . . . . . . . . . . 3
3. Problem Statement . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Peak Shaving and Valley Filling of Electrical Grid . . . . 3
3.2. Connecting Renewable Energy to the Grid . . . . . . . . . . 3
4. IoT Benefits . . . . . . . . . . . . . . . . . . . . . . . . . 4
4.1. Data Acquisition and Analysis . . . . . . . . . . . . . . . 4
4.2. Demand Prediction and Response . . . . . . . . . . . . . . 4
4.3. Energy Routing . . . . . . . . . . . . . . . . . . . . . . 4
5. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
5.1. Smart (Micro-)Grid . . . . . . . . . . . . . . . . . . . . 5
5.2. Distributed Storage . . . . . . . . . . . . . . . . . . . . 5
6. Gap Analysis and Protocol Needs . . . . . . . . . . . . . . . . 5
7. Security Considerations . . . . . . . . . . . . . . . . . . . . 6
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 6
9. References . . . . . . . . . . . . . . . . . . . . . . . . . . 6
9.1. Normative References . . . . . . . . . . . . . . . . . . . 6
9.2. Informative References . . . . . . . . . . . . . . . . . . 6
Author's Addresses . . . . . . . . . . . . . . . . . . . . . . . . 7
1. Introduction
The traditional energy and electricity industries have not changed a
lot in recent years, comparing with the ICT industries. The rise of
Internet of Things (IoT) has bring new chances to the energy and
electricity industries.
A large proportion of energy consumption is in the form of electric
energy. Human generate electric energy from fossil fuels,
hydroenergy, nuclear energy, etc, and consume electric energy for
industry, residential, transport, and other uses. The root cause of
most energy and electricity relevant problems is that electric energy
can not be easily stored on such a big scale.
The development of ICT technologies as well as IoT provides possible
solutions on a totally different aspect: focus on the "thing". A
thing could generate, consume, or store electric energy. A thing
could also have other limited capabilities, e.g., monitoring,
communicating, and computing. Using the limited capabilities of those
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things (constrained nodes) could enable data acquisition and
analysis, (electric power) demand prediction and response, energy
routing, etc. Thus, the energy and electricity industries could get
benefit and the overall energy consumption of human-being could be
reduced.
To make a better cooperation and convergence for IoT with energy and
electricity industries, the idea of edge intelligence (edge
computing) as well as cloud computing are important. There are also
protocol needs in IETF, accompanied with the development of different
kinds of ICT enabling technologies. These protocols are relevant (but
not limited) to connectivity and communication among things that
generate, consume, or store energy, and configuration and management
between the thing and its controller (IoT gateway) or any higher
level servers.
2. Acronyms and Terminology
IoT: Internet of Things
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
3. Problem Statement
As electric energy can not be easily stored on such a big scale, thus
causing problems.
3.1. Peak Shaving and Valley Filling of Electrical Grid
Peak shaving and valley filling is actually a common behavior of the
electrical grid to balance the overall energy generating and
consuming, but it does cause huge loss of the energy and abrasion of
the generating facilities. The peak load of a grid could be twice as
the valley load, which means, for example, a 100MW power station
switches its output from 100MW to 50MW and then back to 100MW within
24 hours, over and over again. The intuition here is similar to
driving a car, accelerating and braking continuously not only
consumes more oil, but also harms the engine.
3.2. Connecting Renewable Energy to the Grid
Wind or solar energy stations are "weather sensitive" so that their
electrical power output are unstable. Connecting renewable energy
stations to the grid could make it more difficult for the grid to do
the peak shaving and valley filling job. For example, the wind is
averagely more stronger during the night than daytime, meanwhile, the
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average load of the grid is higher during daytime than night.
4. IoT Benefits
By implementing IoT nodes (e.g. an IoT specific gateway) to interact
with traditional energy generation facilities and energy consumption
devices, or embedding edge computing capabilities into these
facilities and devices, IoT could benefit the energy and electricity
industries.
