Towards Intelligent and Self-Evolving Network Infrastructures for Energy Management

Towards Intelligent and Self-Evolving Network Infrastructures for Energy Management

Budapest 2010

Matthias Baumgarten – Maurice Mulvenna University of Ulster

Socio-Economics Inspiring Self-Managed Systems and Concepts

SEISMYC – SASO 2010 – Budapest, Hungary

Outline

n  The Current Grid – The Smart Grid n  Goals n  Drivers and Challenges n  The Grid Ecosystem n  Potential for Self-Organization – A Typical Day in

the UK n  Towards Self-Evolving Energy Networks

n  Step 1: Smart Meters n  Step 2: Self-Awareness and Actionable Devices n  Step 3: Networked Intelligence

n  Conclusions


The Current Grid

n  Large power stations n  No embedded intelligence for e.g.

n  Fault detection n  Local or distributed control / device management n  Demand <-> supply management

n  Centralized control that is performed manually using expert knowledge

n  Difficult to fully incorporate small scale power supplies dynamically

n  Unidirectional power- and information flow n  Depends heavily on forecasts for e.g. next hour or

next day


The Smart Grid

Based on the European Technology Platform on SmartGrids it is

“an electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers and those

that do both – in order to efficiently deliver sustainable economic and secure electricity supplies”

•  It employs •  dynamic monitoring, •  intelligent control, •  secure and fast communication and •  self* -technologies

•  in order to •  better facilitate the connection and operation of generators (of all sizes) •  actively incorporates users preferences, behaviors and objectives •  provide better – in time – information and supply choices •  reduce environmental impact by e.g. improving efficiency, optimizing spatial delivery networks •  increase reliability and security of supply and general QoS •  reduce management overhead

In addition “ SmardGrids must include not only technology, market and commercial considerations, environmental impact, regulatory frameworks, …, but also societal requirements and governmental edicts”.

Source: SmartGrids_SDD_FINAL_APRIL2010


Goals

n  Reduce costs n  Better correlate energy demand with supply and vice

versa n  Predict demands in real time n  Provide detailed usage information n  Co-ordinate devices within and beyond LAN’s

n  Reduce environmental impact n  Improve efficiency and reduce energy use

n  Secure future energy supply n  through renewable energy resources

n  Provide a more robust framework n  Move from large scale power plants to micro

generators and virtual power plants

Energy Demand

Energy Distribution

Energy Supply


Driving Forces Facts n  Increased energy demand n  Diminishing resources n  Environmental impact n  Need for optimizing the use of energy Technology n  Outdated infrastructures n  Move towards renewable resources n  Shift towards small scale power generators n  Latest advances in technology Other n  Federal stimulus n  Regulatory Frameworks

Source: http://carbon-pros.com/blog1/2009/07/smart_grid_ecosystem.html


Challenges n  Complexity

n  Energy networks on a world wide scale are larger and arguably more complex than the internet and comprise more “users”

n  Data volumes n  The amount of data to be monitored transmitted,

processed and reacted upon is vast n  Real time aspect poses a significant challenge

n  Cost of installation and maintenance n  Trade-off between savings achieved and the the costs to

achieve them are still unbalanced n  Security and privacy concerns

n  It has been reasoned that users behavior can be deducted through the energy usage (e.g. a person is not at home if energy use us below a certain threshold)


The Grid Ecosystem

Based on http://carbon-pros.com/blog1/2009/07/smart_grid_ecosystem_part_4.html

Possible Workflow 1.  Demand-Supply Manager (DSM)

detects an decrease / increase in demand and advices Home Management Systems (HMS) to enable / disable (non-)essential power use within its ‘reach’.

2.  Based on specific Prosumer preferences and available devices, the HMS advices individual devices to power up / down or increase / decrease power output / intake.

3.  This request is received through a LAN and individual actionable devices accept / reject the request also providing feedback to HMS.

4.  Enterprise Apps monitor power consumption and adapt current energy costs to promote the cut back on energy.

5.  Grid Overlays provide hierarchical or network like organization on which DMS operate at various levels of granularity and on which self-organization can be facilitated.

Applications

Demand Supply Manager

Network

Util

ities

Providers / Custom

ers

Enterprise Apps HMS

Devices Grid Overlays


A Typical Day in the UK

Source: www.nationalgrid.com


Event Based Energy Demand

Source: www.nationalgrid.com

Self-organisation based on n  Spatial regions n  Environmental considerations n  Regulatory frameworks n  Demand and supply

characteristics n  Device types n  Device properties n  Social behaviour n  Commercial objectives n  Event based patterns


Towards Self-Evolving Energy Networks

Smart Meters

Actionable, Self-aware Devices

Networked Intelligence

Enable Monitoring


Smart Meters n  Purpose

n  automatically collect consumption, diagnostic and status data from smart metering devices such as water-, gas-, electric- meter) and transmit them to relevant utility providers

n  Advances n  Detailed and real time overview to the consumer n  Customized billing as an incentive to save energy n  Saves utility providers the expense of periodic trips to each physical location

to read individual meters n  Limitations

n  No detailed monitoring possible n  No control / management of devices

n  à The real time information collected, coupled with analysis, can help both utility providers and customers to better control the demand and supply of resources

n  Potential savings will largely depend on a change of behavior of the consumers and their manual actions


