The deep renovation of high-rise apartment buildings to create positive-energy neighborhood

Abstract

Decarbonizing cities requires transforming existing high-density residential districts into low-carbon or Positive Energy Neighborhood (PENs). This is particularly challenging in cold climates, where high seasonal heat demand, limited solar availability, and aging building stock constrain both energy performance and on-site renewable energy generation. This study evaluates the feasibility of transforming a high-rise residential neighborhood in Estonia into a PEN through deep renovation and local renewable energy integration. A multiscale approach was applied, combining building-level energy performance modelling with neighborhood-scale renewable energy supply analysis. The results show that deep renovation measures, including improved insulation and high-efficiency heating and ventilation systems, can reduce building energy demand by 60%–70%. Rooftop photovoltaic (PV) systems can supply 12%–27% of post-renovation electricity demand when combined with efficient district heating. Facade-integrated PV systems can increase renewable electricity coverage to as much as 85%; however, their energy yield decreases by 24% because of non-optimal orientation and solar exposure. The findings show that achieving PEN status in cold-climate high-rise building neighborhoods is not possible through building-integrated renewable energy alone and requires additional off-site or neighborhood-scale renewable energy generation. Meeting winter heating demand with renewable sources would require land areas approximately 20 times larger than the building footprint for biomass sources and twice the footprint for ground-source heat systems. This study proposes an integrated pathway for transitioning high-rise residential neighborhoods toward PENs by combining deep building renovation, improved indoor environmental quality, and neighborhood-scale renewable energy deployment. The results highlight the importance of aligning technical, spatial, social, and ecological strategies within urban planning to enable scalable implementation of positive energy neighborhoods in cold climates.

Highlights

• Existing high-rise districts assessed as future positive energy neighborhoods

• PEN feasibility depends on both renovation depth and renewable space

• Neighborhood-scale renewable integration extends beyond building footprints

• Seasonal energy imbalance identified as a key PEN challenge

• Integrated planning is critical for scalable cold-climate PEN deployment.

1 Introduction

Decarbonizing building stock is a cornerstone of the EU’s climate strategy, which requires a shift towards zero-emission buildings through deep renovation and the integration of renewable energy systems (EPBD, 2024). Deep renovation is a comprehensive process that maximizes a building’s energy savings and performance—based on its type and climate—by minimizing energy demand, fully covering needs with renewables, and ensuring high indoor environmental quality (BPIE, 2021). The first step of deep renovation typically involves upgrading buildings to a nearly zero-energy building (nZEB) standard, a transition that has been demonstrated to be technically, economically and environmentally feasible for residential buildings in various climates (Pihelo et al., 2017; Iturriaga et al., 2018; De Luca et al., 2020; Palma et al., 2022; Boussaa et al., 2023).

However, beyond the building scale, district- and neighborhood-level strategies provide greater opportunities for cost-effectiveness, facilitate energy sharing between buildings, and incorporate integrated infrastructure solutions (Bayera Madessa et al., 2024). Despite this potential, national renovation strategies across EU member states still exhibit a weak commitment to mass-scale renovation (Lihtmaa and Kalamees, 2024), and the need for management and the capacity for the mass renovation of existing buildings (Lehmann, 2012) have not been well recognized.

Positive-energy district (PEN) or Positive Energy Neighborhood (PEN) – urban areas that are not only energy-efficient but also actively manage annual local or regional surplus production of renewable energy (EERA JPSC, 2020; Hinterberger et al., 2020) – have emerged as key concepts in the decarbonising of building stock. However, a recent survey of over 60 European PED initiatives revealed that only 27% address only the existing building stock (others considered newly built or mixed neighborhoods) (Bossi et al., 2020), exposing a critical gap. While the PED Booklet (Gollner et al., 2020) and other recent reviews (Derkenbaeva et al., 2022; Sassenou et al., 2024) have helped define the field, they underscore the lack of real-world implementation data, especially in cold-climate, densely occupied urban contexts. As PENs should be integrated into local policies to enhance stakeholder commitment (Gohari et al., 2024), a strong involvement of research and development institutions and consideration of local and national needs are necessary.

PEDs/PENs require on-site or nearby energy generation from renewable energy sources (RES). Wang et al. (2025) provided a detailed multi-dimensional analysis of PV potential in Hong Kong’s high-rise high-density urban morphology. The results of that analysis are useful for identifying optimization objectives suitable for dense urban environments and for performing multi-dimensional PV capacity evaluations on optimized urban forms. Gouveia et al. (2021) analyzed the PED model’s potential for a historic district in Lisbon (Portugal) to reduce emissions and energy poverty, showing that building retrofits could cut energy needs by 84% for heating and 19% for cooling, while integrated PV technologies could generate up to 60 GWh/year. Bambara et al. (2021) analyzed the PEN of detached houses in Canada, showing that nearly half of a house’s electricity can be directly supplied by the BIPV roof. However, a significant portion of the annual solar electricity generation cannot be directly utilized by the houses. Due to the different environmental conditions and building archetypes in cold climates, additional knowledge is needed for the renovation of existing buildings in these areas.

