1. Introduction
The intensively growing global population affects the supply and demand of food, fuel, consumer goods, services, and natural resources. According to a new UN report, the current world population of 8.1 billion [
1] is expected to reach 8.6 billion by 2030, 9.8 billion by 2050, and 11.2 billion by 2100 [
2]. At the same time, the global urban population continues to grow, putting enormous pressure on urban infrastructure, resource management, and global energy consumption [
3]. Urban areas account for a disproportionately large share of global energy consumption, approximately two-thirds [
4]. With increasing urbanization, it is projected that by 2050, nearly 70% of people will live in urban areas, which will inevitably lead to further increases in energy consumption and demand, highlighting the urgent need for sustainable energy systems in the urban environments [
5].
In this transition towards sustainable energy systems, energy communities have emerged as key players, pivotal actors in the decentralized renewable energy adoption. These communities are organizations that facilitate collective ownership and participation in various energy-related activities [
6]. Also, they enable local communities; stakeholders, such as individuals and businesses; and public authorities to collaborate and invest in clean energy [
7]. This will contribute to a more resilient and efficient electricity grid. These collective energy-related actions are coming to the fore today as they play a key role in achieving a more sustainable and socially equitable energy infrastructure [
8].
Although there are efforts to adopt this emerging concept, the overall development of the country remains low in terms of public awareness and confidence in energy communities. The historical dominance of large, state-owned energy utilities contributes to skepticism when it comes to community initiatives. Despite the potential of energy communities, several barriers, including financial constraints, lack of awareness, technological limitations, and weak government involvement, make adoption difficult and hinder public participation.
The aim of this study is to comprehensively assess public awareness, perceived benefits, barriers, and willingness to engage in energy communities in Romania, based on a nationwide survey. This study also aims to identify socio-demographic differences in perceptions and participation through statistical analysis, with the aim of informing policy-making, improving communication strategies, and supporting the inclusive development of decentralized renewable energy systems. Furthermore, this study fills a gap in the literature by offering one of the first empirical assessments of public opinion on energy communities in Romania and participation in these communities. This is achieved by providing a localized insight using quantitative data and statistical analyses, highlighting demographic differences and providing information on emerging renewable energy initiatives.
2. Background and Analytical Context
2.1. Legislative Framework at Global and EU Levels
Over the past few years, several initiatives have been developed that play a crucial role in promoting energy efficiency and sustainable energy sources worldwide. Firstly, the United Nations (UN) Sustainable Development Goal (SDG) 7 emphasizes access to affordable, reliable, sustainable, and modern energy for all people around the world. Furthermore, SDG target 7.3 states that global energy efficiency improvements should be doubled by 2030 [
9]. These goals highlight the increasingly important role of communities and individuals in contributing to the energy transition.
At the European Union (EU) level, legislative and policy frameworks have been designed to promote energy efficiency in various sectors and facilitate active citizen involvement. The Ecodesign Directive (2009/125/EC) [
10] and the comprehensive Energy Efficiency Directive (2012/27/EU) [
11], revised in 2018 [
12] and 2023 [
13], establish ambitious targets and national obligations to reduce the environmental impact of energy-related products throughout their life cycle and improve energy efficiency. The most recent revision, Directive (EU) 2023/1791 [
13], sets a legally binding goal of increasing energy efficiency efforts by at least 11.7% by 2030 compared to the level of effort under the EU 2020 reference scenario. These targets not only require structural and policy-level changes, but also call for increased public awareness and participation, as behavioral shifts are essential for achieving such goals.
In addition, the Clean Energy for All Europeans initiative sets the stage for citizen-driven energy transitions by supporting the development of energy communities across the EU [
8]. These communities are central to the EU’s vision for a decentralized and inclusive energy future. The European Energy Communities Facility, another EU-funded initiative, supports the creation and expansion of at least 140 energy communities across Europe, including in EU Member States, plus Iceland, Moldova, Northern Macedonia, and Ukraine [
14]. This support includes funding and customized capacity-building programs to help communities establish viable and participatory energy models.
