Net Zero Energy Districts: Connected Intelligence for Carbon-Neutral Cities
1.1. Problem Definition
1.2. Research Hypotheses
1.3. Theoretical Framework
1.4. Methodology and Data
2. Net-Zero Energy Districts: Literature Highlights for NZED Model Design
2.1. The Origin of the Concept
2.2. Types of Net-Zero Energy Districts
2.3. NZED Processes towards Carbon Neutrality
3. A Model for Transitioning to NZED
3.1. Model Building Blocks
3.2. Block A: District
3.3. Block B: Energy Usage and CO2
3.4. Block C: Transition Measures to NZED
- Housing: Energy saving by building refurbishment
- Housing: Energy saving by smart city solutions
- Public lighting: Energy saving by smart city lighting
- Transport: Green mobility and energy saving
- Smart grid and storage
- Local RE: Photovoltaic panels
- Local RE: Heat pumps and geothermal heat pumps
- Nature-based solutions: Tree canopy and CO2 offset
- C1. Housing: energy saving by building refurbishment
- C2. Housing: energy saving by smart city solutions
- C3. Public lighting: energy saving by smart city lighting
- C4. Transport: Green mobility, energy, and CO2 emissions
- All energy and CO2 emissions for mobility are counted in the residential district of travel origin. As the commuting distance increases, energy consumption and emissions are released to neighbouring city districts. This calculation is the worst-case scenario for the district of travel origin but is neutral at the entire city level, as total emissions are aggregated from one district to another.
- Within the next few years, public transport will progressively adopt electromobility, and all energy consumption (EMPT) will be covered by electricity. If only renewable energy is used, CO2 emissions (CMPT) will go down to zero.
- Green mobility is on the rise and will continue to increase. The share of the population (z) that will adopt green mobility is specific to each city and should be introduced in the respective scenario.
- However, a part of the population will continue to use conventional fossil fuel cars that release CO2. These emissions should be absorbed by nature-based solutions.
- C5. Smart grid and energy storage
- C6. Local RE: Photovoltaic panels
PVs = 0.70 × [Ah × BRC + 0.1 × Ah + 0.1 × Ar] (sm)
ERE = f (DC system size) (kWh/year)
- C7. Local RE: Heat pumps and geothermal heat pumps
- C8. Nature-based solutions: Tree canopy and CO2 offset
- Public gardens, large and small, and city forests can contain 500 trees per hectare. We assume 60% coverage of green spaces by trees.
- Roads with trees on both sides at an average distance of 5 m from each other can contain 400 trees per km.
- Private gardens and yards may have 25% of their surface covered by trees.
CO2-a = [f (Ag)+f(Rlg)+f(Ah)] × 24 kg CO2/tree (kg)
3.5. Block D: Balancing Energy and CO2 in the NZED
4. Simulation and Results
4.1. Baseline Scenario and Simulations
4.2. Feasibility of NZED—H1
4.3. Critical Thresholds for Carbon-Neutral Disricts—H2
4.4. Rejection of the Compact City Form—H3
5. Conclusions: Connected Intelligence for Carbon-Neutral Cities
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Human Intelligence||Collective Intelligence||Machine Intelligence|
|AP||Active population as % of the district population||Working person|
|H||Number of households||Household|
|At||Total area of the district||Hectare|
|As||Social care, education, culture, sports area||Hectare|
|Ar||Local retail and services area||Hectare|
|Ar||Road and parking area||Hectare|
|Ag||Green space, gardens, urban forests area||Hectare|
|City grid and public lighting|
|Bb||Number of building blocks on the grid||Building block|
|Pl||Number of lighting poles on the grid||Pole|
|Rlg||Road length of the district grid||Kilometre|
|BRC||Building Coverage Ratio||Percentage|
|Hfpc||Housing floor per capita||Square meter|
|Bnf||Number of building floors||Floor|
|Tpc||Number of commuting travels per worker per year||Travel|
