The Smart Grid

1. IntroductionEnergy has been opined to be a major driver for any economy with its lack impeding societal

development [1-4]. Though not explicitly stated, it was posited to be instrumental to the full

realization of the Millennium Development Goals (MDGs). The significant growth witnessed in

China, Singapore, Malaysia, United States of America (USA) and OECD countries etc. could be

attributed to the fact that these economies have a huge per capita of electricity compared to the

countries in sub-Sahara Africa (SSA) and South East Asia (SEA) who have over 850 million

persons without access to electricity [5, 6]. The Figure 1-1 [7] shows a comparison between

some developed countries/regions and under developed/developing countries/region with respect

to electricity access while Figure 1-2 [8] shows the electricity per capita for the same

countries/regions. The low electricity access for the SSA region is seen to be less than 40% of its

overall population compared to 100% for the OECD countries and USA. This obvious electricity

(energy) deficiency for the SSA and SEA regions has also seen a decline in economic growth for

these economies due to the huge costs involved in running their industries.

Fossil fuels have continuously played a huge role in driving the generators and power houses

responsible for electricity generation in the developed economies due to their cheap nature and

advanced technology in this sector. However, recent occurrences bordering on energy security

and sufficiency seem to cast doubts on the viability and sustainability of this cheap source of

Fig 1-1: Electricity access (% of population) for selected regions Fig 1-2: per capita electricity consumption (kWh) for selected regions

Environment

Sustainable development

Economy

Energy

Fig 1-3: energy, environment and economy mix

energy [9] as their harmful effect on the environment alludes to the fact that in order to safeguard

the quality of life of the future generations, cleaner and more efficient energy sources be

evolved. Stimulated by environmental concerns as regards climate change and the growing

pressure to reduce carbon emissions from the energy sector, there has been a heightened global

interests in renewables [10-12] alongside new and efficient technologies [13] with a substantial

commitment to the development and deployment of these technologies. This is consequent upon

the fact that sustainable development is only feasible when there is an un-harmful synergy

between the environment, economy and energy as shown in Figure 1-3 [14, 15].

Traditionally, the movement of electricity from the generation station to the consumer is shown

in the Figure 1-4. It is observed from the Figure 1-4 [15] that electricity movement is

unidirectional and involves huge losses down the electricity transfer network as shown in the

Figure 1-5 [16]. The consideration of renewables however as an alternative to fossil fuel based

electricity generation has seen adjustments being made to the movement of electricity as the

incorporation of these renewable energy sources (RES) means generation could be injected as

either the generation entry point or the distribution point. Similarly, the introduction of such

schemes as the Feed-in Tariff (FiT) and grid coupled inverters mean consumers could also

become electricity producers (leading to the evolution of the so called ‘prosumers’). This

injection of electricity at these points different from the generation side takes advantage of the

Generation

Transmission

Distribution

Consumption

Level 1

Level 2

Level 3

Level 4

Energy Flux is unidirectional

Fig. 1-4: Traditional concept of Power flow

fact that electricity is bi-directional in movement depending on net energy balance as it flows to

establish equilibrium. This bi-directional movement of electricity is thus shown in the Figure 1-6

[15] with Figure 1-7 showing the exploded traditional grid architecture.

The significant growth in the exploitation of RES like wind and solar has seen a tremendous

increase in renewable energy technologies (RETs) that allow for the full maximization of these

RES. For example, the combined installed wind capacity in 2010 was estimated to be about 160

GW (an increase of about 60 GW compared to 2006 estimate) and is expected to rise to about

460 GW in 2015 [17]. China has seen an aggressive wind program take its wind farm capacity to

about 13242.2 MW representing a 108.4% increase from 2008 [18]. In the United States,

cumulative wind power capacity as at 2012 was put at 51, 630 MW due to an additional wind

power generation capacity of about 4728 MW in 2012 alone [19].

Primary energy for Electricity generation (x, MWh)

Generated Capacity, y MWh (one-third of x, MWh)

T & D Losses (9% of y, MWh)

Distributed Electricity (91% of y, MWh)

x MWh

y = (x/3) MWh

(9*y/100) MWh

(91*y/100) MWh

Fig. 1-5: losses in current energy chain

Generation

Transmission

Distribution

Consumption

Energy Flux is bidirectional

Fig. 1-6: New concept of Power flow

Distribution

DG

Self-Generation

The increase in these technologies notwithstanding, a limitation in the utilization of the

tremendous capabilities of RES occurs due to the nature of the traditional grid. A system is

therefore needed that is flexible and seamlessly allows for the sharing of resources. Also, there is

the need for this envisioned grid to incorporate fully information and communications

technology (ICTs) in its operations. A total overhaul would thus be needed in making the

existing grid even a fraction of what this ‘optimistic’ grid should look like. Also, the huge costs

involved would practically make it almost impossible.

Figure 1-7: Traditional grid exploded architecture

The block diagram of the envisioned smart grid is shown in the Figure 1-8. It is observed from

the Figure 1-8 that such a grid must be capable of accommodating the variability caused by

fluctuating RES, the instability caused by consumers feeding back electricity to the grid (from

their roof top solar panels, plug-in hybrid electric vehicles (PHEV), battery storages etc.), the

wind farm operator injecting energy at medium voltage into the grid from another location etc.

The complexity is further increased considering the fact that alternating currents is the standard

of operation making synchronization at points of common coupling (PCC) very difficult.

Overcoming all these challenges would further lead to the problem of energy balance between

demand and supply. Considering the fact that at every instant supply must match demand, the

grid must be capable of ensuring this. Also, in the event of a supply surplus, the grid must be

able to route extra electricity to storage or initiate shut down procedures (or communicate a

reduction in generation capabilities of some generating plants). Furthermore, it may be capable

of predicting demand and ensuring that available supply matches the demand for the

instantaneous time under consideration.