Defined by the European Commission as key actors in the green transition, energy communities promote increased energy efficiency [
15] and align with the circular economy principles [
16]. The Renewable Energy Directive (2018/2001/EU) [
17] further reinforces this participatory approach by setting a 32% renewable energy target by 2030 and introducing measures that empower citizens to produce, consume, and share renewable energy within community structures [
18]. This legal recognition of renewable energy in energy communities underscores the EU’s commitment to encouraging public participation and transforming perceptions of energy consumption, from passive use to active participation.
2.2. Regulatory Framework and National Development in Romania
Understanding the factors influencing the willingness to take such initiatives is key for policy-makers, government, academics, and energy stakeholders to enable them to act and support such energy initiatives. According to Eurostat, the average share of renewable resources in the EU in 2014 was 17.416%, while in Romania it was 24.845%, putting Romania well above the EU average, with a difference of 7.429%. However, in the latest available year, 2023, the EU average was 24.554%, increasing by 7.138% in 9 years, while in Romania it was 25.757%, increasing by only 0.912% [
19]. This shows us that the EU is making strong progress in renewable energy, while Romania has barely progressed, closing the gap by only 1.203%. This is because Romania relied on old, large, and state-owned infrastructures, most of which were built during the communist period between 1950 and 1990. During this period, several 115 hydropower plants were built, including the largest Romania has [
20].
Comparative studies of post-socialist EU countries help to place the challenges facing Romania’s energy sector in a broader European context. For example, the comparative research on Romania and Poland highlights how different paths of governance and institutional reforms have led to different outcomes in the energy transition, with Poland achieving faster progress thanks to stronger regulatory frameworks and market liberalization [
21]. Similarly, studies comparing Romania with Hungary and Bulgaria highlight the common legacy of centralized infrastructure and a lack of public trust in privatization processes, which together have hindered public participation in renewable energy initiatives [
22,
23].
In addition to the infrastructure, the market was also under state control until 1989, when the first economic reforms, together with privatization, attempted to adapt the system to the market. Initially, the entire infrastructure was inherited by a single entity, the “Autonomous Electricity Authority (RENEL)”, but in 1998, with government decree 365/1998, the liberalization process began [
24]. Several private companies came to buy parts of the once complete system. This period is remembered by the collective Romanian population as the time when the country was sold off cheaply to foreigners for the benefit of those in charge. This type of action also affected the energy sector: in 2004, resources such as oil and gas were sold to the Austrian OMV. According to a study, by 2006, 17 years after the regime change, Romania had 63 producers (partly regulated), 1 mainly state-owned energy transmission company (Transelectrica), 1 state-owned market operator, 8 distribution networks (5 private), 104 suppliers, and 8.6 million consumers [
25]. The population was used to having energy supplied and delivered to their homes by these entities, and many were not aware that they could participate in energy-related activities.
Even after Romania’s energy market was declared fully open in 2007, the system proved to be inefficient. A large proportion of consumers remained in the regulated sector, where market segment prices were artificially kept low for social and political reasons [
26]. These manipulated prices did not reflect the true costs of energy production, transmission, and distribution, thereby discouraging effective competition and, crucially, public engagement in energy-related activities. The specific, and often controversial, methods of privatization in the post-socialist era, particularly the public perception of assets being “sold off cheaply”, directly eroded public trust in market mechanisms and institutional actors. The historical legacy of centralized energy systems, rapid privatization, and distrust of institutions appears to influence current public skepticism towards community-based energy initiatives. The results of the survey used in this research reflect this dynamic, with respondents highlighting obstacles such as a lack of government support, complex permitting procedures, and limited public awareness, all of which may stem in part from persistent distrust of institutions and a lack of knowledge about participatory energy models.
