Compensaciones ambientales basadas en la equivalencia del valor económico

The previous section outlined the general approach used across the PhD study to build towards a significant contribution to the body of knowledge. This sec- tion will detail the process by which each research question was answered and how the outcomes were validated. In the case of research questions 2, 3 and 4, different optimisation and control methodologies have been developed and applied to the relevant field. To demonstrate the methodologies’ effectiveness, and hence provide evidence for the answers to each research question, the individual methodologies were applied to specific case studies. These case studies are all simulation-based to allow full control of factors such as weather and occupancy, reproducibility of results across different scenarios, and to pro- vide direct comparison between the optimised scenario and baseline strategy. Every effort has been made to make these case studies as realistic as pos- sible by feeding in learnings from the projects and through interactions with specialists and practitioners.

3.3.1

Building-Level Control

Chapter 4 aims to address research question 2; Can predictive control of build- ing energy demand with consideration of external factors lead to reductions in energy cost and improve demand-side flexibility? The case study was based around a simulation model of the authors’ office building in Cardiff. This was chosen as the building was relatively small with only 6 conditioned zones al- lowing detailed modelling. It is a multi-purpose building with different types of zones including office spaces, a meeting room, reception and kitchen providing a more interesting and complex example with a requirement for zone-level con- trol as opposed to a more homogeneous building. Furthermore, access to the building was unproblematic, allowing easy measurement of building geometry and equipment as well as surveying of occupants to build realistic schedules. To validate the performance of the proposed building control methodology, the results were compared to a standard, baseline scenario. This baseline sce-

nario applies the same heating schedule to the entire building which is the case in reality. It follows a pre-determined heating set point schedule of 12◦C when unoccupied, and 21◦C when during occupied hours. As the simulation models in the optimised and baseline case are absolutely identical apart from the decision variable in the optimisation methodology, comparison can provide assessment of potential optimisation savings. Furthermore, the difference be- tween setting a building-wide heating set point temperature and a zone-level set point temperature will be analysed.

3.3.2

District-Level Control

The case study outlined in Chapter 5 aims to address research question 3; Can taking an optimisation-based approach to the control of district heat generation improve upon existing rule-based priority order strategies? To develop this, an entirely simulated district energy system including the supply and demand is designed. The design of both the supply and demand was greatly influenced by the research projects outlined in Stage 2 of the research approach.

To model a realistic energy demand, reference building EnergyPlus models from the US Department of Energy were used. As demonstrated via the PEN- TAGON project, it is important for the buildings connected to a district heating network to have some level of constant, year-round base load. In the case of ‘The Works’ in Ebbw Vale (a PENTAGON pilot site), the base thermal load is largely provided by swimming pools in a sports centre. In the case study developed for this research, it is provided by a hospital and hotel. In total five different buildings were selected to provide the demand profile for the case study district. Following analysis of the district heating demand, standard de- sign procedures could be used to size the energy generation units which is outlined in greater detail in Chapter 5.

The chosen energy supply configuration is inspired largely by the scenarios used in the PENTAGON project. The aim was to create a multi-vector energy centre combining gas, electricity and heat networks in a single case study. To achieve this aim, generation and conversion units from different case-studies were merged to provide a complex, modern district energy system. To validate the performance of the optimisation methodology outlined in Chapter 5, it was compared to a static rule-based operation which formed the baseline scenario. The baseline scenario is a typical priority order strategy depending on the cur- rent demand. This is the current strategy deployed at ‘The Works’ pilot site and is therefore a fair representation of reality to benchmark against.

3.3.3

Combined District and Building Control

The combined building and district energy management strategy provided in Chapter 6 uses the same district utilised in Chapter 5. It aims to use this case study to tackle research question 4; Can integrated, holistic control of both en- ergy supply and energy demand lead to greater economic and environmental benefits than independent control? The same logic and assumptions behind the creation of the case study still hold true. The crucial difference between Chapter 5 and Chapter 6 is that the demand of one of the buildings within the district is now controllable through adjustment of the heating set point temper- ature in a similar manner that proposed in Chapter 4. Only direct control of the office building is available in this case study. The aim here was to limit the amount of decision variables for the optimisation, and yet provide a proof of concept for this kind of combined supply and demand control. In particular, the office building was selected as this type of building would be the most likely to acquiesce to the removal of direct control over their heating systems in com- parison to a hospital, hotel or residential apartments where comfort is king. In terms of validation for this case study, the optimisation outcomes can be com- pared to the same baseline scenario as the district level control outlined above. In addition, comparisons can also be drawn to the optimised results from Chap- ter 5 to illustrate the potential improvements in terms of cost of energy that can be achieved by allowing direct control of supply and demand.