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.

Status of this Memo

   This Internet-Draft is submitted to IETF in full conformance with the
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Copyright and License Notice

   Copyright (c) 2017 IETF Trust and the persons identified as the
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   This document is subject to BCP 78 and the IETF Trust's Legal
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   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document. Please review these documents
 


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   carefully, as they describe your rights and restrictions with respect
   to this document. Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.


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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