In 2007, Romania joined the European Union and had to transpose the EU energy policy, which at that time focused on the creation of a competitive internal energy market, given the demand for green energy and the continuous increase in the efficiency of the energy sector [
26]. Efforts to transpose the third EU energy regulatory package, National Law 220/2008, which aimed at “expanding the legal framework for renewable energies” [
27], and also introduced a green certificate system. This was later followed by Law 123/2012 on electricity, and natural gas has been amended for 2020 and 2021 with regard to electricity generation from renewable energy sources. It strengthened the role of the National Regulatory Authority (ANRE) by giving it greater control over the regulation of energy-related activities [
28]. It also facilitated the phasing out of regulated prices, reinforcing the transition towards a decentralized energy sector. Government emergency ordinance (OUG) No. 143/2021 was amended due to an incorrect and incomplete translation of European Directive 2018/2001 on renewable energy and energy communities [
29]. This existing legal framework was not considered effective. As a result, Romania faced infringement procedure 2021/0333 for non-compliance with EU Directive 2018/2001, for failing to transpose the Directive into OUG 143/2021, promote the use of renewable energy, and facilitate the creation of energy communities. In response to this issue, the Romanian government issued OUG 163/2022, which attempts to create a better legal framework for energy communities and promote the use of renewable energy sources [
30,
31]. This OUG attempted to define their activities and rights and facilitate their existence by removing unnecessary bureaucratic obstacles, and at the time of writing, it is still the main legal framework. Romania currently has an Energy Strategy Plan for the period 2025–2035 to 2050, published in November 2024, which sets out clear objectives for the future. Energy education needs to be implemented on a mass scale [
32], so the knowledge of the problems of the Romanian masses is key to take action to achieve the targets set. It is also important to examine how social factors encourage or hinder individuals from participating in energy communities. One energy community guide noted that “the more people know about energy issues, the more likely they are to support renewable technologies” [
33].
In terms of funding mechanisms, the above-mentioned National Law 220/2008 introduced tradable green certificates, rewarded for each MWh generated from renewable sources and delivered to the grid [
34]. It was approved by the EU after some revisions in 2011 by Decision No. 4938/2011. This system created a separate market where green certificates were sold, independent from the energy market [
35]. This generated a lot of investment in the renewable energy sector from the private sector. But the system was not open on a smaller scale to the general population. People who wanted to access these certificates and to be able to produce and supply electricity to the grid had to be licensed as a supplier by ANRE. It was only with Law 184/2018 that there was a legal basis for the decentralization of electricity production at a smaller scale [
34], introducing the concept of “prosumer”. A prosumer is a distribution grid user who both consumes and produces or stores energy, such as households with self-generation systems [
36].
In addition, Romania is committed to the EU’s climate goals and promoting change in the energy industry is of high importance; therefore, raising awareness and changing policies can have a positive impact, which increases the positive attitude of consumers towards the use of renewable energies [
37]. In 2019, ANRE launched the Photovoltaic Greenhouse Program (Casa Verde Fotovoltaice), which aims to finance the purchase and installation of photovoltaic panel systems that use renewable, non-polluting energy sources for the production and use of electricity by consumers connected to the national electricity grid, by the Administration of the Environment Fund (AFM) [
38]. The beneficiaries of the program have been involved in four sessions so far: the first in 2019, the second in 2021, the third in 2023, and the last one in 2024. These beneficiaries in 2019 and 2021 were all private individuals who were eligible to receive support for household-scale photovoltaic systems. And in 2023, a specific call for tenders for photovoltaic systems for religious institutions (Unitate de Cult) has been launched [
39]. In general, aid can be granted up to a maximum of RON 20 000, with a contribution from the beneficiary of RON 2000 [
40] and has so far financed 90% of the solar infrastructure for the population [
41]. In addition, this program has made it increasingly accessible for people to act and own their own solar energy infrastructure, and at the time of writing, it is still working. Romania is also trying to access European funds through programs such as the National Recovery and Resilience Plan (PNRR), approved in 2021 [
42], which aims to “better prepare Romania for the challenges and opportunities of the green and digital transition” through significant European funds [
43].