In this manuscript, Positive Energy Neighborhood (PEN) is used consistently as the operative term. The term positive-energy district (PED) is retained only when referring to the broader literature. Here, PEN is defined as an existing residential neighborhood in which the annual operational building energy demand is balanced or exceeded by locally or nearby generated renewable energy. High-density, high-rise neighborhoods common in post-war mass-constructed cities pose particular challenges to PEN targets because of their high energy demand, limited roof area, constrained solar access on facades due to dense urban form, and the seasonal mismatch between solar availability and winter heating demand in cold climates.

Thus, this study investigated the feasibility and requirements for transforming such a neighborhood in Estonia’s cold climate into a PEN through deep renovation and on-site renewable integration.

2 Materials and methods

This study applies a multiscale methodology to assess the feasibility of transforming an existing high-rise residential neighborhood in a cold climate into a Positive Energy Neighborhood (PEN). The approach combines building-level energy performance analysis with neighborhood-scale renewable energy assessment to evaluate deep renovation measures, indoor climate improvements, renewable energy integration, and land-use requirements. Section 2.1 presents the general framework of the study. Section 2.2 describes the case-study neighborhood and building typologies. Section 2.3 introduces the indoor climate and energy performance calculation methods, while Section 2.4 outlines the analyzed renovation measures and renewable energy system solutions.

2.1 General framework

The European Commission Joint Research Centre (JRC) methodology (Shnapp et al., 2020) for systematically supporting the deep renovation of high-rise apartment-building neighborhoods on the path towards PENs was adopted. This process integrates building-level energy performance improvements with district-scale renewable energy sources (RES) alternatives, as illustrated in Figure 1. The approach begins with analyzes existing building conditions, characteristics, spatial configurations, and current energy systems based on digital twins (3D. Maaruum, 2021), building register (EHR, 2023), and statistical typology databases (Torim et al., 2025) (chapter 2.2). Subsequently, the buildings in the neighborhood are characterized using measured energy consumption data and classified into representative models to facilitate a scalable analysis. We use a simulation methodology to assess the energy performance of the neighborhood by aggregating data from individual buildings (chapter 2.3). The simulation model was calibrated based on measured energy use and onsite building survey (chapter 3.1). Renovation measures are then identified, focusing on building envelopes, HVAC systems, and renewable energy integration (chapter 2.4).

FIGURE 1

Renovation packages were shortlisted using four criteria: the ability to achieve the target EPC level when envelope insulation, ventilation renovation, and the selected heat source were considered together; technical feasibility in prefabricated large-panel apartment buildings; representativeness for the subsequent neighborhood-level RES analysis; and economic attractiveness based on the net present value (chapter 3.2). On this basis, two representative solution sets were taken forward for detailed analysis: a cost-optimal package and a maximum-efficiency package. By combining deep renovation solutions for buildings, RES options (at both the building and neighborhood levels), and external energy systems, we understand the requirements for on-site or nearby renewable energy systems and the land needed to support them (chapter 3.3). Finally, strategies to achieve a Positive Energy Neighborhood (PEN) through surplus renewable energy production were analyzed, focusing on electricity from photovoltaic systems, heat from geothermal energy via heat pumps, and biobased fuels for efficient district heating, as well as the seasonal mismatch between energy demand and supply (chapter 3.4).

2.2 The neighborhood and buildings

The Mõisavahe neighborhood, covering 13.3 ha and constructed between 1985 and 1995, is in the Annelinn, district of Tartu, Estonia. With 4,330 annual heating degree days at a base temperature of 17 °C (Kalamees and Kurnitski, 2006), it faces significant heating demands due to Estonia’s cold climate. This neighborhood was selected as a representative case for examining the challenges of deep renovation in high-density residential areas. Its inclusion in Tartu’s broader climate neutrality efforts highlights the importance of addressing energy inefficiencies in these older, densely populated districts.

There are 22 apartment buildings in the Mõisavahe neighborhood (Figure 2), most of which are six–nine stories high and all of which are unrenovated. These buildings suffer from outdated insulation, inefficient heating and ventilation systems, and limited roof space for renewable energy installations, making deep energy renovation challenging. With a living density of 0.91 m/m²—calculated by dividing the total area of the neighborhood by the floor area of the buildings—this neighborhood has the highest density in Tartu (Kertsmik et al., 2025).

