Sameh El Khatib

8/11/2019 Sameh El Khatib

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Wednesday, October 09, 2013

Smart Grids: The Path Going Forward,

Dr. Sameh El Khatib, and Dr. Amro FaridEngineering Systems and Management Dept., Masdar Institute

3rdSMART GRIDS AND SMART METERS SUMMIT

2425 SEPTEMBER 2013, ABU DHABI, U.A.E.


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Introduction


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Making grids smarter is a required transformation fueled by

several drivers characterizing current factors & inclinations


Environmental & sustainability

concerns

Energy demand growth

Electrified transportation

Aging power systems infrastructures

Empowerment of demand-side

Operational challenges in terms of

requiring significantly higher levels of

regulation and ramping capacity

New flow patterns at the distribution

level which necessitate drasticchanges to the protection, distribution

automation, and voltage/VAR

management

Limited dispatchability and increasedintermittencies, which result in

increased ancillary services

Monitoring and automationdeficiencies leading to inadequacies

in meeting increased loads on

distribution networks

Need for Smarter GridsEffect on Power SystemsFactors &

Inclinations

Control has to rise to the occasionand counter a significant number of

these challenges

Advances required in sensing

technologies to make new

information available about various

aspects of the grid

Progress in communication

technologies needed to make datadynamically available at pertinent

locations within the grid


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A Smart grid is an end-to-end cyber-enabled electric power

system bringing control and automation to center stage


The Essence of Smart Grids is to

Enable integration of intermittent

renewable energy sources;

Help decarbonize power systems;

Allow reliable and secure two-way

power and information flows;

Promote energy efficiency;

Facilitate effective demand management

and customer choice;

Provide self-healing from power

disturbance events;

Allow power systems to operate

resiliently against physical and cyber

attacks

Smart Grids Facilitate

Decision making, in an automated manner,

from seconds to seasons, at desired, new,

and distributed locations

Opportunities for control:

Reducing consumption Exploiting renewable sources

Increasing reliability and

performance of the transmission

and distribution networks

Demand response thus allowing load to be

shaped rather than followed

The use of plug-in electrical vehicles as

dispatchable assets aiding distribution

system

The usage of energy storage technologies to

be used as alternatives to fossil fuel-based

spinning reserves.

Vision for Smart Grids

Closing loops in power systemswhere they have never been closed

before, across multiple temporal andspatial scales

Enable decision making underuncertainties, across broad temporal,geographical, and industry scales

Meet desired emission andsustainability targets whilemaintaining accepted levels ofreliability


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In this talk we will discuss the role of control systems in the

evolution of Smart Grids and touch upon the way going forward


A look into theFuture

Baseline

Going Forward

Introduction Presents an overview of Smart Grids and their role in current power systems

Discuss drivers for change that pave the way for a paradigm shift in the electric grid

Present different scenarios of Smart Grid evolution that might emerge in the future along with researchchallenges associated with such scenarios

Highlight practices in current control systems illustrating the roles of control in power systems such as

power balance, frequency regulation, and reactive power control


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Baseline


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The challenge of power systems is the requirement of interrelated

tools of dynamical systems analysis, control, and optimization


Historical and current practices in power

grid control focus on four major topics:

Generation power set point selection

through market operations or economic

dispatch

Primary and secondary control for frequency

regulation and power balance

Reactive power control for regulation of

voltage magnitudes

Communication and sensing technologies to

support these control functions.

Challenging Characteristics of Power Systems

The transfer of power through long-distance, high-

voltage transmission induce dynamic

electromechanical coupling on a nearly continental

scale of power grids

The mix of near-speed of- light electrical phenomenawith mechanical response of generators and load

means that major disturbances can propagate over

long distances, at very high speeds

At slower timescales, the characteristics and cost of

grid operations depend heavily on the geographic

and cost mix of generation and load which implies

that considerable attention is devoted to periodicupdates of the set points of many thousands of

pieces of equipment throughout the network

Control for the grid is not only a problem of feedback

design to achieve regulation, desirable dynamic

response characteristics, or both, but also the

selection of the quasisteady state or steady-state

operating point as determined by the grids nonlinearpower flow equations of optimality and reliability

equilibrium

Control as interpreted in

power systems applications,

must be understood in a

very broad context

1

2

3

4


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Generation dispatch has a huge impact on cost of power

production inducing the use of periodic optimization to dispatch


1 Generation power set point selection through market operations or economic dispatch

Load treated as an uncontrolled,exogenous input, and electricutilities have been operated withan assumed obligation to serve