3. Materials and Methods
3.1. Research Approach
This study applied a quantitative research approach to explore public perceptions and engagement with energy communities.
We used a publicly available online survey to collect data from a larger number of Romanian respondents for two main dimensions: (1) the demographic profile of respondents and (2) their perceptions of energy communities. The latter included attitudes about perceived benefits and barriers, current level of participation, awareness of the concept, willingness to participate in future energy initiatives, willingness to invest, and other related factors.
3.2. The Sample
The data were gathered through the online survey, which was accessible for less than a year, from the 30th of June 2024 to the 5th of April 2025. In total, 16 items specifically addressed perceptions of energy communities, supplemented by items capturing additional demographic information. Items related to energy communities are presented in
Table 1.
The sample consisted of 213 respondents; after analyzing the responses, 118 questionnaires that had valid responses were validated and used in this research. The collected data were gathered from 118 respondents and allowed for a comprehensive statistical analysis to identify patterns, trends, and correlations of public engagement with energy communities. However, the sampling process was based on voluntary online participation, and the criteria for selecting valid responses were limited to the completeness of the responses. This approach may limit the representativeness of the results. Due to Romania’s current digital divide and inequalities in internet access between regions and socio-economic groups, certain demographic groups—especially those living in rural areas, older age groups, or those with lower incomes—may be underrepresented. In addition, the voluntary nature of the survey may have caused self-selection bias, with people who are more interested in or knowledgeable about energy issues being more likely to participate in the survey. Although the sample included respondents from all four Romanian macro-regions, and the proportions of genders, age groups, and educational attainment were balanced (see
Table 2 for details), these limitations call for caution when generalizing the results to the entire Romanian population. In future research, it is worth considering the use of stratified or random sampling methods and mixed data collection methods to better cover the diversity of public opinion and ensure more reliable representativeness.
3.3. Data Analysis
The gathered data were processed digitally using custom Python scripts 3.10. It consisted mainly of categorical variables and ordinal Likert-scale responses, encoded numerically. Questions included single-choice, matrix single-choice, and open-ended formats. The data, stored in a matrix, were processed in Python with Pandas, SciPy, seaborn, matplotlib, and NumPy. Each row represents a survey response and each column a question. Using a Pandas Data Frame allowed counting values, calculating statistics, and printing results with basic functions.
The printed results were then plotted using the matplotlib and seaborn libraries, to have a better visual understanding of them. Descriptive statistics were applied as well, calculating the mean and mean deviation of the responses, along with the Mann–Whitney U-test. The same test used in other studies in the same field [
44] to assess statistical differences and compare the distributions of the responses. The Mann–Whitney U-test was used to compare two groups and determine whether one group had higher or lower scores than the other. The test produces a U-value that tells you how much the two groups overlap. A lower U-value means that the groups are more different from each other, which supports the research hypothesis (H1) that there is a real difference between the groups. On the other hand, a larger U-value means that the groups are more similar, which supports the null hypothesis (H0) that there is no significant difference [
45]. Also, the
p-value is a number that shows the probability of the results if there is indeed no difference between the groups (the null hypothesis is true) [
46].
The tests were performed to assess the differences between the rural and urban areas, both genders, and the ones involved and not involved in the energy communities. This open source programming language enabled us to create and run multiple scripts in a single Jupyter notebook project, collecting everything efficiently. The results gathered by the survey and processed by the scripts are presented in this paper.
4. Results
Following data processing using the above analytical techniques, we identified the public perception of energy communities. The results presented in the tables below show the average scores calculated for each survey item within the relevant questions. Items are ranked in descending order of average scores. Since the survey used a Likert scale, the average score reflects the average level of agreement or importance assigned by respondents to each item.
In addition to the mean, the most frequently chosen response level is also highlighted, along with the percentage of respondents who chose it. A higher percentage indicates greater agreement among respondents, suggesting that opinions cluster around a particular response level.