FIGURE 2

All buildings are constructed of prefabricated concrete large panel walls, floors, and roofs. The thermal transmittance of the building envelope is high: U_wall = 0.80 W/(m²·K), U_roof = 0.90 W/(m²·K), U_window = 1.8 W/(m²·K), and U_floor ≈ 0.8–1.1 W/(m²·K). Typical of prefabricated concrete large-panel buildings, the envelopes have many thermal bridges (Ilomets et al., 2017b)—areas with higher heat flow due to structural elements like panel joints and connections between floors and walls. At the building level, indoor climate and energy performance simulation with the dynamic software IDA-ICE, the influence of thermal bridges on the heat loss of the building envelope was considered by multiplying linear thermal transmittance Ψ (W/(m·K) and the length of the thermal bridge. For neighborhood-level simulations, the same heat loss characteristics were used. The buildings are connected to the district heating network. The heat distribution system was mostly with one-pipe and with hydronic radiators, typically without room thermostats, thus not allowing for individual control of room temperature. The indoor temperature is regulated at the building level in heat substations and depends on outdoor temperatures. At the room scale, residents can control the temperature by opening the window. Domestic hot water (DHW) is also prepared in heat substations with a heat exchanger.

All studied dwellings featured passive stack ventilation. Some apartments had mechanical exhaust ventilation in bathrooms and kitchens. Energy audits revealed that many buildings experienced insufficient heating and ventilation, leading to poor indoor climate and high humidity levels (Maivel et al., 2015; Ilomets et al., 2017a; Mikola et al., 2017).

2.3 Indoor climate and energy performance modelling

The energy performance of buildings is expressed as annual primary energy (PE) consumption and presented as the energy performance value (EPV, kWh/(m²·a)). EPV accounts for heat and fuel consumption for room heating, heating of ventilation air and infiltration air, DHW and cooling, as well as electricity for lighting, electrical appliances, and technical building services (pumps and fans). Transport energy use, embodied impacts, and other urban infrastructure are excluded from the present PEN balance. Grid exchange is discussed only in relation to temporal mismatch and self-consumption and does not redefine the annual balance criterion.

The criterion for an nZEB in Estonia is 105 kWh/(m²·a) (corresponding to energy performance certificate (EPC) ‘A’, i.e., EPV ≤125 kWh/(m²·a) (EPC ‘B’) minus 20 kWh/(m²·a) of electricity generation from RES) and criteria for major renovation is EPV ≤150 kWh/(m²·a) (corresponding to EPC ‘C’).

Energy use for room and ventilation heating, domestic hot water (DHW), and electricity consumption for appliances, lighting, pumps, and fans was measured over 3 years from a representative sample of 12 apartment buildings. Heat consumption was corrected to the reference climatic conditions by using heating degree days. This measured energy consumption data was essential for accurately assessing the actual energy consumption of buildings in the neighborhood.

Energy performance modelled at the building level with the dynamic software IDA-ICE (validated by Travesi et al., 2001) and at the neighborhood level with the ReST tool (Hallik et al., 2024). The consistency between IDA-ICE’s dynamic modelling and ReST’s static calculation (with an average deviation of only 3% (Hallik et al., 2024)) confirms the accuracy of the energy demand calculations. The influence of renovation scenarios on energy performance was analyzed by considering the standard usage of each building. This included factors such as occupied hours, ventilation air flow rates, heating and cooling set points, maximum heat gains from occupants, appliances, and lighting during occupied hours, as well as the efficiency of building service systems (RT I22.08, 2019). For non-renovated buildings, daily average passive stack ventilation by opening windows 0.05 L/s per heated m² and infiltration airflow from building envelope airtightness were used to calculate the air change rate. For renovated buildings, the indoor climate category II (ICC II, criteria for the design of a new building, renovation of an existing building (EN 16798-1, 2019)) was used in energy calculations. After renovation, the general ventilation airflow in ICC II is 0.42 L/(s·m²) or 0.6 h⁻¹, meaning design values for airflows in living rooms and bedrooms are at least 1.0 L/(s·m²) or 7 L/(s·person). In ICC II, the extraction airflow from the bathroom is 15 L/s, and from the WC, it is 10 L/s. To represent the real outdoor climate for modelling, the Estonian typical meteorological year (Seyed Salehi et al., 2024) was used for modeling.

2.4 Renovation and renewable energy measures

Additional thermal insulation for building envelopes, window replacement with different thermal transmittances (U_wall, 0.7–0.09 W/(m²·K), U_roof, 0.8–0.07 W/(m²·K), U_floor, 0.7–0.1 W/(m²·K), U_window, 1.6–0.7 W/(m²·K)), improvmenet of airtightness of building envelope with different air leakage rate (q₅₀ 1.0–5.0 m³/(h·m²), the implementation of ventilation heat recovery (0%–85%), and the construction of a two-pipe hydronic heating system with thermostats were used as energy performance improvement measures. The renovation of the heating system, specifically the upgrade from a one-pipe hydronic radiator system without thermostats to a two-pipe hydronic heating system with thermostats, as well as the domestic hot water system, which involves replacing and insulating pipes and circulation systems are essential and must be implemented regardless of other measures. The improvement of ventilation from natural passive stack ventilation (typically indoor climate category ICC ≈ IV (representing <25% Predicted Percentage of Dissatisfied (PPD) and −1.0 to +1.0 Predicted Mean Vote (PMV) (EN 16798-1, 2019)) to mechanical ventilation with heat recovery (ICC II, PPD <10% and −1.0 < PMV < +1.0) was factored into all renovation measures. For mechanical ventilation, we considered a balanced ventilation system with a specific fan power (SFP) of 1.5 kW/(m³/s) and a heat recovery efficiency of 80%.