|Dtpc||Average distance per commuting travel||Kilometre|
|Pmpc||People using a private car in commuting, % of total commuting||Percentage|
|Pmpt||People using public transport in commuting, % of total commuting||Percentage|
|Pmgr||People using a bicycle, walk or work from home, % of total commuting||Percentage|
|ERPC||Energy consumption residential per capita||kWh/year|
|ERT||Energy consumption residential-Total||kWh/year|
|EH||Energy consumption residential-Heating||Per cent of total|
|ELA||Energy consumption residential-Lighting and appliances||Per cent of total|
|EDWH||Energy consumption residential-Domestic water heating||Per cent of total|
|EC||Energy consumption residential-Cooking||Per cent of total|
|ECL||Energy consumption residential-Cooling||Per cent of total|
|ERE||Energy production renewable||kWh/year|
|CRT||CO2 emissions residential-Total||Tons/year|
|CH||CO2 emissions residential-Heating||Tons/year|
|CLA||CO2 emissions residential-Lighting and appliances||Tons/year|
|CDWH||CO2 emissions residential-Domestic water heating||Tons/year|
|CC||CO2 emissions residential-Cooking||Tons/year|
|CCL||CO2 emissions residential -Cooling||Tons/year|
|ESL||Energy consumption streetlighting-Total||kWh/year|
|LP||Lamp power per pole||kWh|
|HSL||Street lighting system operating hours per year||Hours|
|EMT||Energy consumption in mobility-Total||kWh/year|
|EMPT||Energy consumption in mobility by public transport||kWh/year|
|EMPC||Energy consumption in mobility by private car||kWh/year|
|EMEV||Energy consumption in mobility by electric car and micro-mobility||kWh/year|
|CMPT||CO2 emissions in mobility by public transport||Tons/year|
|CMPC||CO2 emissions in mobility by private car||Tons/year|
|Energy Usage||Percentage of Total Energy Consumption|
|Lighting and appliances||14.1%|
|Domestic water heating||14.8%|
|Daily Commuting by||Initial||Impact on||NZED State||Impact on||Measurement Unit|
|Public transport||15%||kWh||15%||kWh||0.1 kWh/km|
|Private car||70%||CO2||15%||CO2||190 gr/km|
|Private car—electric vehicle||0%||kWh||50%||kWh||0.2 kWh/km|
|Walking, cycling, non-commuting||10%||-||10%||-||-|
|Country||Type of |
|Heat before (kWh/m2)||Heat after (kWh/m2)||Saving %|
|C1: Building refurbishment||5,082,271||7,310,113||9,219,478|
|C2: Smart home solutions||563,365||810,319||1,021,970|
|C3: Smart city lighting||388,420||366,264||355,026|
|C7: Heat pumps||10,963,641||16,997,697||15,769,616||24,256,313||19,888,559||30,485,033|
|C6: PV panels||31,118,964||20,115,406||19,342,450|
|Energy balance NZED (kWh)||+6,184,861||−15,030,255||−24,562,739|
|C4: CO2 emissions||285,000||285,000||285,000|
|C8: CO2 capture||298,200||298,200||298,200|
|CO2 balance NZED (kg)||+13,200||+13,200||+13,200|
|Energy usage after saving||24,934,103||35,145,661||43,905,189|
|RE surplus or gap||24.80%||−42.77%||−55.94%|
|C1: Building refurbishment||6,098,725||4,093,664||3,964,375|
|C2: Smart home solutions||676,038||453,779||439,447|
|C3: Smart city lighting||388,420||366,264||355,026|
|C7: Heat pumps||13,156,369||20,319,553||8,830,985||13,744,691||8,552,080||13,310,929|
|C6: PV panels||31,118,964||20,115,406||19,342,450|
|Energy balance NZED (kWh)||+1,275,724||+272,679||+260,854|
|C4: CO2 emissions||342,000||159,600||122,550|
|C8: CO2 capture||298,200||298,200||298,200|
|CO2 balance NZED (kg)||−43,800||+138,600||+175,650|
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Komninos, N. Net Zero Energy Districts: Connected Intelligence for Carbon-Neutral Cities. Land 2022, 11, 210. https://doi.org/10.3390/land11020210
Komninos N. Net Zero Energy Districts: Connected Intelligence for Carbon-Neutral Cities. Land. 2022; 11(2):210. https://doi.org/10.3390/land11020210Chicago/Turabian Style
Komninos, Nicos. 2022. "Net Zero Energy Districts: Connected Intelligence for Carbon-Neutral Cities" Land 11, no. 2: 210. https://doi.org/10.3390/land11020210