To assess the variability in the responses, the mean absolute deviation was calculated. A lower mean absolute deviation indicates a greater agreement between participants, with responses concentrated near the mean. In contrast, a higher mean absolute deviation indicates greater variance and lower consensus on a given item.
Table 3 shows that solar energy is the most popular renewable energy source, with 68.64% of respondents rating it as “very important”. The response to this question also showed a low mean absolute deviation, indicating a high level of agreement among respondents. Wind energy closely followed, also with a high mean score and relatively clustered responses. In contrast, hydropower, biomass, and geothermal energy received lower average scores, indicating that they are relatively less highly regarded by the public. These renewable energy sources showed more dispersed response patterns, with scores around level 4 on the Likert scale and a lower percentage of respondents choosing the highest importance, reflecting greater diversity of public opinion.
In
Table 4, the results are presented on the perceived benefits of energy communities. The highest ranked benefit was environmental impact, with nearly 50% of respondents giving it the maximum importance (level 5), resulting in a mean score of 4.08. This was closely followed by technological innovation and reduced energy costs, both with average scores above 4 and a strong concentration of responses for the highest level of importance. For greater energy independence, the responses were evenly split between levels 4 and 5, resulting in a mean score of 3.96 and a relatively low absolute deviation, indicating a high degree of consensus on this value. In contrast, job creation and community responsibility were the lowest rated benefits. It is noteworthy that the number of respondents who ranked job creation at level 5 was the same as those who ranked community responsibility at level 4. This distribution suggests that these two aspects are considered less critical compared to environmental and economic benefits.
In terms of perceived barriers,
Table 5 shows that insufficient funding is perceived as the most significant barrier to the development of energy communities. Nearly half of the respondents identified this as a significant barrier, reflected in a mean score of 4.09 and a mean absolute difference of 0.88, indicating a medium level of agreement among respondents. A slightly lower mean score of 4.06 with a mean deviation of 0.67 indicates a stronger agreement that lack of government support is also a critical barrier. In contrast, limited access to technology within communities was rated as the least significant barrier, with a lower mean score and a greater variance in responses, indicating lower agreement. High upfront costs and low community awareness were rated as moderately important barriers, both with mean scores below 4 and moderate agreement among respondents.
Table 6 shows respondents’ perceptions of the importance of different potential regional strengths. Favorable climatic conditions received the highest mean score of 4.11, indicating a high level of importance, accompanied by a relatively low mean variance of 0.68, indicating a strong consensus among respondents. This finding may help to explain why solar energy is the most favorable renewable source, followed by wind. Strong community support was found to be the second most valuable strength, with a mean score of 3.96, highlighting the importance of local engagement in promoting renewable initiatives. In contrast, the availability of a qualified work force was rated as the least important, indicating a possible lack of education and training in the renewable energy sector. This highlights the need to further develop local capacity building and skills development programs to better support the transformation of the energy sector.
Table 7 presents the main opportunities identified to promote renewable energy, starting with “interest in the development and use of renewable energy”, which received the highest mean score of 4.24, indicating strong support and relatively high consensus among respondents—more than half of them chose the highest response (level 5). Educational programs were also considered very important, with a mean score of 4.16, closely followed by technological innovation with a mean score of 4.15. The most concentrated pattern of responses was observed for the item “private sector partnerships”, which had the lowest mean deviation of 0.68 and a mean score of 4.02, reflecting participants’ perceptions of high importance and strong agreement. In contrast, government subsidies and incentives were rated the lowest of the options listed, despite response levels 4 and 5 receiving 37.29% of the responses, suggesting that perceptions of their importance are more evenly distributed.
