Smart grid(v1)

Sahar Rahim
MS-Electrical Engineering
Supervisor: Dr. Nadeem Javaid
Smart Grid
COMSATS Institute of Information Technology, Wah Campus,
Pakistan

Contents
 Introduction
 Conventional power grid
 Smart grid
 Comparison between Conventional and Smart grid
 Difference between Conventional and Smart grid
 Benefits of Smart grid
 Distribution generation
 Energy Storage banks
 System Model
 Proposed Solution
 Billing Mechanism
 Conclusion
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COMSATS Institute of Information Technology, Wah Campus, Pakistan

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Traditional power grid
 Interconnected and complex network
 Deliver electricity from utility companies to consumers.
 Comprises of following four major parts as in Fig. 1*
 Generation
 Produce electrical power
 Non-renewable resources (fossil fuel, coal, gases, e.t.c.)
 Renewable resources (wind, solar, water, e.t.c )
 Transmission
 Bulk of high-voltage transmission line.
 Transformers (Step-up, step-down)
 Towers.
 Distribution
 To distribute electrical power.
 Relays
 Interrupters
 Consumption
 Residential load.
 Commercial load.
 Industrial load.
Introduction (1/4)
Fig. 1: Conventional power grid
* https://cleantechnica.com/2015/12/16/how-the-grid-works-why-renewables-can-dominate/

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Introduction (2/4)
* https://en.wikipedia.org/wiki/Electrical_grid
Drawbacks
 Unintelligent electricity system.
 Conventional power grid suffers lots of economical losses.
 Contributing factors and its consequences include*:
 Aging equipment:
 Unreliable--higher failure rates.
 Customer interruption rates--maintenance costs, repair and restoration costs.
 Obsolete system layout:
 Require serious additional and smart substation.
 Lack of computational abilities.
 Lack of communication abilities.
 Outdated engineering:
 Traditional tools for power delivery.
 Lack of smart electronic control and sensors.
 Lack of storage system.
 Lack of energy management systems.

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Parts that can be made smart
 To increase efficiency, reliability
and robustness of the entire electrical
power system.
 In this regard, there is a need to modify
all sections of electrical power grid.
 We have summarized these section
as in fig. 2
Introduction (3/4)
Power system
Generation
Smart Ways of
Generation
Water powered
LED shower
Solar, wind,
hydro energy
Piezoelectric
Effect
Transmissio
n
Intelligent Ways of
Transmission
Self healing
Machine
communication
Eliminate
transmission
lines
Smart
electronic
sensors
Distribution
Efficient
Distribution
Smart metering
Smart control
room
Optimization
techniques
Consumptio
n
Cost- effective
Consumption
Dynamic Tariff
models
Energy efficient
appliances
Fig. 2: Sections of power grid

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Smart grid(Evolutionary power grid)
 Infrastructure that supports*
 Advanced electricity generation, delivery, and consumption;
 Advanced information metering, monitoring, and management; and
 Advanced communication technologies.
 Steps for conceptual design of a smart grid as in fig. 3
 Visualizing power system in
real time
 Increasing system capacity
 Eliminating bottlenecks
 Enabling a self healing system
 Enabling connectivity to
consumers
Introduction (4/4)
Fig. 3: Concept of Smart power grid

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Comparison between Conventional
power grid and Smart grid
* www.slideshare.net/jhasumit/smart-grids-business-case

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Difference between Conventional grid
and Smart grid

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Benefits of Smart grid
 Generation (Distributed)
 Transmission (Bi-directional)
 Distribution
 Computational ability
 Communications infrastructure
 Reliability
 Intelligent Fault detection
 Intelligent Fault anticipation
 Sustainability
 Bank of electrical energy
reservoirs
 Demand side management(DSM)
Smart grid
Security DSM
Load
management
Demand
response
Network
topology
Fig. 4: Smart grid units
Fig.5: Main features of smart grid

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Distribution generation
* http://carbon.coop/blog/zapaman/community-smart-grid-prosumer-perspective.
 Smart grid will enable renewable resources i.e.
 Solar energy
 Wind energy
 Hydro energy plants
 Bio-gas energy plants e.t.c.
 Promotes consumers to
actively participate in
energy management system.
 Smart grid will lessen
CO2 emission benefits.
Fig. 6: Expected CO2 emission

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Distribution Energy storage banks
* https://en.wikipedia.org/wiki/List_of_energy_storage_projects
 Grid energy storage is a collection of methods
 Used to store electrical energy on a large scale.
 Electrical energy is stored
 When production exceeds consumption and
returned to the grid when production
falls below consumption.
 Some notable energy storage projects
include*
 Sir Adam Beck Hydroelectric Generating Stations
 Bear Swamp Hydroelectric Power Station
 Seneca Pumped Storage Generating Station
 Salina Pumped Storage Project
 Carters Dam
 Smith Mountain Dam
 Matanoagawa Dam
Fig. 7: Energy Storage Systems

