MétaCan
Menu
Back to cohort
Record W4362513406 · doi:10.22215/etd/2023-15374

Techno-Economic and Environmental Performance of Two Distinct State-of-the-Art Solar-Assisted District Energy System Topologies

2023· dissertation· en· W4362513406 on OpenAlexafffundabout
Nicholas Brunt

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsCarleton UniversityEmissions Reduction Alberta
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centre of Innovation
KeywordsPhotovoltaic systemBooster (rocketry)MATLABEnvironmental scienceSolar energyThermalRenewable energyNetwork topologyEngineeringEnvironmental engineeringMeteorologyCivil engineeringComputer scienceElectrical engineeringGeographyAerospace engineering

Abstract

fetched live from OpenAlex

This study introduces a novel, ambient-temperature district energy system topology that enables bi-directional mass flow to booster heat pumps and includes distributed solarthermal generation.The ambient system topology is described, and a corresponding detailed model is developed in the MATLAB-Simulink® environment.An equivalent model is developed for a conventional, supply-return district system utilizing hot water (at 75°C) and chilled water (at 15°C), allowing for the direct comparison with the proposed topology-both with and without solar-thermal integration-in technical, environmental, and economic analyses.Technical performance is assessed using a system coefficient of performance and solar fraction, environmental performance is estimated using carbondioxide equivalent emissions, and economic performance is characterized using a levelized cost of energy approach.Annual simulations are conducted for the case study of an urban district energy system in Ottawa, Canada, connected to 12 commercial building clusters.The ambient-temperature system achieves an annual system coefficient of performance of 1.40 without solar assistance and 1.43 with solar assistance.The conventional system achieves annual coefficients of performance of 1.26 and 1.28, respectively.The solar fractions of the ambient and conventional systems are 5.5 and 4.0% for heating and 9.3 and 10.0% for cooling, respectively.Despite these noted improvements in performance with solar-thermal, the technical findings indicate that the rooftop solar collection fields are undersized relative to system loads due to rigid rooftop space constraints.Nonetheless, the ambient system (without solar) decreases annual carbon emissions by 32.16% relative to the conventional system, a significant improvement.Furthermore, while the ambient system's levelized cost of energy is higher than the conventional both without solar (8.1 iii vs. 6.0¢/kWh) and with solar (11.0 vs. 9.2¢/kWh), the ambient system becomes the most economically attractive option if the social cost of carbon is considered at any price above $16/tCO2-e-a rate far below the existing Canadian price of $50/tCO2-e.v Nomenclature 𝐴 Area (m 2 ) 𝐴𝐸𝑂 Annual energy output (kWh) 𝑏 𝑖 Incidence angle modifier coefficient 𝑖 (-) 𝑐 𝑖 Heat loss coefficient 𝑖 (-) 𝑐𝐿𝐶𝑂𝐸 Composite levelized cost of energy ($/kWh) 𝐶𝑂𝑃 Coefficient of performance (-) 𝐶 𝑝 Specific heat of water at constant pressure (J/kg-K) 𝐶𝑅𝐹 Capital recovery factor (-) 𝑐𝑇𝑎𝑥 Carbon tax rate ($/tCO2-e) 𝑑 Pipe depth 𝐷 𝑖 Pipe inner diameter (m) 𝐷 𝑜 Pipe outer diameter (m) 𝐸 𝐶𝑂2𝑒 Carbon-dioxide equivalent emissions (t) 𝐸𝐹 Emissions factor (tCO2-e/GWh) 𝑓 𝐷 Darcy friction factor (-) 𝐹 𝑡 Natural gas costs in year 𝑡 ($) 𝐼 𝑇 Incident solar radiation (W/m 2 ) 𝐼 𝑡 Capital costs in year 𝑡 ($) 𝑘 Thermal conductivity (W/m•K) 𝐾 𝜏𝛼 Incidence angle modifier (-) 𝐿 Pipe length (m) 𝑙 Solar collector length (m) 𝐿𝐶𝑂𝐶 Levelized cost of carbon ($/kWh) 𝐿𝐶𝑂𝐸 Levelized cost of energy ($/kWh) 𝐿 𝑑𝑒𝑠𝑖𝑔𝑛 Design load (W) 𝑚̇ Mass flow rate (kg/s) 𝑀 𝑡 Operations and maintenance costs in year 𝑡 ($) 𝑁 Number of computational nodes in tank model (-) 𝑛 Project lifetime (years) 𝑃 𝑡 Electricity costs in year 𝑡 ($) 𝑄 ̇ Rate of heat transfer (W) 𝑟 Discount rate (%, annualized) 𝑅𝑒 Reynolds number (-) 𝑆𝐹 Solar fraction (%) 𝑇 Temperature (K or °C) 𝑡 Thickness (m) 𝑡 𝑑𝑒𝑙𝑎𝑦 Build time (years) 𝑣 Velocity (m/s) 𝑉 𝑆𝑇𝑆 Tank volume (m 3 ) 𝑊 ̇ Rate of electrical power consumption (W) 𝑤 Solar collector width (m) Greek Letters 𝛽 Solar collector tilt (°) 𝛾 Solar collector azimuth angle (°) 𝛥𝑃 Design pressure differential (kPa) 𝛥𝑇 Design temperature difference (K or °C) 𝛥𝑡 Simulation time step (s) vi 𝜖 𝐻𝐸𝑋 Heat exchanger effectiveness (-) 𝜂 Efficiency (-) 𝜂 𝐻𝑃,𝐶𝑎𝑟𝑛𝑜𝑡 Heat pump Carnot effectiveness (-) 𝜃 Angle of incident solar radiation (°) 𝜌 Density (kg/m 3 ) (𝜏𝛼) 𝑛 Transmittance-absorptance product (-) Abbreviations and Subscripts AC Absorption chiller air Air amb Ambient topology AMY Actual meteorological year c Cooling CAD Canadian dollars casing Pipe casing CEEDC Canadian Energy & Emissions Data Centre CHP Combined heat and power chw Chilled water stream (in variable-compression and absorption chillers) cond Condenser (of heat pumps or chillers) conv Conventional topology COP Coefficient of performance CT Cooling tower CV Control valve cw Cooling water stream (in variable-compression and absorption chillers) DC District cooling DE/DES District energy/District energy system DH District heating DLSC Drake Landing Solar Community DN Diametre Nominal (metric standard pipe sizes) EIA United States Energy Information Administration eva Evaporator (of heat pumps or chillers) h Heating HEX Heat exchanger HP Heat pump hw Hot water stream (in absorption chiller) in Inlet ins Pipe insulation IPCC Intergovernmental Panel on Climate Change ISO International Organization for Standardization load Load side of plant solar dispatch loop LT Long-term (thermal storage) max Maximum (i.e., rated capacity) min Minimum NCR National Capital Region NG Natural gas NPV Net present value out Outlet PE Polyethylene return Return-side property, entering plant

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.004
GPT teacher head0.180
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes3
Has abstractyes

Explore more

Same topicIntegrated Energy Systems OptimizationFrench-language works237,207