Figure 1-8: Block diagram of the envisioned smart grid showing its subsystems

It can thus be seen that the complexity of this system is also further complicated considering the

fact that electricity cannot be easily stored and a lot of institutions, companies, industries and

service oriented organizations like hospitals, clinics, transport etc. depend solely on the grid to

carry out their activities and a failure in the grid supply will initiate a torrent of problems. The

exploded architecture for such a complex grid call the smart grid is shown in the Figure 1-9. The

Figure 1-9 shows the role of ICT in facilitating the operations of the smart grid. From the Figure

1-9, a smart grid controller is introduced to harness the outputs of the other subsystems. Artificial

intelligence (AI) is also seen to be of great importance in the prediction and modelling of such

parameters as wind speed, solar radiation, demand profile, supply potential prediction etc.

Similarly, the generation controller block controls the generation from plants based on advanced

information from the controller etc. Other subsystems like the advanced metering infrastructure

(AMI), Demand Response (DR), Dynamic Pricing (DP), Communications control etc. are also

incorporated to ensure that system balance is ensured.

The two way communication between the consumers and the grid is also maintained through the

smart meters which communicate to users their consumption patterns, current prices etc. This

report thus aims at providing a thorough and summarized description of the major subsystems

that make up the smart grid and how they interact across the smart grid network. Section 2

introduces the concept of smart generation techniques such as distributed generation, microgrids,

virtual power plants etc. Section 3 provides a detailed review of energy management techniques

for the consumer side traversing such areas as energy management techniques and its growth,

demand side management (DSM), dynamic pricing etc. Section 4 examines the role of

government and regulatory institutions in ensuring a safe operation of the smart grid examining

policies ranging from fair trading to privacy issues, grid codes, standards etc. Section 5 examines

some smart grid initiatives being localized for localization in SSA and SEA considering the fact

that they have a bulk of the persons without access to electricity. This section further explores

the financial initiatives and technical frameworks being set up to encourage the proliferation of

electricity. Section 6 examines the current status of the smart grid using selected case studies

while providing a chart for its future progress with section 7 concluding the report.

Figure 1-9: The exploded smart grid architecture.

2. Generation techniques

Electricity generation in the smart grid differs from electricity generation in the traditional grid.

In the traditional grid, generation is based on assumed full demand resulting in under-utilization

of the generation plants and fuel wastage since there is better fuel utilization at rated capacity.

However, in the smart grid, generation is controlled based on predetermined demand. This way

the need for spinning reserve is usually reduced. Also, in the envisioned smart grid attention is

shifted from the conventional means (fossil fuels) of electricity generation to more

environmentally friendly and sustainable means of electricity generation like wind, solar and

biomass (though there has been a heightened interest in gas in recent times). The advantage of

this newer means of electricity generation being considered (solar and wind) lies in the fact that

supply from them could be dispatched (scaled) based on competing factors like demand, cost etc.

The integration of these RES is also facilitated by power electronics that handle the variations

they introduce in voltage and frequency. An additional difference here is the fact that generation

is not only from the generation point but across the electricity network (storage, consumers etc.).

This flexibility of generation in the smart grid sets it apart from the traditional grid. Biomass for

example is gaining interest as a means to meeting the European Union (EU) goals on reduction

in greenhouse gas (GHG) emissions due to its little start-up capital investment and dispatch able

nature. In Canada, there were 23 active biomass to electricity projects as at March 2013 with a

combined capacity of about 18.7 MW. Iskandar Malaysia (IM) hopes to buoy its RE contribution

to 6% of total generation in 2015 with further investments meant to increase this to 10% in 2020

and 12% by 2025. In all these, biomass is being posited to play a critical role in its RE electricity

generation [20-22]. Electricity generation from the sun through photovoltaic (PV) technology is

also a major RES. In fact, solar energy is posited to be the most abundant form of energy with

the sun being an obviously clean and cheap energy source. As at 2005, installed PV capacity

worldwide was an estimated 1.5 GW. Furthermore, it is reported that the hourly solar radiation

reaching the earth if harnessed could meet the energy demands of the world’s population for a

year. The utilization of RES at local places could be exploited using a number of technologies. A

couple of these are described subsequently [23-25].

2.1. Distributed Generation (DG)

The concept of embedded generation (DG) stems from the fact that generating electricity at load

centres reduces transmission and distribution losses. As a component of the smart grid, DGs

greatly encourage the exploitation of local resources. Furthermore, they can also be incorporated

into the existing grid or operated as stand-alone devices. Familiar terms associated with DG

include distributed energy resources (DERs), microgrids, virtual power plants (VPPs), small

scale energy zones (SSEZ) etc. According to [15], the infrastructure that facilitates the synergy

between DG and storage is referred to as distributed energy resources (DERs). Various

definitions have been put forward describing the VPP. They have been described as energy

mangers that hire DERs to profit maximally from their exploitation [26], to a primary vehicle

that is capable of delivering the most efficient cost integration of DERs [13]. A more robust

definition for the VPP was put forward by [15] “as intelligent autonomous system equipped with

advanced metering infrastructures, information and communication technologies, energy

management systems and a host of other smart devices that aggregates dispersed energy

resources, distributed generation units and renewable energy sources in a bid to creating a virtual

pool of power with uses varying from meeting supply shortfall to supplying isolated areas and

for other purposes as defined by the reasons behind its design while meeting all technical, cost

and future constraints.” This exhaustive description aims at anticipating future needs and

upgrades and providing an avenue for such in the VPP design. In conveying the description of

the VPP put forward by [26], the Figure 2-1 provides an apt overview of the VPP.

PV Array

PV Array

microCHP

Wind Turbine

Micro Dam

VPP

PV Array

PV Array

VPP bidirectional supply route

From distribution Substation

Load/consumers

VPP Communication route

Prospective DER for “hire”.