The district-level energy system analysis emphasizes the integration of renewable energy sources—such as solar, geothermal, and biomass—with building-level renovations. By assessing these options, the energy demand following the renovations can be met using non-fossil energy sources, thereby aligning with the objectives of PEN. Other energy sources, including wind, aerothermal, hydrothermal, hydropower, landfill gas, sewage treatment plant gas, and biogases, were not considered due to their unavailability in this neighborhood.

Electricity generation from photovoltaic (PV) panels at the building level was modelled using PV Sol (Valentin Software GmbH, 2024) software. To evaluate the electricity generation capacity and efficiency of the PV panels, a detailed calculation model for each building archetype was developed, considering shading from nearby buildings on various facades. The results from PV Sol were used to verify the accuracy of the neighborhood RES model. This neighborhood analysis included PV panels installed on rooftops and different facades of all buildings, considering both direct and diffuse radiation as well as shading effects. Shading conditions were assessed by analyzing direct radiation from neighboring buildings on an hourly basis throughout the year and calculating diffuse radiation based on the horizontal and vertical components of the sky dome.

The area needed for ground source heat pump collectors was determined based on the heating requirements of each building. We estimated a horizontal collector area of 4–5 m² for every square meter of heated space, with a collector power of approximately 18 W/m² (Todoran and Balan, 2016). For vertical boreholes of a 100 m depth, we considered spacings of 6 × 6 m and 10 × 10 m. Additionally, the energy required to produce biomass from fast-growing energy bushes, which serve as fuel for heat generation during the winter, was considered. The energy density of wood chips is 5 kWh/kg (Djomo et al., 2011), and the average biomass yield is 13 t/ha of dry matter, with harvest cycles occurring every 3 years (Nassi O Di Nasso et al., 2010; Bacenetti et al., 2016).

3 Results

This chapter presents an energy-performance assessment of the neighborhood, following a stepwise structure. It begins with the pre-renovation baseline, then evaluates the impact of deep renovation measures on building energy demand and indoor climate. Next, it examines renewable energy options at both the building and neighborhood scales. The final section addresses the feasibility of achieving Positive Energy Neighborhood status by analyzing renewable energy surplus, seasonal mismatch, and the land requirements associated with various energy supply strategies.

3.1 Energy use before renovation–baseline study

Before renovation, the average (over the 3 years) delivered energy demand of the whole neighborhood for room heating was 145 kWh/(m²·a), varying between 129 and 163 kWh/(m²·a) depending on the specific building. The demand for DHW averaged 24 kWh/(m²·a) (range: 20 to 30 kWh/(m²·a)), while electricity consumption for appliances and lighting averaged 27 kWh/(m²·a) (range: 24 to 44 kWh/(m²·a)), as indicated in Figure 3 (left). The average primary energy use before renovation was 164 kWh/(m²·a) (range: 151 to 210 kWh/(m²·a)). The measured electricity and water use were lower than the typical standard use due to the buildings’ user behavior, while the average heating energy use matched the calculated value for the indoor climate category ICC IV (EN 16798-1, 2019) and passive stack ventilation without heat recovery, as illustrated in Figure 3 (right).

FIGURE 3

3.2 Performance of energy renovation measures

With renovation measures, energy performance was improved to at least EPC ‘B’ EPV ≤105 kWh/(m²·a) and a positive energy neighborhood was achieved by using onsite or nearby energy generation from renewable energy sources.

In multi-story apartment buildings, the external wall constitutes the largest share of the building envelope area, rendering the additional insulation of external walls the most effective single renovation measure. This can significantly reduce heat loss and improve energy performance, Figure 4. While the roof and foundation also contribute to the building envelope and should be insulated during a deep renovation, their impact on overall energy performance is smaller when compared to external walls.

FIGURE 4

Table 1 presents the solutions for building envelope insulation with different heat sources for space heating, ventilation, and DHW to achieve different EPC classes. All EPC values reported in Table 1 were calculated for renovation scenarios that already include the transition from passive stack ventilation to balanced mechanical ventilation with heat recovery at ICC II, with SFP = 1.5 kW/(m³/s) and heat recovery efficiency of 80%. These solutions were selected for further examination concerning the necessary generation of on-site electricity from photovoltaic panels. Because EPC ‘B’ was not reached in the case of a gas boiler without PV panels, this heat source was not included in subsequent analyses. Results show that high insulation and efficient services are necessary for PEN.