The sum of the power output levels ofgenerators must be regulated to matchthe total load plus losses on the grid

Evolution of complex electricitymarkets that are based on

power pools governed byindependent system operators

High dimensional regulation problem, inwhich a very large number of generatingunits are required to stably regulate tonew set points of desired megawatt (MW)

power output, while maintaining reliable

system operation

Situation Contro l Requirement

Historic

Cur

rent

Solut ion Method

Solved on a periodic basis,on timescales of minutes asan optimization problem, toselect desired set points for

generator output

Solved as a game where thepool receives offers to selland bids to buy electricity

Pool solves an optimization

problem that minimizesoffered generation costs andmaximizes buying bidssubject to generation,transmission and secur i ty-cont ingency con stra in ts


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Smart Grids assist in the control challenge of generating units

stabilizing to their set point while maintaining reliable operation



Control Challenge at this Level

Determination of system-wide stability properties is

heavily influenced by the nature of both continuously

acting and discrete control systems throughout the

network

The requirement of reliability adds a huge number ofscenario-based analyses (N1) secure

From a control analysis standpoint, this specification

is a large-scale robust stability requirement: stability

must be maintained for every member of a family of

systems, each representing a different discontinuous

structural change to the nominal system

A typical dynamic model for a power system is a

mixed system of nonlinear differential-algebraic

equations governing its dynamic response.

These requirements bring in much more complex,

large-scale system challenges inherent in operating

the power grid, as their satisfaction involves not only

the control systems of the individual generators, butalso of the transmission network, and of a wide range

of other grid equipment and load characteristics.

Smart Grids Will

Allow future power grids to greatly expand the

numbers and classes of equipment productivelycontributing to control through enhanced

communication and computation

Lead to more distributed control involving larger

numbers of contributors which carry great promise to

improve the stability, reliability, and economy, and to

reduce environmental impact of grid operation.


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Smart Grids also increase price elasticity of demand by facilitating

real-time engagement of retail consumption in periodic markets



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Stably regulating frequency reflects the objective to reliably

maintain the instantaneous balance between generation and load


2 Primary and secondary control for frequency regulation and power balance

Power Systems Fact 1

At bus locations with generators attached, the inherent physics of

synchronous machines dictate that the electrical frequency of the

generator voltage and the mechanical rotational speed of the

generator are locked in fixed proportion to one another so that

variation of frequency at these locations directly reflects deviations

in rotational speed away from the desired steady state.

Power Systems Fact 2

The nature of alternating current (AC) power transmission is such

that a synchronous region is in exact equilibrium only if electrical

frequency is equal at every node in the network (i.e., all

interconnected generators rotating at the same nominal speed).

Underlying Grid Control Problem

The requirement for stable dynamic performance, such that any deviation of the independent

frequencies of generators converge to steady state in a stable fashion

The quasisteady state regulation requirement that the shared synchronous frequency (equal at all

nodes in equilibrium) be regulated to a tight band about its desired 60 Hz (hertz) value

Primary

Control

Secondary

Control


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Primary control is a corrective feedback while secondary control

acts on a slower timescale over a wider region


2 Primary and secondary control for frequency regulation and power balance

A corrective feedback (often just a proportional gain) that incrementally changes a generators

power output in response to locally measured frequency/speed error

Each time the generator receives an updated market command for a desired MW output, this

update is simply a new set point to the feedback control system. This feedback measures terminal

electrical power delivered and correspondingly adjusts the mechanical shaft power input

(typically through valves controlling gas, or steam, or water flow delivered to a turbine).

Acts on a slower timescale, over a wider region, by modifying a subset of generators power set

points in the region, with the objective of regulating a measured signal called the area control

error (ACE).

The ACE signal comprises a weighted sum of area frequency error and deviations from set point

(scheduled interchange) of powers on select transmission lines that carry major power flows

in/out of the region of interest (Automated Generation Control)

Primary

Control

Secondary

Control


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In addition to active power control/frequency regulation is the

control of reactive power for regulation of voltage magnitudes


3 Reactive power control for regulation of voltage magnitudes

Power Systems Facts

An important qualitative feature of power flow in a synchronous grid

can be observed when power balance equations are written in

sufficient detail to represent reactive power balance at buses and its

dependence on voltage magnitude variations

If reactive power drawn or injected into the network at a bus istreated as a control input, the coupling of this input to the response

of voltage magnitude at that bus is quite strong

The impact of reactive power injection at a specific bus on voltage

magnitudes at neighboring buses drops off quickly away from the

point of injection

The problem of regulating voltage tends to be a more localized

problem, with a controllable reactive source at a given bus being

responsible for regulating voltage magnitude to a desired set pointat that bus or at a nearby neighboring group of buses