Prospective DER for “hire”.

Energy playing field

Fig 2-1: Energy playing field with VPP as manager

3. Energy Management

Energy management is actually a core in the smart grid development since the overall aim of the

smart grid initiative is to discourage the need for the creation of bigger and additional generation

plants. The smart grid initiative is premised on among other facts the idea that with the

consumers being more aware of their energy consumption pattern in real time and with other

subtle prodding techniques, they (the consumers) could adjust their consumption pattern to show

a more environmentally friendly attitude in terms of consumption. This has led to the

development of a metering infrastructure that has seen an increase in associated technology like

smart meters [27, 28], energy meters [29-31] and human computer interactive (HCI) devices [32-

34] which inform users on their consumption profile, carbon emissions, efficiency of

consumption etc. Furthermore, there has been the introduction of demand side management

(DSM) technique like dynamic pricing (DP) [35-37], time of use pricing (ToU) [38], time of day

pricing (ToD), demand response (DR) [39-42] etc. Additional initiatives have seen the increase

in more energy efficient electrical devices like light bulbs, refrigerators, entertainment devices

etc. The interaction between the EMS and the smart home is shown in the Figure 3-1. These

various sub-components of the smart grid are discussed subsequently.

ENERGY MANAGEMENT

SYSTEM

ENERGY GENERATOR

APPLIANCES

SMART METER

ENERGY STORAGE

Figure 3-1: Energy management system representation

3.1. Smart meters

These are energy meters fitted with electronic components that enable the meter to produce very

time specific reports to the consumer and the distributor the advantage of which is to enable the

“prosumer” actually improve on their power consumption behaviours and contribute their own

quota to making the grid more efficient as well as improve grid stability and security. They form

a conspicuous part of the advanced metering infrastructure (AMI) and are fitted with

communication equipment that enables a lot of flexibility with the use and control of power

supply by the consumer. Smart meters support data reporting and registration, send messages to

the consumer, allow for remote supply control by the consumer and accommodate different

tariffs as well as support credit and pre-payment modes [43].

3.2. Demand side management (DSM)

DSM forms an integral component of the energy management system (EMS) as it basically seeks

to influence the consumer consumption pattern subtly through such means as DP, HCI devices

etc. In [33], a persuasive smart energy management system (PSEMS) was developed to act as an

intermediary between prepaid meters and the consumer distribution board. The aim of this

DSM/HCI component is to provide electricity consumers control over how much they spend on

electricity on daily basis. Though such a scheme was applied in SSA, it has immense potentials

in the developed world since existing smart meters and HCI devices merely inform the

consumers rather than giving them control over how much they could spend on electricity.

3.3. Energy efficiency

In a report by the IEA, energy providers are opined to be a major driver in ensuring efficiency

limits is met. For example, in meeting the energy efficiency obligations (EEO), Efficientia a

subsidiary of CEMIG (the Brazilian electricity distribution company) is obliged to spend about

0.05% of annual revenues on efficiency projects. Similarly, HEPA SpA provides free

consultancy services to large industrial operators in the area of energy measurement and

valuation which is aimed at helping them reduce energy wastage while in China; a government

policy mandates regions to maintain a 0.3% reduction in peak demand of preceding year.

Similarly, the incorporation of smart devices for lighting and carbon limits also enforces

efficiency from consumers and buildings.

3.4. Feed in Tariff (FiT)

The feed-in Tariff (FiT) system is one of the most lucrative incentives “prosumers” stand to gain

from since the smart grid is aimed at providing more reliable and cheaper power supply to

“prosumers”. The feed in tariff is the extra included in the deal. You don’t just get cheaper

power, you also get paid when you generate more power than you “prosume” (the process of

consuming energy smartly and efficiently). The extra generated energy by whatever means,

usually solar, entitles the “prosumer” to some payment by the utility company. This is one way

that the smart grid integrates the “prosumer” and makes the “prosumer” better off than a

consumer. In a study, feed-in tariffs showed a five percent reduction on the demand side and had

a potential to cause a 7-15% reduction in the local marginal price of electricity.

3.5. Energy storage

Storage is an important component of the emerging smart grid as it provides a backup in the

event of grid failure to sensitive sectors like healthcare, communications, defence etc. While the

conventional idea of storage refers to batteries etc., consumers in a smart grid scenario could be

classified as storage (if they participate in a demand response (DR)) scenario. The idea of this

flexible storage is to be able to dispatch these remotely controllable loads through smart

thermostats that enable them to be put on line and off line within a short time based on the real

time demand. This way peak demand is shaved (adjusted accordingly) without the need for

additional generation capacity.

3.6. Plug in electric vehicles

The plug-in electric vehicle (PHEV) offers another exciting challenge to the envisioned smart

grid. With improved storage technology and growing investments in alternative fuels for

vehicles, PHEVs are gradually gaining momentum in terms of purchase. The current projection

for the demand of EVs by 2050 is enormous as the technology is expected to experience high

demand in all parts of the world. The Figure 3-2 gives a graphic representation of the projected

demand.

Figure 3-3: Projected worldwide sales for EVs

4. Standards and regulations

Interoperability plays a crucial role in the success of the smart grid. With a myriad of problems

to be solved and an increased growth in solutions all aimed at ensuring its stability, there is the

need for standards that will allow for solutions to operate and co-exist harmoniously without

detriments to the smart grid. Furthermore, “grid umpires” are needed that ensure the protection

of rights of the consumers as well as the suppliers. It is worth nothing that there does not exist

any code known as a smart grid code. This is because the smart grid is a collection of different

solutions all lumped together to improve the flexibility of the traditional grid. However, different

regulations and standards do exist that regulate the operations of the sub-blocks and provide for

interoperability. Bodies such as the United States National Electric Regulatory Commission

(NERC), Institute of Electrical and Electronics Engineers (IEEE), International Electrotechnical

Commission (IEC) etc. do regulate from time to time these existing standards, anticipate

future/likely problems and carefully evolve new standards to regulate such. According to [44,

45], the different standards were classified into six groups. The Tables 4-1 – 4-4 gives a highlight

of some of these standards under their main classification and a brief description.