The improvement of indoor climate (from ICC IV to ICC II) increases energy use due to the use of electricity for mechanical ventilation and the need to heat ventilated air. If standard usage was implemented and indoor air quality improved, primary energy consumption would rise by 22% (ICC III) or 28% (ICC II). The implementation of ventilation heat recovery (VHR) would reduce heating energy consumption by approximately 26%–27%. The reported increase in primary energy reflects the indoor climate and ventilation upgrade itself, whereas the EPC outcomes in Table 1 reflect the combined effect of envelope improvement, ventilation heat recovery, and heating system renovation.

3.3 Renovation and renewable energy integration for PEN

3.3.1 PV panel criteria

The neighborhood’s annual electricity needs total 4,943 MWh (41 kWh/(m²·a)) with efficient district heating (EffDH) as the primary heat source. Using a ground source heat pump (GSHP) increases electricity demand to 7,017 MWh (58 kWh/(m²·a)). Roof-mounted photovoltaic (PV) panels generate about 11 kWh/(m²·a) for four-story buildings, 7 kWh/(m²·a) for six-story buildings, and 5 kWh/(m²·a) for nine-story buildings, which is insufficient for an EPC ‘A' energy performance level in high-rise buildings. If PV panels were installed on all neighborhood roofs, the maximum output would be 752 kWp, generating 639 MWh (5.3 kWh/(m²·a)) annually.

PV panels can be installed on building facades, though electricity generation is lower due to orientation and shading from nearby buildings. The average PV electricity generation for all facades is 35 kWh/(m²·a). By utilizing all available facades, buildings can maximize solar energy capture year-round. Total on-site electricity generation from PV on roofs and facades in the neighborhood would be 4,142 MWh (639 MWh from roofs and 3,503 MWh from facades), as illustrated in Figure 5, covering 84% of EffDH electricity needs and 59% of GSHP needs with optimal insulation applied, although the majority of the PV panels perform in significantly suboptimal conditions in this scenario (reduction in generation >30%).

FIGURE 5

The electricity generation is 72% on the southern facade, 61% on the eastern facade, 55% on the western facade, and 28% on the northern facade, compared to the ideal orientation (south) and slope (40°). The self-consumed electricity produced by PV panels on the southern facade is 80%, 69% on the eastern facade, 67% on the western facade, and 39% on the northern facade, compared to ideal conditions.

At the neighborhood level, however, the surrounding buildings have additional influence on the solar exposure conditions for facade-integrated PV panels. Figure 6 illustrates the productivity of PV panels due to unfavorable orientation and additional shading effects (left) and the distribution of panels operating above and below 70% of the maximum panel productivity (right); 70% of the ideally installed (south orientation, 40° angle) PV system is set as an economically viable criterion according to the national regulations (RT I22.08, 2019).

FIGURE 6

As a deployment decision rule, surfaces operating below the ≥70% productivity threshold (relative to a south-facing 40° reference) are deprioritized or substituted by ground-mounted PV to maintain cost-effectiveness and grid-friendly self-consumption.

Table 3 presents the incremental electricity generation potential from PV panels installed on roofs and facades, and highlights the decrease in production caused by PV orientation and shading from neighboring buildings. To maximize total generation, solar panels are installed beginning with the most efficient location (the roof) and orientation (the south facade), progressing towards less efficient installations.

An alternative to the facade-integrated or adapted PV panels is installing them on the ground. Considering only the addition of the PV panels installed on rooftops, the land in the neighborhood needed to cover the total electricity required for lighting, household appliances, and building services would be 8.1 ha (61% of the neighborhood’s total land area) for EffDH and 11.9 ha (89% of the neighborhood’s total land area) for GSHP. When facade-integrated PV panels operating at >70% efficiency (compared to ideal installation) are added to the scenario, the additional land area for ground-installed PV would be 6.2 ha (EffDH) and 9.9 ha (GSHP), while 1.6 ha (EffDH) and 5.3 ha (GSHP) would be needed to cover the annual electricity demand of the entire neighborhood when all BIPV/BAPV are considered, corresponding to 12% and 40% of the total land area of the neighborhood.

3.3.2 Biomass and GSHP land criteria

To meet the neighborhood’s energy needs based on the PEN definition in terms of annual local or regional surplus production of renewable energy, the land requirements for biomass and geothermal energy were calculated.

Post-renovation (with the criteria provided in Table 1), the neighborhood needs 7,276 MWh/a (60 kWh/(m²·a)) on an annual basis for space heating, heating of ventilation air, and DHW, requiring 336 ha for biomass (energy bushes) based on a yield of 13 t/ha and a 3-year harvest cycle. Using the lowest thermal transmittances would help to reduce the land area needed to 263 ha. Notably, at best, this area is 20–25 times larger than the entire land area of the neighborhood.