Remarks

There is coupling between voltage magnitude

behavior to frequency and angle which can be

exploited to design stability-enhancing

supplementary controls

Some aspects of the voltage control problem can

be viewed as more localized, and therefore

perhaps less challenging than active

power/frequency control

However As new classes of customer equipment

become more widespread, the characteristics of

load response can change in ways that make

voltage stability problems more critical

Smart Grids promise to advance

reactive power regulation without

undesirable coupling with other

regulation mechanisms


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Key contributions anticipated from Smart Grids are enhanced high

bandwidth and wide-area communication for control functions


4 Communication and sensing technologies to support these control functions

Energy Management System (EMS): Describes a wide ranging suite of software and hardware that supports a regional

control center in managing the production, purchasing, transmission, distribution, and sale of electrical energyEMS

SCADA

PMU

RTU

PLC

Automated

Metering

DCS

Supervisory Control and Data Acquisition (SCADA) system: An umbrella term to describe the wide range of physical

measurement and communication systems supporting operator control of remote (or local) equipment, whether the

physical media be microwave link, f iber optics, or wire line, and whether the control operation is opening or closing anetwork circuit breaker or commanding a set point change to a generator.

Phasor Measurement Units (PMU): Synchronized PMUs provide measurements of the voltage and current

magnitudes and phase angles, precisely time synchronized across large geographic distances.

Remote Terminal Units (RTU): Special-purpose microprocessor-based computers that contain Analog-to-Digital

Converters (ADC) and Digital-to-Analog Converters (DAC), digital inputs for status, and digital output for control

Programmable logic Controllers (PLC) are used to implement relay and control systems in substations

Designed to upload residential and/or commercial gas and/or electric meter data.

Plant Distributed Control Systems: plant-wide control systems that are used for power plant automation and control

Description of High Level Critical Systems Forming the Architecture of Present Day Grid Control Operations

Power Systems use power line carrier (PLC), microwave, fiber-optic,

pilot wire and wireless as underlying communication layers


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Going Forward


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Global movement towards Smarter Grids is fuelled by four major

drivers


Driver Description

Environmental

Stewardship

Societys future energy choices will likely be dominated by environmental constraints and compliance with local,

national, and global initiatives

The global decarbonization of energy systems has been steadily advancing facilitated to an ever-greater degree by

electricity

Reliability in Responseto Growing Demand

Power systems infrastructure is vulnerable to increasing stress from the imbalance between growth in demand for power

and enhancement of the power delivery system to support this growth

The result is increasing power outages and power quality disturbances

Empowered

Consumers

Made possible through a combination of technological, social, and behavioral changes, all of which will allow loads

to be responsive to the grids needs

In several places across the globe, demand response might be the only available asset to cope with unprecedentedgrowth in the demand.

Electricity SectorRestructuring

In the past 15 years global electricity sectors have witnessed trends toward privatization, deregulation, restructur ing, and

reregulation

A new energy value chain is emerging as a result of new regulatory environments, new technologies, and new players that

encourage competitive markets.


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The challenges are formidable however such challenges place the

notion of smart grids at the core of the solution path


Driver Challenges

Environmental

Stewardship

In the context of renewables, limited dispatchability necessitates new solutions that do not lead to increased

ancillary services. Their intermittency introduces several operational challenges in terms of requiring significantly

higher levels of regulation and ramping capacity. They also introduce new flow patterns at the distribution level,

implying drastic changes to the protection, distribution automation, voltage management, and VAR management

Reliability in Responseto Growing Demand

Significant new loads on distribution networks, many of which are inadequate when it comes to monitoring and

automation, requiring a major overhaul of distribution systems across the globe

Large, distributed loads have to be coordinated with grid operation to manage highly complex interactions that arisefrom spatial and temporal imbalances between requirements versus what is available from the grid

Empowered

Consumers

Modeling of empowered consumers without violating privacy or security concerns. A stressed infrastructure implies

that with additional demand and intermittent generation, reliability is severely compromised. Innovative methods forachieving and ensuring power balance are needed

Electricity SectorRestructuring

With price-based mechanisms taking center stage for the transformation of demand into a flexible entity, the challenge that

emerges is how real-time price is to be determined, with changing grid conditions both in generation and in demand