Table 8 shows the perceived impact of several gaps identified at regional level. Of these, high initial costs was the most significant barrier, with a mean score of 4.08. When assessed at the general level, this issue scored slightly lower, with an average score of 3.87, indicating that the perception of barriers is more pronounced in the local context. Regulatory challenges showed the highest level of agreement among respondents, as reflected by a mean deviation of 0.76 and a mean score of 4.03, indicating both a high level of perceived impact and a high level of agreement. Similarly, the issue of limited sources of funding was rated with a mean score of 4.01 and a mean deviation of 0.79, indicating the unanimous perception of the importance of the issue. Lack of technical expertise showed a similar level of agreement (mean deviation of 0.78), although it was rated as lower in importance with a mean score of 3.86. The same mean score (3.86) was observed for insufficient public awareness, but with a higher mean difference (0.87), indicating a greater diversity of respondents’ opinions and lower consensus on the perceived impact.
Table 9 analyzes the perceived regulatory and policy barriers, with the most significant problem identified being complex authorization processes; 41.53% of respondents rated this barrier as a significant impact, resulting in aa mean score of 4.04. This was closely followed by the lack of incentives, which resulted in a mean score of 4.03. This was followed by an unfavorable regulation, which was characterized by the most compact distribution of responses and a mean score of 4.00, indicating a high degree of agreement among respondents. Bureaucratic barriers were rated the least influential in this category.
The assessment of potential opportunities was carried out at regional level, as detailed in
Table 10. Among the factors assessed, the availability of renewable resources received the highest average score of 4.04, with 41.37% of respondents indicating a maximum Likert level of 5. In contrast, founds and subvention resulted in a more balanced distribution of responses, with 37.29% indicating a level 4 and 37.27% indicating a level 5, resulting in an average score of 3.98. These results suggest that the availability of renewable resources and access to financial support are considered the most important opportunities in the regional context. On the other hand, the interest and implication of the community received the lowest mean score of 3.79, indicating that opportunities for collective engagement and participation at the community level were perceived to be relatively lower.
From a technological point of view,
Table 11 presents the most important items and their corresponding statistical values. High maintenance costs were the most significant concern, with a mean score of 3.93 and a relatively low mean deviation of 0.72, indicating a high level of agreement among respondents. It is noteworthy that 37.29% of respondents rated this item as a 4 on the Likert scale, indicating a widely shared view that significant operating costs persist, even after the initial installation of the equipment. The limitations of energy storage followed closely behind, with a mean score of 3.88 and a mean deviation of 0.71, also reflecting a high level of agreement. Similarly, the lack of technical expertise was also identified as a key challenge, with a mean score of 3.87 and a mean deviation of 0.72. These three elements showed high mean scores and low variance, indicating that they are seen as the most significant technological barriers to the development of energy communities. Other technological concerns, such as technological reliability and problems related to the grid integration, received lower mean scores but were still considered important, highlighting their importance in the broader context of technology challenges.
Also,
Table 12 summarizes the perceptions of threat from a variety of factors, with economic instability proving to be the most significant threat, with the highest mean score of 3.95, indicating widespread concern about the financial challenges facing individuals. The changes in government policy followed closely with a mean score of 3.90, reflecting uncertainty about regulatory frameworks. Mean scores declined gradually for the other items, with the lowest mean score of 3.47 being public opposition. It is noteworthy that public opposition also had the lowest level of agreement, with a mean deviation of 0.97, indicating a higher degree of variability in responses. This may indicate that public opposition is not yet seen as a critical barrier, possibly because public engagement with energy communities is limited at this stage, or because more immediate economic and political concerns take precedence.
5. Discussion
To examine perceptual differences between key demographic and involvement subgroups, a series of non-parametric analyses were conducted using the Mann–Whitney U test. This statistical approach is suitable for comparing two independent groups when assumptions of normality are not met. Data were processed using custom Python scripts, where subgroups were defined based on three categorical variables: residence (urban vs. rural), participation in energy initiatives (involved vs. not involved), and gender (male vs. female).
