Introduction

We have been offered the opportunity of applying our methodology to a construction site near to Prestwick airport. The construction site will become the new NATS control building and covers approximately 550 square metres, with a range of land use, from office space and facilities for the workforce in the form of a construction village, through to the new site of the building and associated supply and storage areas for construction materials. We will be applying our methodology to the entire site taking each area into account.

The construction village comprised of 24 modular cabins linked together over two storeys. The modular cabins in the village were of different generations, with one type conforming to current building standards and the other being an older model with a lower specification of insulation.

Aims and objectives

By applying our methodology to the site we hope that we will achieve the following outcomes from this casestudy;

Data collection

We travelled to the Prestwick site and met representatives from the contractor and discussed the project. We were given a great deal of specific information about the site which would allow us to calculate the loads that were present.

For this case study we gathered information about the numbers of workers, the equipment and activities in the cabins, the equipment on site, the proposed schedule of activities and the necessary resources for different phases of building construction.

Energy conservation

The focus of our energy efficiency study will be on the construction village where we will try to reduce energy consumption associated with the workers behaviour and their use of electrical appliances. We reviewed the largest demands of lighting, heating and hot water in the construction village. However, in this all electric environment the dominant loads were lighting and heating. It would be in these areas where we will be able to achieve the greatest reduction in demand.

The heating was controlled by a thermostat or a variable heat output control on the convection heaters. However the thermostat and the heat output controls were often set to the maximum and left switched on even if the office was unoccupied.

All of the lighting was of the fluorescent tube type with two bulbs per luminaire and no reflectors. There were set out in a standard pattern and did not account for the actual use of the space that they were illuminating in the cabin. As a result the lighting was often inappropriate for the space and could be substantially reduced.

The lighting tended to stay on all day despite there often being enough natural light available.

Due to the linking together of the different cabin modules, the lighting that was available was often poorly controlled.

The other loads that made up the rest of the cabins' demand were from general office equipment such as computers, fax machines and a refrigerator in the small canteen on the upper floor.

Define time period

We defined the time period as one day because the data lent itself to daily calculations. If larger timescales are required the daily power demand will be scaled up.

Grid and supply options

The generator is rated for loads up to 250 kVA. Generators should be run at full load whenever possible to maximise their efficiency, because at part load, there will be a drop off in their efficiency.

There are a couple of supply options that were investigated to supplement the electricity from the generator being used in the cabins and on site. These were generation from wind and solar generation in the form of photovoltaic (pv) panels.

Solar

There is potential for pv panels as the site is open without any shadows being cast by the surrounding buildings. However there may be some structural issues with the mounting of the panels on the roofs of the upper storey of the cabins. There must be provision for regular access to the units for maintenance in order to keep the outer surface of the cells free from dust.

We modelled the generating capacity of a pv installation using Merit and found that the power from such an installation would be quite small. With this low output, the price per kWh would be far higher than that from the diesel generators, so the solar installation was discarded.

Wind

Due to the site's location and the proximity of the current NATS building, there are very strict guidelines about the type of equipment that can be placed nearby. Between these stringent regulations and the heath and safety implications of having a wind turbine active on the site, we decided not to pursue this method of supply.

Compare supply and demand profiles

On the site the supply was always equal to the demand with the generator tracking and supplying the load up to its nameplate rating of 250 kVA.

Apply DSM techniques

In this case study we quickly identified that there were limited opportunities to shift loads because the employees had a high priority of use of their equipment. As a result the main DSM technique used in this case study will be the efficient use of energy on site.

We have stopped the methodology here because the two subsequent steps are not applicable to this particular case study.

Investigation of loads

Lighting

Our review of the lighting load proceeded along the following pathways. We initially assessed the use of the office space and standardised the lighting load per unit floor area. We standardised the lighting load at 10 W/m2 , which is at the lower end of the optimum load of 10-12 W/m2 [29]. With the lighting set to this level we then investigated ways in which the lighting could be controlled to operate only on demand.

Once energy conservation had been carried out, education will play a part in the reduction of energy use. Topics such as the connection of energy use to environmental impact can be highlighted along with simple ways to reduce energy consumption. The end result should be a substantial reduction in the energy required to operate the cabins.

From our initial survey the calculated level of lighting for the cabins varied between 1 and 26 W/m2 per day. As part of the energy efficiency measures we changed the level of lighting to 10 W/m2 per day where necessary. In some cases there was an increase in lighting levels to achieve 10 W/m2 , but overall there was an energy saving from a large reduction in lighting levels.

The initial estimation of the energy consumed for the lighting was based on the assumption that all the installed lamps were operating continuously from 08:00hrs until 17:00hrs at their rated loads. The total power drawn was then calculated and the subsequent reduction in electricity use recorded.

With the current lighting patterns and use the daily electricity required was 93.77 kWh. However with the reduction of the lighting levels to the optimum of 10 W/m2 the electricity required has been lowered by 36.06 kWh to 57.71kWh per day. This is a potential saving of 38.5%.

The implications of this reduction in energy use can be translated into economical and environmental benefits regarding fuel use and CO2 emissions.

Heating

Our review of the cabins' heating load proceeded along the following pathways. During our visit to the site we investigated the number and types of heaters per cabin. We hoped to establish better control over the existing heating systems, with the aim of reducing energy expenditure and costs. There were a range of different uses and occupation of the cabins within the construction village, each with correspondingly different heating regimes.

We wished to investigate these reductions based on better control of the heating system. In order to investigate the situation in more detail we modelled one of the cabin modules in ESP-r so that we could get a better understanding of the energy requirements per cabin. ESP-r is a leading building simulation program that helped us to quantify the energy performance of the cabins. This calculated the energy requirements necessary to maintain a constant temperature environment. We ran numerous simulations on the model, varying inputs such as the construction materials, dimensions of the cabin, occupancy period, climate and the internal air temperature. Casual gains from the lighting and occupants were also taken into account in the overall energy balance.

We calculated the energy demand required to maintain the air temperature at 18ºC and 21ºC. We then compared this with the energy demand of the cabins at full load. We defined full load as when all of the heaters were operating with their thermostats set to the maximum. To represent this we calculated the energy demand of the cabin with an air temperature of 30ºC.

As a final step in the process the message of energy conservation and its connection to environmental impact should be reinforced by education in these areas.

We saw from our site visit the patterns of convection heater use. We wished to model possible reductions based on better control of the equipment that was installed in the cabins. We calculated the energy demand required to maintain the air temperature at 18ºC and 21ºC. We then compared this with the energy demand of the cabins at full load. We defined full load as when all of the heaters were operating with their thermostats set to the maximum. To represent this we calculated the energy demand of the cabin with an air temperature of 30ºC.

From the comparison of the above calculations we found that the power consumption with the air temperature controlled at 18ºC and 21ºC compared to 30ºC was reduced by 29% and 14% respectively.

Within our heating scenarios there is a high level of discomfort to the occupants at the start of the day in all of the cabins modelled. This is due to the heating only being operated during the hours of the working day, from 08:00hrs until 17:00hrs. In our model the occupants also have a relatively low clothing level, which is representative of standard office wear.

In order to avoid this high level of discomfort at the start of every day, the heating programme should be changed to start operating for a short period before the office will be occupied at 08:00hrs. An additional benefit of changing the heating program to allow the gradual heating of the cabins will be to help reduce the sharp morning peaks in the demand profile.