Energy consumption is increasingly becoming the hot topic of the twentieth century for politicians, engineers and scientists alike. The most recent IPCC report claimed that scientists are 95% certain that humans are the “dominant cause” of global warming since the 1950s (IPCC, 2013). The government has set a target for new domestic houses in the UK to be “zero carbon” by 2016 and new non-domestic buildings by 2019, and it is common knowledge that buildings account for almost 40% of CO₂ emissions within the European Union, so it is necessary to consider how buildings can be made more efficient to reduce overall carbon emissions within the buildings sector (The European Parliament and the Council of the European Union, 2010). Globally it accounts for 40-50% of natural resource use, 20% of water use, 30-40% of energy use and around a third of CO₂ emissions (UK Green Building Council, 2014) therefore it is of no surprise that a key element in the route towards a zero carbon future requires extensive research and understanding of energy consumption within new and existing buildings.

One of the key scenarios of this project was to address a future scenario of a move towards progressive levels of electrification that might be driven by a renewable grid such as the innovative NINEs project that SSE are developing out in the Shetland Isles. In this project the electricity network is controlled more effectively through demand side management to encourage the use of renewable energy technologies to play a bigger part in the Shetland Island communities’ energy need. In this scenario electric storage water heaters and boilers are used to provide heating and hot water as well as small power and lighting loads with the provision of a 1MW storage battery. This also is in line with the Smart Grid technologies as customers are encouraged to use energy at different times of the day, where possible, to reduce the overall peak demands. If successful this could pave a way for future cities and communities to adopt a similar approach and provide a higher demand for green electricity (Scottish & Southern Energy, 2014).

Electric vehicles (EVs) are considered to be the most prominent solutions towards achieving a decrease of petroleum dependence as well as reducing emitted greenhouse gases and pollutants on the road. Nevertheless, the transition to EVs is dependent on the status that the transportation organisations will be able to integrate and promote this new technology. (Electric Vehicles: charged with potential , 2010)

Electric vehicles operate solely on electricity. They are driven by an electric motor powered by rechargeable battery packs. EVs present numerous benefits over conventionally fuelled vehicles, such as:

•Energy efficiency: Electric vehicles convert about 59–62% of the electrical energy from the grid to power at the wheels—conventional gasoline vehicles only convert about 17–21% of the energy stored in gasoline to power at the wheels.

•Environmental friendly: EVs produce no pollutants at all, however it can be argued that they shift the emissions from the road to the power generation stations.

•Enhanced performance: Electric motors provide quiet, smooth operation and stronger acceleration and require less maintenance than internal combustion engines.

•Reduced energy dependency: (Samaras & Meisterling, 2008)

EVs, on the other hand, face substantial battery-associated challenges:

•Limited driving range: Most EVs can only go for approximately 100–200 miles before they need to be recharged while conventional cars can go over 300 miles before they need to be refuelled.

•Recharging time: A full recharge of the battery pack can take up 4 hours for fast charge and 8 hours for slow charge. In the event of a rapid charging rate it will charge from 0 to 80% capacity within a 30 min period approximately.

•Battery cost: The bulky battery packs are expensive and need to be substituted multiple times.(Canis, 2013)

Nevertheless, scientists are occupied on developing techniques towards enhancing the current state of battery technologies in order to increase driving range and to further reduce recharging time, weightiness, and price. These factors will be the ones that will define the future of EVs in the long run.(IEA, 2013)

After diversity maximum demand (ADMD) is an index that industry uses to determine what size to make electricity wires.  For this project, the ADMD was calculated by adding the maximum load at each time interval to compose a profile which represented the estate. The maximum load in the resultant graph is the ADMD value. The diversity of the index is taken into consideration with the composition of the estate.

The process that is being followed in order to calculate the ADMD values is as follows:

The ADMD is being multiplied by a diversity factor (DF) and this factor causes an increase in the demand per house as the size of the set is being reduced. The formula which is being widely used to this extent is given below.

Where,

MD = Maximum Demand

DF = Diversity Factor

ADMD = After Diversity Maximum Demand

N = Number of Customers

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