Market power shifts and price abuse


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Policy, technological advances, standards, and interoperability are

key enabling factors facilitating movements toward Smart Grids


Technology

Policy

Interoperability

Enabling Factors in the Deployment of Smart Grids

Standards

Digital advances in information and

communication of varied aspects of the grid,

Innovations in power electronics that allow

bidirectional flow and advanced control of all

aspects of the grid

Blueprint for smart management (i.e., control)

of this information, enabling decision making at

all crucial spatio-temporal locations in the grid

It is important that components and subsystems

from different suppliers are based on open,

accessible interfaces and protocols

Without standards, the effort and expense of

product development and system integration are

increased

The importance of interoperable standards for

the Smart Grid is globally recognized

The Smart Grid is a systems of systems;

solutions are, and will increasingly be,

integrations of components, often from

different sources

The components in question are not just

physical products, but also communication

protocols, information and data models,

software implementations of algorithms, etc.

Recent policies in the U.S., China, India, E.U., U.K., and

other nations throughout the world, combined with

potential for technological innovations and business

opportunities, have attracted a high level of interest in

Smart Grids

Nations, that best implement new strategies and

infrastructure might reshuffle the world pecking order:

Emerging markets could leapfrog other nations


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A Look into the Future


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Smart Grid promises revolutionary changes to the generation,

delivery, storage, and use of electricity


Scenario Vision

Grid-scale real-time

endpoint-based control

Hundreds of millions of active endpoints: sensors, actuators, and communication devices are deployed at generators,

along transmission lines, at substations, in transformers, in distributed energy resources (DER) such as photovoltaics and

wind turbines, and in inverters, storage devices, electric vehicles, and microgrids

Millions of individual and institutional agents: stakeholders in the operation of the new power-ICT (information

communication technology) grid include industrial, commercial and residential customers, governmental and university

campuses, microgrids, utilities, power generators, energy services companies, and regulators

Dynamic pricing and

multiple-horizon power

markets

A radical market reform from the realization that both generation and demand are implicated in the need for reserves,

transmission line congestion, and voltage support, and thus both have a role in optimizing power system efficiency.

Full power market participation of both generation and loadsbe they large-scale centralized entities or small-scale

distributed entities. In other words, distributed loads and generation (e.g., rooftop PV, small wind turbines) have access to

high-voltage power markets on par with centralized generation and large wholesalers/load aggregators, while responding

to and affecting distribution network costs and power quality requirements.

Real-time, closed-loop,

demand response

Customer facilities integrate not just loads, but distributed generation and storage resources as well. All of these energy

assets are modeled with their dynamics and uncertainties formally captured and integrated with control and optimization

methodologies

Loads, storage, and generation resources, whether in homes, buildings, or industry, respond in real time to the state of the

grid, the variation of grid-level renewable generation, and other factors that traditionally were little more than disturbances

in old-style facility energy management

Renewable generation Active distribution systems and adaptive networks that differ from existing systems in four important aspects to be

discussed later

Smart meters, phasor measurement units,power electronics are the foundation on which

control can construct the future Smart Grid

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4


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Understanding and modeling electricity user utility,in particular, the utility of new flexible loads suchas HVAC, EV battery charging, and other storage-like schedulable loads. This involves inter-

temporally sensitive dynamics because theservice rate at a particular time is a function of thepast consumption trajectory.

Distribution network costs and congestion willneed to be incorporated in prices available todistribution network-connected consumers andproducers

Modeling abstractions employed must capture thefollowing information:

o The market scenario characteristics,

o Power system physics,

o Critical smart grid-related technologies,

o Distributed loads and resources that mightenable significant social welfare gains.

Today, centralized generation is theprimary full market participant, engaged intwo-way communications with market

operators

Other generation and the consumer sectorcan provide information to the market butare generally not involved in bilateralmarket interactions

In the proposed dynamic pricing scenario we envision all players

being full market participants


2 Scenario: Dynamic pricing and multiple-horizon power markets

Market reform has occurred in the timescales onwhich markets operate. The cascadingtimescalesday-ahead, hour-ahead, minutes-

ahead, and seconds-ahead transactionhorizonswith separate, incomplete, and ofteninconsistent market mechanisms employed foreach, have given way to a broader and seamlessspectrum of market and reserve choices

The gap in timescales between market-basedreserve pricing and centrally coordinated reservemanagement has been bridged

Distributed coordination is now accomplishedwith dynamic models and optimization algorithmsacross a broad class of market- facing assets.