Table 4-1: Substation protection and automationS/n Standard Brief description1 IEC 60870-5 Standard for “telecontrol equipment and systems with coded bit serial data

monitoring and controlling geographically widespread processes” [46]2 IEC/IEEE 60255-24 “defines a format for files containing transient waveform and event data

collected from power systems or power system models” [47]3 IEC 61850 Standards for “Communication network and systems in substations” [48-51]4 IEC 61850 Ed 2.0 Standards for “Communication networks and systems for power utility

automation” [52]5 IEC 61850-7-410 Standards for “Hydro-electric plant – communication for control and

monitoring” [52]6 IEC 61850-7-420 Standards “LNs for Distributed Energy Resources” [52]7 IEC 61850-7-5xx “Standard for application guides” [52]8 IEC 61850-90-1 “Standard for Communication between substations” [52]9 IEC 61850-90-3 Standard for “condition monitoring” [52]10 IEC 61850-90-5 Standard for “Synchrophasor communication” [52]11 IEC 61869 “Standard for Instrument Transformers” [52-54]12 IEC 61869-9 Standard for “Digital Interface for Instrument Transformers” [52]13 IEC 61869-13 Standard for “Standalone Merging Unit” [52]14 IEC 62271 “Standard for High-voltage switchgear and control gear” [52, 55-58]15 IEC 62271-3 Standards “Digital interfaces based on IEC61850” [52]16 IEC 62439-3 “Standards for High availability automation networks” [52, 59, 60]

Table 4-2: Wide Area Situation Awareness (WASA)IEEE std C37.118-2005

“Standard for Synchrophasors for Power Systems equipment measurement data” [61, 62]

IEC 61850-90-5 Standards for ”Transmit Synchrophasors information”IEEE std C37.242 Standards for “Synchronization, Calibration, Testing, and

Installation of PMU for Power System Protection and Control” [63]IEEE std C37.244 Standards for “Phasor Data Concentrator (PDC) Requirements for

Power System Protection, Control, and Monitoring” [64]

Table 4-3: Interconnection of distributed energy resourcesIEEE std 1547 “Standard for Interconnecting Distributed Resources with Electric Power

Systems” [65-68]IEC 61850-7-420

This the standard for “basic communication structure - Distributed energyresources logical nodes” [69-71]

IEC 61400 This the “Standard for Wind turbines”IEC 61400-25 This is the standard of “Communications for monitoring and control of

wind power plants” [72-75]

Table 4-4: Time synchronizationIEEE 1588 This is the standard for “Synchronization over data networks”. This standard

describes a protocol facilitating precise synchronization of clocks in measurement and control systems [76, 77].

IEEE std C37.238

This standard is intended primarily to facilitate the adoption of IEEE Std 1588-2008 for power system applications synchronization that require a high precision time [78, 79].

Table 4-5: Cyber securityIEC 62351 This is a “Standard for Power systems management and associated

information exchange - Data and communications security” [52, 80-82].IEEE std 1686

This is a “Standard for substation intelligent electronic Devices (IED) cyber security capabilities” [52, 83, 84]

IEC 61850-90-5

“This is a standard for the design of electrical substation automation” [85, 86]

Table 4-6: Other relevant standardsIEC 61970 This is the “Standard for Energy management system application program

interface (EMS-API)” [87-89]IEC 61968 This is the “Standard for Application integration at electric utilities - System

interfaces for distribution management” [90-92]

5. Localized smart grid initiatives

The growth of the smart grid notwithstanding, there appears to be a disconnect between solutions

proffered for the developed economies compared to solutions for the developing economies. For

example, the concept of dynamic pricing lacks locus in SSA and even in most parts of SEA

owing to the poor electricity network in such regions. Similarly, the introduction of HCI devices

and other EMS schemes may lack full utilization owing to the low level illiteracy in these

regions. Due to this technical lacuna, it becomes imperative that smart grid solutions be localized

to match the terrain and suit the people of these regions. In assisting off grid medium income

dwellers manage their solar powered inverter systems, [93] proposed an intelligent load manager.

This initiative localizes the management of embedded generators and load profile dispatching for

demand side management in the developed economies to suit SSA and provide some optimal

comfort in terms of dispatch. Similarly, [33] proposed a persuasive smart energy management

system (PSEMS) for a grid connected house with grid interruptions in SSA. This device localizes

the functions of the smart meters by influencing consumers’ preferences on the prepaid meter. It

furthers the responsibilities of the smart meter by ensuring that the user is in control of how

much electricity should be consumed on a daily basis – a function currently lacking in smart

meters. The Millennium Development Goal (MDGs) was launched in 2000 with the aim of

fighting poverty [94]. In other for these goals to be achieved access to energy services were

essential in the area of social and economic development [95]. Emphasizing the need of energy

in achieving socio-economic development, Sustainable Energy for All (SE4ALL) project was

declared in 2014. SE4ALL is focused on ensuring universal access to energy, increasing energy

efficiency and the use of renewable energy around the globe by 2030. The initiative is a

partnership between United Nations and World Bank with other stakeholders like private sectors,

civil societies, financial institutions and leaders from both developed and developing countries

[96]. This project aims at solving the major challenges in our time which are Poverty and climate

change. In other to achieve these goals, modern technologies are applied in micro-hydro power,

solar photovoltaic systems, use of biomass efficiently and modernizing cooking fuels. The main

challenge to the project is generating funds in low-income countries to increase energy

production and effectiveness of off-grid technologies [97].

