Discussion

The advice that is given by the model is based on numbers and calculations that are found by studying literature and the use of other information sources. In some of the calculations or information there are done assumptions or some factors aren’t taken into account. Most of the assumptions and the omission of some factors are discussed in this paragraph.

Energy Service Company

The diagram with the expected total housing costs (see figure 9.15) shows what the influence of the investment in energy techniques can be on the total housing costs for the tenants. This is only possible if a housing corporation is allowed to supply energy for their tenants next to their core business of housing. Without the possibility to supply energy to their tenants, the investment will only have an influence of the total costs of the tenants.

The housing corporation will only pay for the investment and the financial revenues of these investments will directly go to the tenants.

There has to be made a construction which will make sure that the revenues of the investments will go to the housing corporation and indirectly go to the tenants. A possibility

Master Thesis: A Decision Support Model for Implementing Energy Techniques in Residential Areas. Page | 95 could be the set up of an Energy Service Company (ESCO): an independent party that operates and maintains the energy sources and supplies the energy.

Besides the need of a construction, to make it possible for a housing corporation to supply energy towards their tenants and to get paid for this delivery, it is also important that this construction is legally allowed and that it is allowed for a housing corporation to commit their tenants to purchase energy from this ESCO. In this study there isn’t done research in these requirements; it is assumed that it is legally possible for a housing corporation to do this.

Costs of an ESCO

As discussed above there is needed an ESCO, or a comparable construction, that invests in the energy techniques and supplies energy for the neighborhood. The costs that are needed for this ESCO are not taken into account in the model. The only costs that are taken into implementing sustainability and sustainable energy. The past has shown that the continued existence of these subsidies is uncertain. It is not wise to make an investment relying on subsidies. Therefore subsidies are not taken into account in this study; subsidies can be seen as additional investment possibilities. If there will be subsidies for implementing energy heat sources, this could mean that the attractiveness for a housing corporation to invest in these techniques will increase. It would financially be more attractive to invest in these techniques, which will lead to more self-sufficient neighborhood.

Improvement of performance of energy techniques

The costs and revenues of the energy techniques will change in the future. Solar PV cells will for instance have a better performance per m² and the price will approximately reduce. This improvement of performance and reduction on costs isn’t taken into account in this study and model. Most likely the improvement of the techniques and the decrease of the investment costs of the energy techniques will have a positive effect on the attractiveness of investing in renewable energy techniques. So therefore the foresight out of the model can be seen as “worst” scenario; with improvement of techniques and decrease of costs the results could even be more positive.

Gas needed for cooking

The production of warmth and reduction of gas consumption by investing in energy techniques for warmth, leads only to a reduction in gas that is needed for heating (73%) and tap water (23%). Adjustments that are needed to reduce the gas that is needed for cooking

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(4%), e.g. induction or electric cooking, are not taken into account in this model. As the gas that is needed for cooking is a fraction of the total gas consumption, this will not lead to an unrealistic result. An advice on improving this model can be to insert the possibility to invest in these adjustments.

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Appendix A

Typology, floorplans and facades of the Airey houses.

Type 90 in blue shades, type 100 in orange.

Floorplan type 00220S000090 (type 90)

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Floorplan type 00220T000090 (type 90)

Floorplan type 00220T00090v (type 90)

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Floorplan type 00220T000100 (type 100)

Facades type 100 (front/back)

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Appendix B

SmartAgent model and SmartAgent research in Eindhoven.

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Appendix C

Potential for open Heat and Cold Storage in the city of Eindhoven.

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Appendix D

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*Black data is the historical data; red is predicted data using the average annual deviation of historical data. The calculation were done using the linear function: y= -8.373.598.393 + 4.323.226x. These data are used to calculate the electricity demand growth in percentages per year.

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Appendix E

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*Black data is actual historical data; red data is predicted data using the average annual deviation of historical data. The calculations regarding to consumption <2500 kWh were done using the linear function: y= -25,420285 + 0,012785x. The calculations regarding to the consumption >2500 kWh were done using the linear function: y = -21,723428 + 0,01092x.

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*Black data is actual historical data; red data is predicted data using the average annual deviation of historical data. The calculations regarding to the consumption < 1250 m³ were done using the linear function: y = -70,1603 + 0,0353x. The calculations regarding to the consumption > 1250 m² were done by using the linear function: y = -31,3389 + 0,0159x.

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Appendix F

Balance courses per investment year for scenario 1: minimal investments

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Appendix G

Expected monthly rental and energy costs for scenario 1: minimal investments

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Appendix H

Balance courses per investment year for scenario 2: ambitious

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