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System Model (1/2)
* https://en.wikipedia.org/wiki/Appliance_classes.
 One of the vital task while proposing smart grid infrastructure is
system model designing.
 Classify all smart appliances.
 Classification is based on following
factors:
 Usage modification.
 Time sensitive.
 Power rating.
 Length of operation
Fig. 8: Load classification
Load
classification
Fixed appliances
(lights, fans, oven,
toaster, tv, etc.)
Shiftable
appliances
(washing
machine, dish
washer, clothes
dyer, etc.)
Elastic
appliances
(air conditioner,
water heater,
space heater,
etc.)

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System Model (2/2)
* http://www.experian.com/small-business/consumer-classification-mailing-lists.jsp.
 Classification of end users to optimize consumption section is also a
big task in smart system modeling.
 Consumers are classified on the basis of their energy consumption
patterns*.
Fig. 9(b): Consumer classificationFig. 9(a): “N” Consumers

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Proposed solution (1/5)
* https://neos-guide.org/optimization-tree
 Deficiencies in conventional power system
treated as mathematical problem.
 To design energy efficient and cost
effective model of smart grid, consider fig. 6.
 Addressed problem is formulated by
using different optimization
methods*.
 Unconstrained Optimization
 Constrained Optimization
 Deterministic Optimization
 Stochastic Optimization
 Continuous Optimization
 Discrete Optimization
 Unconstrained Optimization
 Constrained Optimization
Fig. 10: Smart grid units
Optimization
problem
User comfort
Maximization
Minimize both
electricity bill and
aggregated power
consumption
Power consumption
minimization
Electricity bill
minimization
Without integration
of RESs
With integration of
RESs
PAR reduction

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* https://neos-guide.org/optimization-tree. **http://students.ceid.upatras.gr/~papagel/project/kef5_5.htm.
 Different algorithms are used to find feasible solution of designed
optimization problem.
 Some of the algorithms are stated here*
 Exact algorithm
 Difference Approximations
 Discretization Methods
 Feasible Sequential Quadratic Programming
 Gauss-Newton Method
 Gradient Projection Methods
 Hybrid Methods
 Interior-Point Methods
 Line Search Methods
 Newton Methods
 Heuristics and Meta-heuristics**
 Genetic Algorithm
 Particle swarm optimization
 Binary particle swarm optimization
 Ant colony optimization.
Fig. 11: Exact algorithm and Heuristic techniq

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* https://www.cs.wmich.edu/~elise/courses/cs6800/Genetic-Algorithms.ppt.
Genetic algorithm (GA)
 Genetic algorithms are a randomized heuristic search strategy*.
 Basic idea:
 Simulate natural selection, where the population is composed of candidate
solutions.
 Focus:
 Evolving a population from which strong and diverse candidates can
emerge via
 Mutation
 Crossover.
Fig. 12: GA algorithm

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* https://www.macs.hw.ac.uk/~dwcorne/Teaching/bic_pso.ppt
Particle Swarm Optimization (PSO)
 Combines self-experiences with social experiences*
 Basic idea:
 Number of particles
 Searching for the optimum
 Moving and has a velocity.
 Particle remembers the position
it was in where it had its
best result so far (its personal best)
 The particles in the swarm co-operate.
 They exchange information about what
they’ve discovered in the places they
have visited
 Binary PSO is one of the most important algorithm
 used in optimization problems in Smart grid.
Fig. 13: PSO algorithm

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* https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms
Ant Colony Optimization (ACO)
 Combines self-experiences with social experiences*
 Probabilistic technique for solving computational problems which
can be reduced to finding good paths through graphs.
 Inherent features:
 Inherent parallelism
 Stochastic nature
 Adaptivity
 Use of positive feedback
 Autocatalytic in nature
Fig. 13: ACO algorithm

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Billing Mechanism
* www.cuts-ccier.org/.../ppt/Components_of_Electricity_Tarfiff_Role_of_Consumers.
 Fixed Cost
 Cost of setting up a
 Power Plant
 Inverter
 Plant & Equipment
 Personnel Employed
 Raw Material Inventory
 Variable cost
 Cost of generating the quantum of electrical energy and covers the fuel costs for
generating this quantum of electricity.
 The Fuel in a coal fired Thermal Power Station is coal (Primary fuel) and Oil
(Secondary fuel).
Fig. 14: Billing
mechanism

 Smart Grid provides intelligent, advanced power
control for the next century
 Many new technologies involve for supporting
sensing, controlling, human interfaces.
 Charging electricity cost is fundamental
infrastructure can be implemented similar to stock
market in smart grid.
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Conclusion

Smart grid(v1)

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