In view of this, the World Bank is initiating a program that will bring the majority of the

population in Bangladesh under “Rural electrification and Renewable Energy Systems” project.

The project aims at subsidizing the cost of building solar energy systems. Based on micro

finance system, rural based PV systems are provided at subsidized prices by companies like

Grameen Shakti. Also, in India another program has commenced to replace about five million

water pumps running on diesel to solar energy. The solar project is aimed at producing 700 to

2100 GW of electricity. Sustainable consumer programs are established in India to encourage

people to install solar system at homes. An example is banks giving loans to individual for the

installation of solar homes systems [98]. Moreover, in Brazil the motivation for smart grid has

made the government to come up with policies and regulations to help in the program’s

implementation. Some of these regulations are “smart metering guidelines, Access guidelines for

mini and micro distributed system, Mandatory implementation Geographical information system

and Utilization of the distribution system to transport digital signals [99].” These are just a few

of such initiatives necessary to bridge this growing technical divide between energy solutions for

the developed economies and the developing ones.

6. Smart grid status, its interdependence and growing trend

The smart grid has come to stay. There is no doubt that there is the need to reduce the effect of

carbon emissions in the environment and achieve some form of sustainability in the ecosystem.

However, there are growing concerns concerning the issues of privacy since data mining is at the

heart of the smart grid system. These fears become more pronounced as cyber terrorism gains

momentum. With lots of consumer information being transmitted, there is the possibility of data

thefts. These threats notwithstanding, research is on-going to provide a more resilient grid that

would ensure data privacy. Furthermore, there seem to exist this interdependence between the

smart grid growth and the growth of the renewable energy sector as there is no doubt that the

progress in exploitation of RES provides a platform for the full realization of the smart grid. Due

to advancements in technology and implementation of “smart” policies around the world, there

has been yearly rise of 25% of energy produce from Photovoltaic (PV) for the past ten years with

the highest of 45% in 2005. In 2005, PV added 1,727 MW of power to the world generating

capacity with 833MW, 353MW and 153MW generated in Japan, Germany and U.S respectively

[100]. In Europe the overall renewable energy was increased by 1.1% of the total energy

consumption from 2011 to 2012. In the area of wind energy, 12,086 MW of power was added in

2012 matching the projected value. One of the major contributing factors to the rise is as a result

of the sudden increment in the price of gas during this period. Considering the area of PV in

Europe, which was the major focus of PV in 2012 around the globe, it accounted for about 58%

of the world generated PV power of 28.9 GW. Source from Renewable Energy- statistics in

Germany shows that 7,604MW of power was added to the national grid in the year 2012

increasing the country’s PV capacity to 32,643MW [101].

Over the past decade the increase of renewables has been impressive following the rise in the

total energy capacity (excluding large hydro) from 85 GW in 2004 to 560 GW in 2013. The total

installed capacity was increased from 48 GW to 318 GW and 2.6 GW to 139 GW for Wind and

PV generation respectively with in the same period. The Chart below shows the addition of

renewable energy from 2004 to 2013 [102].

Figure 6-1: Renewable energy capacity addition for selected countries and regions [102]

7. Conclusion

This report has provided a thorough overview of the smart grid showing its subsystems and the

complexities involved. The standards which form a very important core in its operations have

also been listed while several regulatory bodies involved in harmonizing the smart grid

operations have been mentioned. As a complex system made up of more complex subsystems,

the smart grid bases its operation and seamless integration of component modules on

interoperability which ensures there is a common platform that can accommodate all its

components.

References

[1] M. S. Adaramola, “Viability of grid-connected solar PV energy system in Jos, Nigeria,” International Journal of Electrical Power & Energy Systems, vol. 61, pp. 64-69, 10/2014, 2014.

[2] K. Kaygusuz, “Energy for sustainable development: A case of developing countries,” Renewable and Sustainable Energy Reviews, vol. 16, pp. 1116-1126, 2/2012, 2012.

[3] M. O. Oseni, “Improving households’ access to electricity and energy consumption pattern in Nigeria: Renewable energy alternative,” Renewable and Sustainable Energy Reviews, vol. 16, pp. 3967-3974, 8/2012, 2012.

[4] S. O. Oyedepo, “Towards achieving energy for sustainable development in Nigeria,” Renewable and Sustainable Energy Reviews, vol. 34, pp. 255-272, 06/2014, 2014.

[5] R. Paleta, A. Pina, and C. A. Silva, “Remote Autonomous Energy Systems Project: Towards sustainability in developing countries,” Energy, vol. 48, no. 1, pp. 431-439, 2014/12/22/20:22:51.

[6] T. Sesan, “Navigating the limitations of energy poverty: Lessons from the promotion of improved cooking technologies in Kenya,” Energy Policy, vol. 47, pp. 202-210, 2014/09/19/14:28:09.

[7] October 17, 2015; http://www.indexmundi.com/facts/indicators/EG.ELC.ACCS.ZS/compare#country=br:cn:eu:in:id:my:oe:zg:us.

[8] October 17, 2015; http://www.indexmundi.com/facts/indicators/EG.USE.ELEC.KH.PC/compare#country=br:cn:eu:in:id:my:oe:zg:us.

[9] D. Sarvapali, V. Perukrishnen, R. Alex et al., “Putting the ‘smarts’ into the smart grid: A Grand challenge for Artificial Intelligence,” Communication of the ACM, 2012.

[10] C. Fant, C. Adam Schlosser, and K. Strzepek, “The impact of climate change on wind and solar resources in southern Africa,” Applied Energy, 2015/04/30/01:42:43.

[11] D. Mentis, S. Hermann, M. Howells et al., “Assessing the technical wind energy potential in Africa a GIS-based approach,” Renewable Energy, vol. 83, pp. 110-125, 2015/04/30/01:42:31.

