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This report has its purpose to present the load analysis of thermal and energy systems of a selected building and in this case, a nucleus hospital (which is single storied). Moreover, this report will include a CHP analysis with its financial involvement within this system.
2. Key assumptions and load evaluation
The main assumptions which are revolving around the thermal system, in this case, are a) heat capacity, b) thermal expansion, c) thermal conductivity, and d) thermal stress. Moreover, the considerable aspects of this building are the cooling system and space heating. However, when it comes to the major assumptions of the energy system of this building, it can be stated that the considerable elements are: a) lighting, b) pump system, c) ventilation system (which includes fans), f) energy consumption in the pool due to hydrotherapy system, and g) Small power.
The major considerable load consideration includes the heating as well as the thermal load which have been evaluated in both the daily and annual perspective of the building. As for the daily load evaluation the calculation has been done on the basis of the readings that have been taken throughout a single day taking an interval of 1 hour. This indicates the load consumption reading after every single hour in every loading department.
Daily electrical usage of the building
According to the table, it can be seen that the electrical energy laid has been evaluated with the readings that have been taken every one-hour interval of a single day. This process has been continued by enlisting the readings of load every single month. Every single load has been measured with kW unit and for the month of January it has been clearly seen that the energy load has gradually increased from 1 am of the day and takes its peak point at the time 10 am of that day. However, the load decreased after that and again reaches its maximum point in the evening of 5 pm of that day. In addition, the same goes for the daily readings of the month of February.
Daily load evaluation for the dissimilar department of the system
As per this table, it is clearly visible that, the load of the dissimilar department has been evaluated for a single day in every month and this table has presented the daily load utilization for the month of January. The considered departments for the thermal load reading enlisting for a single day are as follows: a) Cooling, b) Space heating, c) DHW, and d) Pool. On the other hand, the enlisted dissimilar load departments for the energy system are as follows: a) Small power, b) lighting, c) Pump and d) fan.
3.1 Reflection on energy and load profiles
This aspect highlighted the load profiles of dissimilar rooms of the hospital. However, to present different load variations within the building 4 rooms have been selected in this case. The considered rooms of this building are: a) Administrative, b) Entrance, c) Workshop and staff areas, and d) Pharmacy. According to the given plan of the building, the evaluation of the dimension of length and breadth of every single room has been successfully evaluated. The standardized elevation has been considered for every single room which is 3 m. However, for that reason, the volume of the rooms has been successfully evaluated. This volume evaluation is necessary for the analysis of the thermal load.
In this case, the volume of the room has been considered for the identification of the thermal load for the respective room. As for the administrative room, the formula for the4 evaluation of thermal load was = Length*Breadth*Height*141 and this formula leads to the value of 305406 BTU (unit of the thermal load). In this scenario, the value of 141 indicates a standardized factor of safety value according to designingbuildings.co.uk, 2022. This evaluation indicated the daily reading of the thermal load of a building. Therefore the annual thermal load have been evaluated by the multiplication by 365.
As for the establishment of the electrical load, the lighting load profile has been selected in this case, and the total lighting power for every single room has been enlisted according to the above table. In this table, for every room the time duration of the load running has been evaluated which further leads to the calculation of the total daily electrical load for respective rooms. According to the evaluation the maximum electrical load has been evaluated in the workshop room for the lighting load profile.
3.2 Tariff selection
The price of establishing electricity will rely on several aspects, in this case, interlinked load, load factor, peak demand, the capacity factor of the hospital, and use factor. These, in turn, will rely upon the kind of the load as well as its conditions (Luo et al. 2019). Therefore, the tariff is divergent for dissimilar load profiles. However, there are several tariffs available for the evaluation of the rate per unit of energy and in this scenario, the chosen tariff is the "flat rate tariff”.
However, within this tariff, dissimilar kinds of energy systems (in this case thermal and electrical) are transformed at dissimilar rates of price per unit (which is 1kWh) of consumed energy of electricity. Dissimilar clients(in this case, thermal and electrical energy systems) in this case have been merged under dissimilar categories (Ansarin et al. 2020). After that, every single category is capital (charged) at a rate (fixed) the same as a simple tariff. The dissimilar rates have been decided as per the thermal and electrical laid and their factors. The considerable merits of this tariff are as follows: it needs simple calculations and provides fair credentials to the energy systems.