As an alternative to efficient district heating, a GSHP with a horizontal collector field would require 23.1–29.4 ha of land area, depending on the renovation level, whereas a GSHP with vertical boreholes would require 7.4–25.6 ha, depending on borehole spacing. In parallel, the annual electricity balance in the GSHP case would require additional ground-mounted PV of 5.3 ha when all roofs and facades are used for PV generation, or 11.9 ha when only rooftop PV is considered.

These land areas should not be interpreted as mutually compatible on the same site in the horizontal GSHP case. The present analysis does not assume PV installation above the horizontal collector field. Therefore, horizontal GSHP collectors and ground-mounted PV must be treated as competing land uses, unless separate nearby parcels are available for one of the systems. This spatial constraint is particularly important in dense urban neighborhoods, where the land available between and around buildings is already limited.

Consequently, when both renewable heat and renewable electricity are considered within the PEN framework, the horizontal GSHP option places additional pressure on land use compared to efficient district heating or vertical borehole GSHP solutions. This supports the conclusion that PEN targets in existing high-density neighborhoods cannot be assessed only at the building scale but must also consider the spatial compatibility of renewable energy systems and the availability of nearby land.

Without deep renovation of buildings, biomass land requirements rise to 979 ha, with horizontal collectors needing 86 ha and vertical collectors requiring 28–75 ha, depending on borehole steepness.

3.4 Surplus production of renewable energy–strategies to achieve PENs

The peak heat demand for room heating, ventilation air, and DHW in the deeply renovated apartment buildings analyzed was 3 MW. Excluding this peak load, the heat demand during winter ranged from 2.0 to 2.5 MW (Figure 7). With seasonal performance factors (SPF) of 4.0 for heating rooms and ventilation air, and 2.7 for DHW, the peak electricity requirement was reduced to 0.8 MW.

FIGURE 7

PV electricity generation exhibits significant seasonal variation, peaking during the summer months and declining markedly during winter. On an annual basis, PV panels installed on roofs and facades with a productivity above 70% of the ideal orientation can cover approximately 34% (1,676 MWh) of the electricity demand for lighting, appliances, fans, and pumps in the EffDH case, where the annual electricity demand is 4,943 MWh (Figure 8, left). When PV panels are installed on all roofs and facades, the annual on-site PV generation increases to 4,142 MWh, which can supply 59% of the electricity required for room heating, ventilation air, DHW, lighting, and pumps (7,017 MWh) when a ground source heat pump (GSHP) is utilized instead of efficient district heating (EffDH) (Figure 8, right). However, these annual values do not describe the temporal match between generation and demand. When the simultaneity of PV production and electricity demand is considered, the neighborhood experiences both periods of electricity shortage and periods of overproduction. In the EffDH case, the simultaneous power balance indicates a shortage of up to 0.6 MW and a surplus of up to 1.2 MW when only PV panels with productivity above 70% are considered. In contrast, when PV is installed on all roofs and facades, the electricity shortfall rises to 2.3 MW, and the surplus also reaches 2.3 MW with GSHP.

FIGURE 8

In the scenario where all roof- and facade-mounted PV panels are included (Figure 8, left), there is a seasonal consumption deficit of 1,302 MWh during the cold and dark periods at the beginning and end of the year and a seasonal generation surplus of 2,382 MWh during the summer period. These values describe the temporal mismatch between electricity generation and demand and should not be interpreted as the annual net electricity balance of the neighborhood. The annual PEN balance is assessed separately against the total annual electricity demand. Since the maximum annual on-site PV generation (4,142 MWh) remains below the annual electricity demand in the EffDH case (4,943 MWh), additional nearby ground-mounted PV is still required to close the annual balance.

If PV panels are limited to installations meeting the regulatory productivity threshold of 70%, the winter deficit increases to 1,416 MWh, while the summer surplus decreases to 0.5 MWh, illustrating that stricter productivity criteria reduce summer overproduction but do not eliminate the winter mismatch. In the GSHP case (Figure 8, right), the seasonal mismatch is even stronger, with a winter deficit of 2,721 MWh and a summer surplus of 2,003 MWh when all roofs and facades are used for PV generation.

Therefore, the results indicate that achieving a PEN requires addressing both the annual balance and the seasonal mismatch of renewable electricity generation. In the present study, the annual balance can only be closed by adding renewable electricity generation beyond the building envelope, such as ground-mounted PV. Energy storage may reduce the temporal mismatch, and this should be investigated in future studies.

The surplus of PV electricity reduces self-consumption, which refers to the amount of energy generated from renewable energy sources (RES) that is used on-site (Figure 9, left). The decrease in self-consumption reaches a breakpoint at the level of nearly zero energy buildings (nZEB), specifically at an EPV of 100–105 kWh/(m²·a). Furthermore, the efficiency of PV generation productivity (compared to the ideal) also declines at this same EPV level (Figure 9, right).