[12] F. Wang, L. Bai, J. Fletcher et al., “Development of small domestic wind turbine with scoop and prediction of its annual power output,” Renewable Energy, vol. 33, no. 7, pp. 1637-1651, 2015/04/30/01:42:34, 2008.

[13] D. Pudjianto, C. Ramsay, and G. Strbac, "Micro-grids and Virtual Power plants: Concepts to support the integration of Distributed Energy Resources."

[14] October 10, 2013; http://energy.gov.ng.[15] C. G. Monyei, “Modelling of a virtual power plant for Independence hall lighting

system,” Electrical and Electronic Engineering, University of Ibadan, Ibadan, 2014.[16] October 12, 2013; http://www.iec.ch/smartenergy/downloads/.[17] K. Bhaskar, and S. N. Singh, “AWNN-Assisted Wind Power Forecasting Using Feed-

Forward Neural Network,” IEEE Transactions on Sustainable Energy, vol. 3, no. 2, pp. 306-315, 2015/05/02/16:20:22.

[18] H. Liu, C. Chen, H.-q. Tian et al., “A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks,” Renewable Energy, vol. 48, pp. 545-556, 2015/04/30/01:01:42.

[19] K. Chen, and J. Yu, “Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach,” Applied Energy, vol. 113, pp. 690-705, 2015/04/30/01:02:15.

[20] V. Bertrand, B. Dequiedt, and E. Le Cadre, “Biomass for electricity in the EU-27: Potential demand, CO2 abatements and breakeven prices for co-firing,” Energy Policy, vol. 73, pp. 631-644, 2015/10/20/21:06:17.

[21] W. S. Ho, H. Hashim, and J. S. Lim, “Integrated biomass and solar town concept for a smart eco-village in Iskandar Malaysia (IM),” Renewable Energy, vol. 69, pp. 190-201, 2015/10/20/21:06:11.

[22] S. Moore, V. Durant, and W. E. Mabee, “Determining appropriate feed-in tariff rates to promote biomass-to-electricity generation in Eastern Ontario, Canada,” Energy Policy, vol. 63, pp. 607-613, 2015/10/20/21:06:14.

[23] D. Atsu, E. O. Agyemang, and S. A. K. Tsike, “Solar electricity development and policy support in Ghana,” Renewable and Sustainable Energy Reviews, vol. 53, pp. 792-800, 2015/10/20/21:06:23.

[24] I. Ganesh, “Solar fuels vis-à-vis electricity generation from sunlight: The current state-of-the-art (a review),” Renewable and Sustainable Energy Reviews, vol. 44, pp. 904-932, 2015/10/20/21:06:20.

[25] A. F. Sherwani, J. A. Usmani, and Varun, “Life cycle assessment of solar PV based electricity generation systems: A review,” Renewable and Sustainable Energy Reviews, vol. 14, no. 1, pp. 540-544, 2015/10/20/21:06:26.

[26] G. Chalkiadakis, V. Robu, R. Kota et al., "Cooperatives of distributed energy resources for efficient virtual power plants." pp. 787-794.

[27] Y. Lei, C. Xu, Z. Junshan et al., “Cost-Effective and Privacy-Preserving Energy Management for Smart Meters,” Smart Grid, IEEE Transactions on, vol. 6, no. 1, pp. 486-495.

[28] K. Samarakoon, J. Ekanayake, and N. Jenkins, “Investigation of Domestic Load Control to Provide Primary Frequency Response Using Smart Meters,” Smart Grid, IEEE Transactions on, vol. 3, no. 1, pp. 282-292.

[29] A. Arif, M. Al-Hussain, N. Al-Mutairi et al., "Experimental study and design of smart energy meter for the smart grid." pp. 515-520.

[30] H. Hongtao, W. Lei, Z. Jiangtao et al., "Calibration method for digital energy meters in digital substations." pp. 261-262.

[31] V. Snram, S. A. Nivass, and C. Selvam, "Bi-directional energy meters and remote monitoring of energy nodes using LonWorks technology." pp. 536-539.

[32] C. Belley, S. Gaboury, B. Bouchard et al., “Nonintrusive system for assistance and guidance in smart homes based on electrical devices identification,” Expert Systems with Applications, vol. 42, no. 19, pp. 6552-6577.

[33] A. S. O. Ogunjuyigbe, C. G. Monyei, and T. R. Ayodele, “Price based demand side management: A persuasive smart energy management system for low/medium income earners,” Sustainable Cities and Society, vol. 17, pp. 80-94.

[34] Y. Zhang, and P.-L. P. Rau, “Playing with multiple wearable devices: Exploring the influence of display, motion and gender,” Computers in Human Behavior, vol. 50, pp. 148-158.

[35] G. Du, W. Lin, C. Sun et al., “Residential electricity consumption after the reform of tiered pricing for household electricity in China,” Applied Energy, vol. 157, pp. 276-283.

[36] Y. He, and J. Zhang, “Real-time electricity pricing mechanism in China based on system dynamics,” Energy Conversion and Management, vol. 94, pp. 394-405.

[37] Z. Hu, J.-h. Kim, J. Wang et al., “Review of dynamic pricing programs in the U.S. and Europe: Status quo and policy recommendations,” Renewable and Sustainable Energy Reviews, vol. 42, pp. 743-751.

[38] Y. Wang, and L. Li, “Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities,” Applied Energy, vol. 149, pp. 89-103.

[39] D.-c. Gao, Y. Sun, and Y. Lu, “A robust demand response control of commercial buildings for smart grid under load prediction uncertainty,” Energy, vol. 93, Part 1, pp. 275-283.

[40] Y. Liu, J. T. Holzer, and M. C. Ferris, “Extending the bidding format to promote demand response,” Energy Policy, vol. 86, pp. 82-92.

[41] H. Safamehr, and A. Rahimi-Kian, “A cost-efficient and reliable energy management of a micro-grid using intelligent demand-response program,” Energy, vol. 91, pp. 283-293.