4.1. Data Acquisition and Analysis
Data acquisition, including metering, data pre-processing, and
communicating, are core capabilities of edge computing. Data analysis
can be done at the edge or in the cloud. This enables demand
prediction and response, strategy distribution, predictive
maintenance, emergency response, etc.
4.2. Demand Prediction and Response
Data acquired from the consumer side could be used by a data center
(cloud) to predict the behavior of consumers in total. For the
generating side, most of the power output could be controlled, others
such as the maximum output of a wind or solar station could be
roughly predicted based on weather forecast. Therefore, the
generation-consumption balance for the next time period could be
roughly calculated and the grid could be prepared to response
properly.
Generally, the response contains load control and supply control. A
great number of distributed energy consumers could be involved in the
load control issue. An IoT gateway or controller that manages a
specific kind of consumers could automatically apply different
strategies respect to the response needs, e.g., switch down the air-
conditioning system when the load is high, switch up the battery
charging rate when the load is low.
4.3. Energy Routing
As the electrical grid has many similar features comparing to the
Internet, it could be helpful to introduce the idea of routing into
the energy world. Based on real-time supply and demand relationship,
a grid could alter its topology to reach an optimized state.
Distributed storage stations could act as "buffers" to support energy
routing.
5. Use Cases
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5.1. Smart (Micro-)Grid
A smart grid that includes smart meters and appliances and different
kinds of energy resources could condition the electronic power and
control the electricity production and distribution. A smart micro-
grid is a localized group of electricity sources and loads. The
micro-grid can be connected to the traditional centralized electrical
grid (macro-grid), but it can also disconnect from the macro-grid
into island mode, depending on the electricity load-supply balance or
other needs. The micro-grid is good at integrating various sources of
distributed generation, especially renewable energy sources.
5.2. Distributed Storage
The idea of making huge electric-energy-storage-dedicated batteries
does not make sense. Instead, distributed, non-electric-energy-
storage-dedicated batteries could be helpful.
One good example of distributed energy storage is the Electric
Vehicles.
Electric vehicles neither save energy nor reduce carbon emission
directly, as the electric power they use are mostly generated from
fossil fuels. But electric vehicles do help with valley filling of
the grid, for a large amount of the electric vehicles are charged at
night. In that case, electric vehicles act as batteries, charging
when the load is low, via charging points that are 'things' connected
to the Internet.
6. Gap Analysis and Protocol Needs
Internet-related protocols are to be defined, including but not
limited to connectivity and communication among things that generate,
consume, or store energy, and configuration and management between
the thing and its controller or any higher level servers. As there
are more than one scenarios within the energy and electricity
industries, and each scenario may need a set of Internet-related
protocols to support rather than one single protocol, new Internet-
related protocols should be defined properly, concluding generally
demands as well as mapping different use cases. For example, various
wired/wireless protocols should be defined to support communications
needs, however, each use case may utilize one or two of these
protocols depending on the use case features and that would be enough
to match its communication need.
[IIoT-EC] has listed some general gaps of edge computing.
More details are to be determined.
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7. Security Considerations
TBD.
8. IANA Considerations
This document does not require any allocations by the IANA and
therefore does not have any new IANA considerations.
9. References
9.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, DOI
10.17487/RFC2119, March 1997, <http://www.rfc-
editor.org/info/rfc2119>.
9.2. Informative References
[IIoT-EC] L. Geng, et al, "Problem Statement of Edge Computing beyond
Access Network for Industrial IoT", draft-geng-iiot-edge-
computing-problem-statement-00, work in progress.
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Author's Addresses
Lihao Chen
Huawei Technologies
No.156 Beiqing Rd. Haidian District,
Beijing 100095 P.R. China
EMail: lihao.chen@huawei.com
Bing Liu
Huawei Technologies
No.156 Beiqing Rd. Haidian District,
Beijing 100095 P.R. China
EMail:remy.liubing@huawei.com
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