FIGURE 9

In addition to installing solar panels on buildings, PEN status requires the installation of ground-mounted solar panels. To meet the total annual electricity needs of highly energy-efficient buildings—4,943 MWh for those with EffDH and 7,018 MWh for those with GSHP—the studied neighborhood will require additional photovoltaic (PV) panels on the ground: 1,000 kWp for EffDH and 3,313 kWp for GSHP, assuming all roofs and facades are covered with BIPV/BAPV panels. This would necessitate additional land areas of 1.6 ha and 5.3 ha, respectively.

If only rooftop panels are installed, the neighborhood will need additional ground-mounted PV panels of 5,062 kWp for EffDH and 7,438 kWp for GSHP, corresponding to land areas of 8.1 ha and 11.9 ha, respectively, which is nearly equivalent to the total land area of the neighborhood.

Table 4 provides a summary of the additional land required to achieve PEN status through the deep renovation of high-rise buildings in a high-density neighborhood in cold climates.

4 Discussion

Despite individual variations in measured and calculated energy consumption (standard use), their average difference was negligible. Existing apartment buildings often do not satisfy indoor climate requirements (Mikola et al., 2017) according to standard EN 16798-1 (2019), and water and electricity usage patterns (Hamburg and Kalamees, 2018) deviate from the building stock average established as the standard use of buildings in national regulations (RT I22.08, 2019). Improvement of indoor climate, mainly due to insufficient ventilation airflow, is needed, thus increasing the electricity used in mechanical ventilation (Hamburg et al., 2025).

Our findings are consistent with those of other studies that highlighted the challenges and potential of achieving PENs in high-rise, densely occupied urban environments. Nematchoua et al. (2021) demonstrated that more than 90% of current energy consumption can be reduced at the neighborhood scale through intensive renovation of all buildings, electric vehicles, and PV panels to reach the nZEB target at the neighborhood scale. Bossi et al.’s (2020) analyzed of 61 PED projects in Europe showed that the integration of PED solutions into existing urban structures remains a crucial long-term challenge. Additionally, Pan and Pan (2021) found that geographical restrictions significantly hinder the development of renewable energy for zero-carbon buildings in high-rise, high-density cities.

On-site energy generation has become a crucial technical factor in achieving PEN. We have proven that merely integrating or adapting PV systems into buildings is insufficient for meeting the electricity needs of appliances, lighting, fans, and pumps in high-rise buildings located in high-latitude locations. Our analysis suggests that generating electricity within the neighborhood using solar panels on rooftops and facades can guarantee three-quarters of the electricity needed for appliances, lighting, pumps, and fans in the case of EffDH and close to half in the case of GSHP. In Switzerland, neighborhoods with many apartment buildings, especially high-rise apartment buildings, do not achieve PEN and remain net consumers due to limited PV capacity and greater demand (Michellod et al., 2025). In Paris, electricity consumption covered by PV panels compared to total consumption was only 27% in the outskirts and 11% in the center of the city (Tao et al., 2025). Similarly, in positive energy districts in Southern Italy with biomass district heating (Volpe et al., 2022), the inclusion of PV panels and their distribution amongst connected buildings does not completely offset the intermittent nature of solar energy. Currently, electricity from renewable sources rarely exceeds 20% of energy production and consumption in cities (Ulpiani et al., 2023).

PV energy generation exhibits significant seasonal variation, particularly in cold climate regions. During the colder months, shorter days and lower solar intensity lead to a substantial decrease in PV output, while the demand for heating peaks. Consequently, other renewable energy sources are necessary during this time in cold climates, which may require accepting a reduction in land-use efficiency. Böhm (2023) demonstrated that the average electricity yield per hectare is 28 times higher with a PV system than with biogas, and that 54 times more heat can be generated per hectare with a PV system than with woodchip production from short-rotation plantations. Dijkman and Benders (2010) found that the energy density of solar electricity is over 40 times greater than that of biomass. Because biomass has a low energy density, its transport distances should be minimized (Searcy et al., 2007). Therefore, PENs must consider renewable energy produced on the ground, not just on buildings in the neighborhood, as the area of buildings alone is insufficient to define a PEN.

A key finding of this study is that annual electricity balance and seasonal electricity mismatch must be treated separately when evaluating PEN feasibility in cold-climate high-rise neighborhoods. Although PV generation can create a considerable summer surplus and a corresponding winter deficit, this does not mean that the neighborhood reaches a positive annual electricity balance. In the present case, even the maximum annual PV generation from all roofs and facades (4,142 MWh) remains below the annual electricity demand of the deeply renovated neighborhood in the EffDH case (4,943 MWh). Thus, substantial temporal overproduction in summer does not remove the need for additional annual renewable electricity generation, which in this study is represented by ground-mounted PV.