[42] J. Yang, G. Zhang, and K. Ma, “A nonlinear control method for price-based demand response program in smart grid,” International Journal of Electrical Power & Energy Systems, vol. 74, pp. 322-328.

[43] October 20, 2015; http://www.decc.gov.uk/en/contents/cms/what_we_do/uk_supply/network/smart_grid/smart_grid.aspx.

[44] M. G. Kanabar, I. Voloh, and D. McGinn, "A review of smart grid standards for protection, control, and monitoring applications." pp. 281-289.

[45] M. G. Kanabar, I. Voloh, and D. McGinn, "Reviewing smart grid standards for protection, control, and monitoring applications." pp. 1-8.

[46] IEC 60870-5-101:Telecontrol equipment and systems – Part 5 -101:Transmission protocols –Companion standard for basic telecontrol tasks, 2003.

[47] IEC 60255-24:2013:Measuring relays and protection equipment - Part 24: Common format for transient data exchange (COMTRADE) for power systems, 2013.

[48] “IEEE Unapproved Draft Standard for Exchanging Information between networks Implementing IEC 61850 and IEEE Std 1815(TM)(Distributed Network Protocol - DNP3),” IEEE P1815.1/D7.00, September 2015, pp. 1-355.

[49] “IEEE Draft Standard for Exchanging Information Between Networks Implementing IEC 61850 and IEEE Std 1815 (Distributed Network Protocol - DNP3),” IEEE P1815.1/D4.00, June 2012, pp. 1-283.

[50] D. Della Giustina, P. Ferrari, A. Flammini et al., “Automation of Distribution Grids With IEC 61850: A First Approach Using Broadband Power Line Communication,” Instrumentation and Measurement, IEEE Transactions on, vol. 62, no. 9, pp. 2372-2383.

[51] S. Matsuda, Y. Watabe, I. I. Asrizal et al., "Issues overcome in the design and application of IEC 61850-compliant substation automation systems." pp. 198-202.

[52] M. Kanabar, I. Voloh, and D. McGinn, "Reviewing Smart Grid Standards for Protection, Control, and Monitoring Applications."

[53] V. Bhardwaj, M. I. Singh, S. Pardeshi et al., "A review on various standards for digital substation." pp. 1-5.

[54] I. Patru, V. Voicu, I. Mihalcea et al., "In phase control system with applications for assessing the transient response in capacitive instrument transformers." pp. 1-5.

[55] “IEEE Draft Standard Test Procedure for AC High-Voltage Circuit Breakers Rated on a Symmetrical Current Basis Amendment 2: To Change the Description of Transient Recovery Voltage for Harmonization with IEC 62271-100,” IEEE PC37.09b/D6, September 2010, pp. 1-14.

[56] “IEEE/IEC High-voltage switchgear and controlgear - Part 111: Automatic circuit reclosers and fault interrupters for alternating current systems up to 38 kV,” IEEE Std C37.60-2012, pp. 1-134.

[57] “IEEE Standard for Rating Structure for AC High-Voltage Circuit Breakers Rated on a Symmetrical Current Basis Amendment 2: To Change the Description of Transient Recovery Voltage for Harmonization with IEC 62271-100,” IEEE Std C37.04b-2008 (Amendment to IEEE Std C37.04-1999), pp. c1-45, 2008.

[58] D. Penkov, C. Vollet, C. Durand et al., "IEC standard high voltage circuit-breakers: Practical guidelines for overvoltage protection in generator applications." pp. 1-12.

[59] G. Hao, and P. Crossley, "Time synchronization (IEEE 1588) and seamless communication redundancy (IEC 62439-3) techniques for Smart Grid Substations." pp. 1-6.

[60] C. Hoga, "Seamless communication redundancy of IEC 62439." pp. 489-494.[61] “IEEE Standard for Synchrophasor Data Transfer for Power Systems,” IEEE Std

C37.118.2-2011 (Revision of IEEE Std C37.118-2005), pp. 1-53.[62] “IEEE Standard for Synchrophasor Measurements for Power Systems,” IEEE Std

C37.118.1-2011 (Revision of IEEE Std C37.118-2005), pp. 1-61.[63] “IEEE Guide for Synchronization, Calibration, Testing, and Installation of Phasor

Measurement Units (PMUs) for Power System Protection and Control,” IEEE Std C37.242-2013, pp. 1-107.

[64] “IEEE Guide for Phasor Data Concentrator Requirements for Power System Protection, Control, andMonitoring,” IEEE Std C37.244-2013, pp. 1-65.

[65] “IEEE Recommended Practice for Interconnecting Distributed Resources with Electric Power Systems Distribution Secondary Networks,” IEEE Std 1547.6-2011, pp. 1-38.

[66] “Ieee standard conformance test procedures for equipment interconnecting distributed resources with electric power systems - amendment 1,” IEEE Std 1547.1a-2015 (Amendment to IEEE Std 1547.1-2005), pp. 1-27.

[67] “IEEE Standard Conformance Test Procedures for Equipment Interconnecting Distributed Resources with Electric Power Systems,” IEEE Std 1547.1-2005, pp. 1-62, 2005.

[68] “IEEE Application Guide for IEEE Std 1547(TM), IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems,” IEEE Std 1547.2-2008, pp. 1-217, 2009.

[69] F. M. Cleveland, "IEC 61850-7-420 communications standard for distributed energy resources (DER)." pp. 1-4.

[70] N. Honeth, Y. Wu, N. Etherden et al., "Application of the IEC 61850-7-420 data model on a Hybrid Renewable Energy System." pp. 1-6.

[71] T. S. Ustun, C. Ozansoy, and A. Zayegh, "Extending IEC 61850-7-420 for distributed generators with fault current limiters." pp. 1-8.