Home Management Systems

Intelligent systems have the potential to reduce the household energy

consumption by 31% [Otellini, CEO Intel

Intel Hom

e Managem

ent Dashboard



Smart Meters


Networked Intelligence

Enable device management and more detailed

monitoring


Self-Awareness n  What

n  Wikipedia - Self-awareness is the awareness of the self as separate from the thoughts that are occurring at any point in time.

n  In this context – Self-awareness means that each object / device is aware of its current status and context of use and their interrelation with other devices and the users that are available within the same environment and, in some cases, beyond.

n  Why n  Self-awareness is a pre-requisite to be able to evaluate and compare states and behavior

to pre-defined standards and values in a self-conscious way. n  This includes in particular the actual and expected consumption of resources

n  How n  Sense and translate relevant contextual information into device specific and situation-

aware concepts to be stored, processed and evaluated by the self-aware object / device.

n  E.g. smart energy profiles n  A bottom-up approach

n  Centralised approach is not feasible due to the complexity and the number of objects involved.

n  For an IE to become fully self-aware, virtually every object or concept therein has to be self-aware

n  For instance, for a home management system to be fully self- (or energy) aware, all devices it is connect to need to be self-aware


Actionable Devices n  Actionable means that devices can adjust their own operational

parameters either by themselves or through external stimuli or advice and enables the efficient and autonomous management of devices and device ensembles based on specific local or global objectives

n  Actionable devices reflect both end-users as well as providers and provide the actionable interfaces that are required to autonomously manipulate demand and supply

n  E.g., individual devices may deactivate themselves for a short period if available energy levels drop below a certain threshold or device ensembles may be coordinated in a way that only a maximum number of devices is active at any given time

n  Similar, components that generate or distribute energy, could be dynamically (de-)activated or configured, respectively, to serve energy on-demand

n  Nevertheless, within autonomic frameworks, each device must be aware of itself and its use to override outside control if necessary



Smart Meters


Networked Intelligence Enable global demand and supply management


A Framework for Networked Intelligence n  If self-aware devices are only able to reason about themselves then the usefulness

of such an environment would still be limited as such objects would only exit and act in isolation. That is, if they would not communicate with other objects about their current context of use or about their collective use as required for achieving more complex tasks.

n  For IE’s to become fully self-aware, virtually every object or concept therein has to feature such a smart profile in dependence of its individual properties.

n  This emphasizes the need for a conceptual layer that n  links the lower oriented physical world to a,

conceptually, higher oriented user layer to which services are offered / delivered too;

n  self-organizes knowledge as well as objects based on their properties or context of use;

n  organizes the organization as well as the communication and interaction between smart devices ↔ activities ↔ users in both directions;

n  Executes relevant measures in support of the self-organizing process


Monitor / Control

Interfaces

Actionable Devices – Consumer / Producer

Self-organising Distribution

Network

In essence, such a layer would bridge the gap between the isolated use of energy by smart devices and complex coordinated activities, which can be monitored, aided, guided or controlled at

all levels of granularity thus achieving scalability

A Framework for Networked Intelligence


Conclusions and Future Work n  The energy grid of the future is one of the most important and at the

same time most difficult vision for today n  Socio-economic aspects offer great potential for the organization and

operation for future infrastructures n  In particular, user behavior, commercial and regulatory frameworks

need to be incorporated into the new infrastructure n  Nevertheless, the dynamic modeling of social and economic objectives

and the subsequent adaptation of the underlying environments is still subject to further research

Future work will concentrate on but is not limited to

n  Efficient and dynamically configurable monitoring and analyzing techniques n  Distributed self-organization techniques n  Self-awareness and device management mechanisms n  Predictive Environments


Thank You

Matthias Baumgarten -

[email protected]


Players

Source: http://carbon-pros.com/blog1/2009/07/


Intelligent Environments n  What are they: Reflect infrastructures to which sensors, actuators and other computational

components are deployed and in which they interact with each other in order n  To monitor and to understand complex behavior and interaction between devices and users. n  With the aim to actively adapt the environment based on the current context and n  To aid the interaction between users and the environment

n  What is the problem: Considering the large number of objects involved and the potentially infinite number of relationships between them it becomes ever more difficult to properly comprehend IE’s over time.

n  Solution: IE’s need to become Self-Aware n  They need to be intrinsically interwoven with dynamic and flexible monitoring systems and inference

mechanisms so that they are able to constantly establish, remove or refine the properties and the relationships that exist between different stakeholders on an operational as well as a social or business level.

n  This will ultimately provide the knowledge base for advanced reasoning and prediction capabilities that would eventually allow IE’s to self-evolve depending on n  their own dynamic context, n  individual stakeholders n  Even more compelling, the interactions and relations between them.

n  As a consequence, IE’s would be more flexible with respect to their use, they would be more resilient and failsafe and would in general be able to provide a higher degree of interaction as well as contextual understanding.

n  Requirement: A pre-requisite for this vision is the requirement of individual devices to become self-aware thus providing a high degree of understanding of n  their own operational status n  their context of use n  their interrelation with other devices and the users that are available within the same environment and, in

some cases, beyond.

Education

Towards Intelligent and Self-Evolving Network Infrastructures for Energy Management