Bibliographic record
Abstract
Energy demand for buildings has been rising during recent years. Increasing building energy consumption has caused many energy-related problems and environmental issues. The on-site community energy system application is a promising way of providing energy for buildings. Community energy system usage reduces the primary energy consumption and environmental effects of greenhouse gas (GHG) emissions compared to the implementation of the stand-alone energy systems. Furthermore, due to the increase in electricity price and shortage of fossil fuel resources, renewable energies and energy storage technologies could be great alternative solutions to solve energy-related problems. Generally, the energy system might include various technologies such as internal combustion engine, heat recovery system, boiler, thermal storage tank, battery, absorption chiller, ground source heat pump, heating coil, electric chiller, solar photovoltaics (PV) and solar thermal collectors, and seasonal thermal energy storage. The economic, technical and environmental impacts of energy systems depend on the system design and operational strategy. The focus of this thesis is to propose unified frameworks, including the mathematical formulation of all of the components to determine the optimal energy system configuration, the optimal size of each component, and optimal operating strategy. The proposed methodologies address the problems related to the optimal design of the energy system for both deterministic and stochastic cases. By the use of the proposed frameworks, the design of the energy system is investigated for different specified levels of GHG emissions ratio, and the purpose is to minimize the annual total cost. To account for uncertainties and to reduce the computational times and maintain accuracy, a novel strategy is developed to produce scenarios for the stochastic problem. System design is carried out to minimize the annual total cost and conditional value at risk (CVaR) of emissions for the confidence level of 95%. The results demonstrate how the system size changes due to uncertainty and as a function of the operational GHG emissions ratio. It is shown that with the present-day technology (without solar technologies and seasonal storage), the lowest amount of GHG emissions ratio is 37%. This indicates the need for significant technological development to overcome that ratio to be 10% of stand-alone systems. This thesis introduces novel performance curves (NPC) for determining the optimal operation of the energy system. By the use of this approach, it is possible to identify the optimal operation of the energy system without solving complex optimization procedures. The application of the proposed NPC strategy is investigated for various case studies in different locations. The usage of the proposed strategy leads to the best-operating cost-saving and operational GHG savings when compared to other published approaches. It has shown that other strategies are special (not always optimal) cases of the NPC strategy. Based on the extensive literature review, it is found that it is exceptionally complicated to apply the previously proposed models of seasonal thermal energy storage in optimization software. Besides, the high computational time is required to obtain an optimum size and operation of storage from an optimization software. This thesis also proposes a new flexible semi-analytical, semi-numerical methodology to model the heat transfer process of the borehole thermal energy storage to solve the above challenges. The model increases the flexibility of the storage operation since the model can control the process of the storage by also deciding the appropriate storage zone for charging and discharging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".