Buying and selling covers active as well asreactive power.

Scenario Detai ls Current Practice Challenges / Research Prospect s


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Electricity consumption and performance of a vastvariety of facility-based devices and systems mustbe modeled with specific attention to variousdynamical aspects.

Advanced forecasting methods for loads andweather

Including end-use sectors in Smart Gridengineering is the necessity of modeling peopleas consumers as well as facility operators andoccupantsas elements of control systems

Pricing structures, policies, algorithms, andconstraints to handle coupling of power flows andmarkets at timescales that have the potential to

cause instability

The consideration of real as well as reactivepower, bidirectional power flows, and multiple-timescale coordination, requiring fundamentaladvances in feedback/feedforward andregulatory/supervisory control strategies.

In comparison to the future vision, thestate of demand response today seemsantiquated

Implementing automated demandresponse today is complicated enoughthat only large facilities can directlyengage in program

The main challenge in scenario 3 comes from the lack of

appropriate equipment for automated demand response


3 Scenario: Real-time, closed-loop, demand response

Advanced control technologies ensuring thatfixed, schedulable, and curtailable loads arerecognized and modeled

Production from on-site renewable generationsources is forecast, incorporating dynamicuncertainty, and these forecasts inform thedemand-response strategy

Fast dynamic response enables facilities toprovide the full range of ancillary services,including spinning and nonspinning reserve,frequency regulation, and reactive power support

The sophistication of control technology hasreached a level that enables sites to be

dynamically aggregated and disaggregated forautomated demand-response (ADR) programs.

The development of plug-and-play energy assets.



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Sensing, optimization, and control (SOC)algorithms must be designed in concert with anunderlying real-time communication andnetworking infrastructure

The actions of heterogeneous distribution systemsdevices with different response speeds need to becoordinated and adapted

An understanding of the spatio-temporal variationsand correlations in power flows on distributioncircuits resulting from massive spatially distributedgeneration capacity

Development of distributed control concepts suchas self-organization, cooperative control, and

virtual leader-follower architectures

Distributed state estimation methodologies canand should be developed, using the properties ofphysical distribution networks, cloud computing,and big data innovations to ensure safe islandingoperation and other requirements

At present, grids have a radial topology;their operation and protection schemesare simple and do not support directionaldiscrimination

There are very few intelligent devices(beyond radio- controlled relays andOLTCs)

Distribution network operations areplanned (open-loop) because changes indemand are relatively slow andstatistically predictable, and voltages arecoarsely regulated (the typical range is5%)

There is little measurement data available

in real-time to determine the operationalstate of distribution systems or theirequipment

Currently grids have radial topologies with simple operation and

protection schemes


4 Scenario: Renewable generation

Distribution systems will have massivepenetration of distributed generation integrated inboth medium-voltage (MV) and low-voltage (LV)grids. Distributed generation will be pooled asvirtual power plants, and their aggregated power

will be dispatched automatically

Microprocessor-based relays or intelligentelectronic devices (IEDs), will be installedthroughout distribution systems to integratemultiple functions (such as metering, protection,automation, control, and digital fault recording)

Smart distribution grids will have hierarchicalcommunication networks: wide-area networks(WAN), neighborhood-area networks (NAN), anduser-area networks (UAN).

Distributed systems will use distributed sensing,estimation, optimization, and control algorithms toallow massive penetration of distributedrenewables



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Smart Grids Mean:

Massive penetration of renewable generation

Reliability of supply under all conditions

Consumer engagement and empowerment

Cost efficiencies for all stakeholders

The way forward span the full design space

The relevance and importance of control extends across bulk and distributed

generation, transmission and distribution networks, residential, commercial, and

industrial facilities, and power markets and regulators Novel control-related insights suggest that the architecture and partitioning of todays

power system can and should be radically rethought

The way forward is contingent upon targeted, intensive and collaborative research and

development in control science and engineering

In conclusion, control technologies can play a crucial role in

achieving the broad societal drivers for the Smart Grid


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More details regarding the presented scenarios can be found in the IEEE Control

Systems Society (CSS) document IEEE VISION FOR SMART GRID CONTROLS: 2030 AND

BEYOND

To get more details about this document and its authors please contact Dr. Amro Farid

at: [email protected]

The scenarios in this talk were based on the IEEE CSS document:

IEEE VISION FOR SMART GRID CONTROLS: 2030 AND BEYOND
mailto:[email protected]:[email protected]


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Thank You

Wednesday, October 09, 2013 Version 1

Sameh El Khatib

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