This criterion indicates the investigation as well as the assessment of the factors utilization of the energy system which are thermal and electrical energy. In this scenario, to identify the benchmarks of this system two types of data will be procured of which one is internal and the other one is external. The utilization of a benchmarking tool (online) has happened in this case, and they have used the "ENERGY STAR Portfolio Manager” in this case. These tools have permitted the system managers to evaluate their development areas of the energy systems of the hospital against national standards of efficiency as well as sustainability.
3.4 Sizing and selection of CHP
In that circumstance the chosen CHP ("Combined heat and power”) system for the hospital is “Solihull Hospital, Birmingham, 770kWe feeds 340kW absorption chiller” and this system provides various energy services to the hospital and they are as follows:
Additional recommendation in CHP system
Letra (Industrial CHP): The generation process of electricity within conventional power plants manufactures a lot of heat, and most of them lost in the process. This CHP will apprehend this heat and transform it to thermal energy. Letra will develop solutions (which are diverse) for renewable energy. This will install the units of CHP for industrial customers, enabling savings within the prices for both the thermal and electrical energy for the hospital This CHP system will also provide manageme3nt of automated energy as well as power plants (virtual) for developing energy efficiency and the stability of frequency.
4.1 Recommended equipment
4.2 Recommended system design
4.3 Recommended system control
This indicates the control system will be computerized and it will be designed in such a way with it can regulate the consumption of energy in this hospital. This may be possible by taking control over the operation which indicates the activities of the systems of energy consumption, for example, ventilation, heating, air conditioning, water heating as well as lighting systems. This system control (computerized) will be capable of observing not only the system but also the environmental loads of the building. This system will customize the operations of HVAC in order to make customization the utilization of energy as well as making the response to the signals of demand response.
4.4 Financial analysis
The above table indicates a financial chart in which it has been clearly started the initial investment as well as the cash flow per year for every single load profile. These dates have helped to establish the value of the payback period of every single load profile. Further, with this data, the NPV and the IRR have been established.
This report has clearly presented the load analysis of both the thermal and electrical with respect to daily and annual utilization for every single laid profile. In the discussion part, an elaboration of the CHP system that has been selected for this building has been done. Moreover, the recommendation has highlighted the proposed equipment, system control, and design for the building with which the energy system can develop in the future.
Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W. and Collins, J., 2020. The economic consequences of electricity tariff design in a renewable energy era. Applied Energy, 275, p.115317.
Luo, F., Kong, W., Ranzi, G. and Dong, Z.Y., 2019. Optimal home energy management system with demand charge tariff and appliance operational dependencies. IEEE Transactions on Smart Grid, 11(1), pp.4-14.
Pacudan, R. and Hamdan, M., 2019. Electricity tariff reforms, welfare impacts, and energy poverty implications. Energy Policy, 132, pp.332-343.
Ahmadi, G., Toghraie, D. and Akbari, O., 2019. Energy, exergy and environmental (3E) analysis of the existing CHP system in a petrochemical plant. Renewable and sustainable energy reviews, 99, pp.234-242.
Fan, X., Sun, H., Yuan, Z., Li, Z., Shi, R. and Razmjooy, N., 2020. Multi-objective optimization for the proper selection of the best heat pump technology in a fuel cell-heat pump micro-CHP system. Energy Reports, 6, pp.325-335.
Urbanucci, L. and Testi, D., 2018. Optimal integrated sizing and operation of a CHP system with Monte Carlo risk analysis for long-term uncertainty in energy demands. Energy conversion and management, 157, pp.307-316.
Perera, A.T.D., Nik, V.M., Wickramasinghe, P.U. and Scartezzini, J.L., 2019. Redefining energy system flexibility for distributed energy system design. Applied Energy, 253, p.113572.
Kotzur, L., Markewitz, P., Robinius, M. and Stolten, D., 2018. Impact of different time series aggregation methods on optimal energy system design. Renewable energy, 117, pp.474-487.
Naderipour, A., Abdul-Malek, Z., Vahid, M.Z., Seifabad, Z.M., Hajivand, M. and Arabi-Nowdeh, S., 2019. Optimal, reliable and cost-effective framework of photovoltaic-wind-battery energy system design considering outage concept using grey wolf optimizer algorithm—Case study for Iran. IEEE Access, 7, pp.182611-182623.
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