This distinction is particularly important in Nordic and Baltic climates, where the seasonal mismatch between solar availability and heating-related electricity demand is strong. During the winter period, PV output is low when demand is highest, whereas during summer, electricity generation may exceed the instantaneous and short-term neighborhood demand. Consequently, the challenge is not only to produce enough renewable electricity annually, but also to manage the timing of production and consumption.

In this study, storage was not modelled as a mitigation measure and therefore is not included in Table 4. However, the results clearly indicate that storage could be relevant in future work for reducing imports during winter deficit periods and exports during summer surplus periods. Even so, in the present neighborhood, storage alone would not remove the need to distinguish between seasonal balancing and annual PEN compliance, because the maximum on-site annual PV generation is still insufficient to cover the full annual electricity demand.

While facade-mounted PV in dense high-rise contexts faces reduced productivity due to shading and non-optimal orientations, several strategies can improve net yield and self-consumption without extensive land take. First, prioritizing surfaces that meet the ≥70% productivity threshold (relative to south-facing, 40° tilt) and reallocating sub-threshold capacity to ground-mounted PV within or near the neighborhood helps to maintain cost-effectiveness, this aligns with urban PV studies that rank surfaces by irradiance/morphology and recommend productivity-based siting (Liu et al., 2023). Second, module-level power electronics (e.g., optimizers/micro-inverters) reduce mismatch losses under partial shading (Liu et al., 2023). Third, combining south with east–west arrays on rooftops broadens the daily generation profile and improves overlap with demand (Formolli et al., 2023). Fourth, façade selection should favor well-exposed balconies/parapets and light-colored/bifacial-suitable surfaces to enhance irradiance and albedo gains where feasible. Fifth, modest tilt adjustments and avoiding near-field obstructions (e.g., setback from parapets) reduce edge shading. Parapet walls are consistently identified as a rooftop PV constraint (Ghaleb and Asif, 2022). Finally, demand-side management and short-term storage can shift mid-day surpluses to evening peaks, improving self-consumption at the building and district scale (Liao et al., 2024). Together, these measures complement our threshold-based placement approach and support productive PV deployment in constrained urban morphologies.

5 Conclusion

The land area available for renewable energy generation is significantly limited without extensive renovations to buildings. To reduce the demand for heat and electricity, it is essential to minimize energy consumption. This can be achieved through additional thermal insulation of the building envelope, particularly the facades, and the implementation of efficient technical service systems. This supports the initial assumption that for a Positive Energy Neighborhood (PEN), building envelopes must be highly insulated and equipped with highly efficient service systems. Comprehensive planning at both the building and neighborhood levels is crucial; otherwise, achieving the goal may necessitate measures that are not cost-effective and could require excessively high investments.

Relying solely on on-site building photovoltaic (PV) systems is insufficient; unfavorable orientations and shading lower productivity and self-consumption. To achieve a PEN, it is necessary to install significantly more PV panels than is currently required for nearly Zero Energy Buildings (nZEB, EPC “A”) or for major renovations (EPC “C”). However, the maximum total on-site electricity generated by adapted or integrated PV panels on the roofs and facades of the neighborhood’s buildings is still inadequate to meet the annual net electricity needs of the area. To reach PEN levels, on-site electricity generation from renewable sources must involve installing PV panels in less favorable orientations and/or shaded areas, which further reduces self-consumption and renewable electricity productivity. This supports the validity of the second assumption.

Transforming high-rise apartment neighborhoods in cold climates into PEN is technically feasible but presents significant challenges. A large area of land is required to generate electricity and heat from renewable energy sources. Key challenges include substantial improvements to building envelopes, effective energy storage solutions, indoor climate requirements, addressing the seasonal imbalance between energy generation and demand, and optimizing the placement of photovoltaic (PV) panels. By utilizing all available facade and roof surfaces for PV installation and incorporating advanced energy management systems, it is possible to move closer to achieving PEN status. Achieving an annual PEN balance requires renewable electricity and heat generation beyond the building footprint and, in most cases, beyond the neighborhood area itself; additional land is therefore necessary for renewable energy production This supports the third assumption that the size of the neighborhood must be expanded by adding land dedicated to heat and electricity production from renewable sources alongside the area occupied by existing buildings equipped with PV panels. A concise mapping between the research assumptions and the quantified findings is provided in Table 5 to make the main implications of the study explicit.

The results of this analysis underscore the necessity for ongoing research and development to enhance the technologies and strategies employed in neighborhood-integrated renewable energy systems. Future work should prioritize improving the efficiency of PV panels under less favorable conditions, boosting energy storage capacity, and creating innovative solutions for energy distribution and management. By concentrating efforts in these areas, we can develop resilient and sustainable urban environments that satisfy the energy needs of their residents while minimizing environmental impact. Additionally, future research should focus on creating integrated solutions that merge technological, financial, social, ecological, and urban planning strategies to support the transition to a PEN.

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