Energy Usage and Electricity Load Profile

In Chapter 2, an example was used to illustrate the energy savings from using micro-CHP. Here an example dwelling in the analysis is used for discussion pur- poses. Figure 3.13 shows the energy flow when comparing the reference case and when using an ICE-based micro-CHP in a semi-detached house. The reduction in energy is 13% which is mostly in the form of waste heat reduced.

When micro-CHP systems are adopted by a large number of dwellings, they are bound to have an impact on the UK’s electricity load profile. Analysing the im- pact of wide penetration of micro-CHP on electricity load profile requires scaling up the data available for the limited dwellings analysed here. In order to real- istically scale the behaviour of the demand from the dwellings, diversity factors were included. This was done by shifting the time of the demand, but maintaining the same shape of the demand, hence keeping the total daily electricity demand constant. Assuming that the penetration of micro-CHPs includes adoption in all detached, semi-detached and terrace houses in the UK, which represent around 83% of the dwellings, and assuming that consumers act rationally by employing the cost-minimisation control strategy to operate their micro-CHPs, a new domes- tic demand profile can be constructed.

Figure 3.13: An example of a semi-detached house with ICE micro-CHP

To show the effects of micro-CHPs on the network, a reference profile is needed. In order to do this, three days were chosen from the UK demand snapshot to represent winter, shoulder and summer national load profiles, which were obtained from the Balancing Mechanism Reporting System website [123]. Since this is the national load profile, it consists of domestic, industrial, commercial and other demands. For comparison to be made, the non-domestic elements need to be separated from the total load profile. To get the domestic load profile, the data from the field trials was used. The average demand of each sample dwelling during the three seasons was multiplied with their respective weights to get the total domestic demand. This domestic demand is taken off the total load to get the non-domestic demand. The new profile is formed by summing non-domestic demand and the total new domestic demand of electricity from the grid (with micro-CHPs present). The load profile for the reference case of the UK national load profile and the new

demand for the scenarios with micro-CHPs can be seen in Figures 3.14, 3.15 and

3.16, which represents the winter, shoulder and summer load profiles respectively.

Figure 3.14: Winter load profile for the four micro-CHP technologies with the three pricing scenarios and the reference national load profile

Figure 3.15: Shoulder load profile for the four micro-CHP technologies with the three pricing scenarios and the reference national load profile

Figure 3.16: Summer load profile for the four micro-CHP technologies with the three pricing scenarios and the reference national load profile

For all three seasons, the load reduces the most in the morning and evening where domestic demand tend to be the highest compared with both domestic demand at other times and demand from other sectors, i.e. industrial and commercial. In the morning, people wake up and get ready to leave for work or school [32]. The morning valley in the profile varies in time between seasons. As many of the micro-CHP units are turned on during that time, less electricity is imported from the grid. Also, the excess electricity generated (which is not consumed on-site at that time) is exported. This is more evident in winter compared to the other seasons. In the winter, the load profile as in Figure 3.14, there seem to be a dip in demand for electricity from the grid, early in the morning. This is because heat demand is higher in winter, which causes micro-CHP to generate both heat and electricity when prices are lower and store the heat for the usage in the morning. There might not be sufficient on-site demand at this time and therefore excess electricity is exported. This causes the total load to fall by a considerable amount, roughly a third or less of the total demand.

The later range of time where there is a fall in the total load is when people come back home in the evening and require heating and electricity for preparing dinner, watching television or turning on other electrical appliances [32]. This fall

in the load profile is more prominent during winter and shoulder seasons compared to that in summer. The reason for this is that heat demand is very low during summer. Another obvious peak in the profile is during mid-day for all seasons. This might be due to the fact that heat demand is too small to start the micro-CHP and therefore, electricity demand is met by the grid [32].

The impact of the penetration of different types of micro-CHP technology on the electricity load profile is more prominent than the impact of the different pricing schemes. However, there is some correlation between the pricing scheme and the electricity load profile. Figure 3.17 shows the average half hour electricity RTP for the three seasons. These prices include all the cost components except for the supplier costs and margins, which will vary depending on the scenario used. The general shape of the average price profile across the seasons is similar. However, the electricity prices are higher in summer compared to those in winter and shoulder seasons as shown in Figure 3.17.

0 5 10 15 20 25 30 35 40 45 50 8 10 12 14 16 18 20

Time (half hour)

Real Time Price (p/kWh)

Average half hour electricity prices Winter Shoulder Summer

Figure 3.17: Day cross section of average real time prices for electricity during

imported from the grid. The prices peak at times 12:30 and 17:30 and the overall demand starts to fall during these times. In summer, there is an additional peak at time 20:00. With longer daylight during summer, the surge in demand for lighting occurs around that time. When the price is at the minimum point, at time 15:00, demand for electricity from the grid starts to increase as the cost-minimisation control strategy takes advantage of the lower grid electricity prices.

Overall, the load profile is shifted downwards when there is a high penetration of micro-CHPs, reducing the peak national electricity demand and this is shown in Table 3.3. Results show that peak reduction is highest during the winter season. This corresponds to the fact that more micro-CHP units will be producing elec- tricity, even if the demand for electricity is not present, due to the high demand of heat during winter. In addition, these units also operate for longer periods of time to meet the high demand. Units with higher electrical efficiency enable higher reduction in peak demand due to the ability to generate enough electricity for consumption and also export the excess electricity to the grid. For the micro- CHPs, the fuel cell based systems perform better than the engine based system, with SE based systems performing the worst, even an increase in peak demand during winter.

Table 3.3: Percentage of reduction in peak national electricity demand Peak Load Reduction (%)

Micro-CHP Pricing Schemes

Technology S2 S3 S4 Winter SE -0.62 1.11 -0.73 ICE 11.42 11.5 11.11 PEMFC 13.83 13.96 14.14 SOFC 16.46 16.45 16.81 Shoulder SE 1.04 1.15 1.09 ICE 4.54 4.6 4.54 PEMFC 5.36 5.43 5.36 SOFC 6.03 6.09 6.03 Summer SE 0.44 0.19 0.2 ICE 1.85 3.96 3.95 PEMFC 2.97 5.37 5.36 SOFC 5.04 6.86 5.84

The pricing scenario that best reduces the peak is S3. With S4, the peak reduction is slightly less than S3, but more than S2. However, the difference in pricing is not the main driver of the load reduction, as the outcome of the different pricing scenarios only differ slightly from each other, especially in the winter and shoulder seasons. There are two reasons for this. Firstly, the higher heat demand during these seasons will enable longer operating times of the micro-CHP systems. Sec- ondly, the lower average RTP for electricity means that the spark spread ratio is lower and hence that will be a closer to the AP.

During summer, prices play a more important role in reducing peak demand. The high average electricity RTP during summer causes the peak reduction to differ based on pricing schemes, with S3 and S4 both having higher peak reduction com- pared to S2. For the ICE based micro-CHP systems, the RTP scenarios enabled more than double the peak reduction of the AP scenario and hence is a viable tool in peak load reduction.