[72] M. A. Ahmed, Y. Won-Hyuk, and K. Young-Chon, "OPNET Simulation Model for Small Scale Wind Power Farm Monitoring Based on IEC 61400-25." pp. 1-5.

[73] L. Jung-Hoon, S. Min-Jae, K. Gwan-Su et al., "IEC 61400-25 interface using MMS and web service for remote supervisory control at wind power plants." pp. 2719-2723.

[74] S. Min-Jae, K. Tae-o, and L. Hong-Hee, "Implementation of web services based on IEC 61400-25 for wind power plants." pp. 2082-2086.

[75] N. Trinh Hoang, A. Prinz, T. Friiso et al., "Smart grid for offshore wind farms: Towards an information model based on the IEC 61400-25 standard." pp. 1-6.

[76] “IEEE Draft Standard Profile for Use of IEEE Std. 1588 Precision Time Protocol in Power System Applications,” IEEE PC37.238/D6, February 2011, pp. 1-67.

[77] “IEC/IEEE Precision Clock Synchronization Protocol for Networked Measurement and Control Systems (Adoption of IEEE Std 1588-2008),” IEC 61588 First edition 2004-09; IEEE 1588, pp. 0_1-156, 2004.

[78] “IEEE Standard Profile for Use of IEEE 1588 Precision Time Protocol in Power System Applications,” IEEE Std C37.238-2011, pp. 1-66.

[79] G. S. Antonova, A. Apostolov, D. Amold et al., "Standard profile for use of IEEE std 1588-2008 precision time protocol (PTP) in power system applications." pp. 322-336.

[80] F. M. Cleveland, "IEC 62351-7: communications and information management technologies -network and system management in power system operations." pp. 1-4.

[81] S. Fries, H. J. Hof, and M. Seewald, "Enhancing IEC 62351 to Improve Security for Energy Automation in Smart Grid Environments." pp. 135-142.

[82] R. Tawde, A. Nivangune, and M. Sankhe, "Cyber security in smart grid SCADA automation systems." pp. 1-5.

[83] “IEEE Standard for Intelligent Electronic Devices Cyber Security Capabilities,” IEEE Std 1686-2013 (Revision of IEEE Std 1686-2007), pp. 1-29.

[84] “IEEE Standard for Substation Intelligent Electronic Devices (IEDs) Cyber Security Capabilities,” IEEE Std 1686-2007, pp. 1-22, 2008.

[85] A. Elgargouri, R. Virrankoski, and M. Elmusrati, "IEC 61850 based smart grid security." pp. 2461-2465.

[86] J. Zhang, and C. A. Gunter, “IEC 61850-Communication Networks and Systems in Substations: An Overview of Computer Science,” University of Illinois at Urbana-Champaign, 2015/10/21/09:50:24, 2007.

[87] M. Mao, M. Ding, C. Liuchen et al., "The IEC 61970-based software frame and information integration of EMS for a Multi-Distributed-Generation Microgrid System." pp. 773-776.

[88] Z. Yilin, L. Yan, and S. Jianwei, "IEC 61970 CIM/CIS in power dispatching automation system standard conformance test technology research." pp. 1-4.

[89] S. Zhang, J. Yao, Z. Yang et al., "Implementation of standard IEC 61970 in EMS systems." pp. 114-118 Vol.1.

[90] L. Guangxian, Z. Jianghe, S. Jian et al., "Research on IEC 61968 Standard Oriented Function Framework of Adapter in Smart Distribution Grid." pp. 1061-1065.

[91] X. Jun, S. Dongyuan, L. Yinhong et al., "Study on power system heterogeneous graphics exchange based on IEC 61968 location package and SVG." pp. 1-7.

[92] Y. Nanhua, C. Hui, S. Xudong et al., "Research on IEC 61968 based message design for intelligent operation and maintenance center." pp. 1331-1337.

[93] A. S. O. Ogunjuyigbe, T. R. Ayodele, and C. G. Monyei, “An intelligent load manager for PV powered off-grid residential houses,” Energy for Sustainable Development, vol. 26, pp. 34-42, 2015/03/26/10:31:01.

[94] C. Sagan, Demon-haunted world: science as a candle in the dark: Ballantine Books.[95] V. Modi, S. McDade, D. Lallement et al., “Energy services for the Millennium

Development goals. New York: Energy Sector Management Assistance Programme, United Nations Development Programme,” UN Millennium Project, and World Bank, vol. 200698, 2006.

[96] "Sustainable Energy for All: Improving energy efficiency," 0101/2015, 2015; www.SE4ALL.ORG.

[97] A. Piebalgs, “Delivering sustainable energy for all,” Development Co-operation Report, pp. 77-88, 2015/10/21/11:07:30.

[98] T. Ishtiaque, M. R. Rahman, M. A. R. Sarkar et al., "Sustainable energy for all challenges: Opportunities & best practices in South Asia." pp. 418-424.

[99] K. G. Di Santo, E. Kanashiro, S. G. Di Santo et al., “A review on smart grids and experiences in Brazil,” Renewable and Sustainable Energy Reviews, vol. 52, pp. 1072-1082, 2015/10/21/11:07:36.

[100] D. M. KAMMEN, "The Rise of Renewable Energy," http://rael.berkeley.edu/old_drupal/sites/default/files/Kammen%202006-%20The%20Rise%20of%20Renewable%20Energy.pdf, 2006].

[101] V. Modi, S. McDade, D. Lallement et al., “Energy services for the Millennium Development goals. New York: Energy Sector Management Assistance Programme, United Nations Development Programme,” UN Millennium Project, and World Bank, vol. 200698, 2006.

[102] REN21, "THE FIRST DECADE: 2004 – 2014," http://www.ren21.net/Portals/0/documents/activities/Topical%20Reports/REN21_10yr.pdf, [October 21, 2015, 2014].