Daños

The cost-minimisation model yields the daily cost for all the dwellings analysed. From this data, the annual cost can be found and this annual cost can be compared with the reference annual cost to identify the annual saving. The distribution of the annual savings for the dwellings with the four technologies and three pricing schemes are shown in Figure 3.10.

The annual savings are influenced more by the type of micro-CHP than the pricing scheme. The distribution of the dwellings according to their annual savings shows that the dwellings saved the most with SOFC based micro-CHPs, followed by PEMFC, and ICE and the least with SE based systems. Within the engine based

<1 1−2 2−3 3−4 4−5 >5 0 10 20 30 40 50 60 70 SE Percentage of dwellings (%) <1 1−2 2−3 3−4 4−5 >5 0 5 10 15 20 25 30 35 40 ICE

Range of annual saving (£ ’00)

<1 1−2 2−3 3−4 4−5 >5 0 5 10 15 20 25 30 35 40 45 PEMFC <1 1−2 2−3 3−4 4−5 >5 0 5 10 15 20 25 30 35 40 45

Range of annual saving (£ ’00)

SOFC

AP (S2)

RTP with Supplier Costs and Margins of 15% (S3) RTP with Supplier Costs and Margins of 20% (S4)

Figure 3.9: Distribution of the annual savings of the sample dwellings for the different types of micro-CHP under average and real time pricing in scenarios

2, 3 and 4 (S2, S3, S4).

micro-CHP, saving achieved with a SE is much lower than that with an ICE. The higher electrical efficiency of the fuel cell based systems is the main contributor to higher savings across the dwellings.

When comparing the different pricing scenarios, S3 performed the best with a higher percentage of dwellings achieving high annual savings. This is followed by S4 and lastly S2. With the fuel cell based systems under S3, around 10% of the dwellings were able to save more than £500 a year. The maximum savings for dwellings employing ICE based systems did not exceed £500 and dwellings with SE based micro-CHPs did not save more than £400.

The effect of the type of dwelling on the annual saving achieved were investigated and this is illustrated in Figure 3.11. Here the effect of ICE on the 28 dwellings is shown and the trend is similar for all the other types of micro-CHP. For the ICE, results show that the dwellings with higher heat demand tend to achieve higher

Figure 3.10: Distribution of the annual savings of the sample dwellings for the different types of micro-CHP under average and real time pricing in scenarios

2, 3 and 4 (S2, S3, S4).

savings. This generally corresponds to older and larger dwellings. In Figure 3.11, it is clear that the savings achieved by detached and terrace houses are positively correlated to heat demand. The dwellings that have the best profiles for micro- CHP are the ones with large heat and electricity demand as well as a coincidence ratio that is close to the heat to electricity ratio of micro-CHP technology used. Although a high ratio of electricity to heat is important, high electricity demand also contributes positively to the annual savings achieved [53]. With the semi- detached houses, the savings have a strong positive correlation with the amount of electricity demanded, as shown in Figure 3.11. There were three dwellings (semi- detached houses 1 and 2 as well as terrace house 1) with a high coincidence ratio, but had relatively low savings due to the low annual electricity demand (all below 1000 kWh). This resulted in lower savings, especially in scenario S2. However, these dwellings have proportionally higher savings when using RTP, in S3 and S4. The results presented here further emphasise the notion that there is no ‘one size that fits all’ for the case of micro-CHPs. There are other factors that play important roles in determining the amount of the saving that can be achieved.

1 2 3 4 5 6 7 8 9 10 0 100 200 300 400

Dwellings with increasing heat demand

1 2 3 4 5 6 7 8 9 10 0 100 200 300 400 500

Dwellings with increasing heat demand

Annual Saving (£) Terrace Houses 1 2 3 4 5 6 7 8 0 100 200 300 400 500

Dwellings with increasing electricity demand

Semi−detached Houses

AP (S2)

RTP with Supplier Costs and Margins of 15% (S3) RTP with Supplier Costs and Margins of 20% (S4)

Figure 3.11: Different types of dwellings and their saving with strong corre- lation to heat or electricity demand.

From the data, it was observed that higher savings occur when the u-value7_{, and}

area of the walls, the floor size and number of occupants are high, but the SAP8

value of the buildings is low [32]. These correspond to larger dwellings, with relatively poor insulation and therefore have high heat demand. In terms of the age of the dwellings, highest savings were achieved by dwellings built between 1900 and 1950. On the other hand, dwellings with the highest savings were those with the highest number of occupants and in this sample it is six. The most suitable micro-CHP technology across the dwellings and pricing schemes is the SOFC micro-CHP. This applies to all the dwellings with varying occupancy, even though the overall coincidence ratios vary between the dwellings.

7_{The ‘u-value’ measures how well the heat transfers between the inside and outside of a}

building, which is usually via the walls and windows. A lower ‘u-value’ generally indicates a building with better heat retention[33]

8_{SAP is the Standard Assessment Procedure which is used to evaluate dwellings in the UK.}

With ratings which run from 1 to 100, the higher the value, the more energy efficient the building is[33].

In the analyses above, only operations cost were compared between the different pricing scenarios and the reference cases. It has been assumed that the mainte- nance cost is similar to that of a standard boiler in these scenarios. However, sensitivity analysis in Chapter 4 (Section 4.2.1.3) will take into consideration a range of maintenance cost. It is also vital to know the viability of investment in terms of the capital cost of a micro-CHP that can be afforded by the consumers. This issue will be explored in Section 4.2.2 of Chapter 4.