5.1. Differences Between Urban and Rural Residents
The analysis revealed statistically significant differences between urban and rural respondents for several questions. Urban respondents consistently reported higher mean scores on key dimensions related to energy communities. Urban participants rated significantly higher economic factors, including lower energy costs (U = 643.50, p = 0.0004; urban mean 4.22, rural mean 2.80), increased energy independence (U = 637, p = 0.007), and new job creation (U = 560.50, p = 0.0276). Similarly, environmental and social motivations also showed significant differences, where environmental benefits (U = 656.00, p = 0.002), community responsibility (U = 674.00, p = 0.001), and community interest and implication (U = 624.00, p = 0.0016) were all rated significantly higher by urban respondents.
Technical and institutional barriers were also rated more critically by urban residents. Items such as lack of founding (U = 545.00, p = 0.0382), insufficient governmental support (U = 556.50, p = 0.0277), and complex authorization processes (U = 557.00, p = 0.0233) were rated higher by the urban group. Technology concerns followed the same trend, including technological reliability (U = 599.00, p = 0.0052) and energy storage limitations (U = 563.00, p = 0.0227).
In total, 34 items showed statistically significant differences between urban and rural groups (see all in
Appendix A). These ranged from broad drivers, such as favorable climatic conditions (U = 654.00,
p = 0.0002) and technological progress (U = 607.50,
p = 0.0033), to barriers, such as regulatory challenges (U = 575.50,
p = 0.0134) and public opposition (U = 595.50,
p = 0.0073). Urban populations seem to be more critical of both the potential and the limitations of energy communities’ development, probably due to their greater exposure to sustainability discourse, infrastructure, or energy policy initiatives in urban environments.
5.2. Differences Between “Involved” and “Not-Involved” Respondents
When comparing those involved in energy communities or energy-related projects with those not involved, several significant differences were revealed. Involved respondents were more strongly in favor of institutional and societal incentives, such as favorable government policies (U = 1254.50, p = 0.0404), strong community support (U = 1258.00, p = 0.0361), and government subsidies and incentives (U = 1238.00, p = 0.0452).
Greater importance was attached to funds and subventions (U = 1274.50, p = 0.0256) and perceived barriers, such as limited funding sources (U = 1288.50, p = 0.0193) and high upfront costs (U = 1246.00, p = 0.0426). This group also evaluated technological innovations (U = 1246.50, p = 0.0322) and the growing public interest in sustainability (U = 1247.50, p = 0.0416) more highly than the non-involved respondents, suggesting that they are more deeply engaged with the systemic challenges and opportunities associated with the local energy communities.
5.3. Differences Between Male and Female Respondents
The gender-based comparison showed significant differences in both the perception of barriers and facilitators associated with energy communities. Female respondents rated several institutional and technical barriers significantly higher than male respondents, including lack of founding (U = 1284.00, p = 0.0275, male mean is 3.87 and female mean is 4.24), insufficient governmental support (U = 1302.00, p = 0.0366, male mean is 3.85 and female mean is 4.19), limited funding sources (U = 1224.00, p = 0.0117, male mean is 3.67 and female mean is 4.22), and lack of technical expertise (U = 1110.00, p = 0.0016, male mean is 3.48 and female mean is 4.10).
Also, they expressed greater concerns about problems related to the grid integration (U = 1208.00, p = 0.0100; male mean is 3.37 and female mean is 3.90), technological reliability (U = 1247.50, p = 0.0184; male mean is 3.43 and female mean is 3.88), and unfavorable regulations (U = 1260.00, p = 0.0210; male mean is 3.74 and female mean is 4.17). These results suggest that female respondents may perceive greater systemic challenges in implementing and managing the local energy communities.
In addition, women scored higher for incentive factors, such as interest and implication of the community (U = 1311.50, p = 0.0475; male mean is 3.57 and female mean is 3.93) and local governmental support (U = 1168.00, p = 0.0048; male mean is 3.52 and female mean is 4.15), which may suggest that the attach greater importance to collaborative and institutional support mechanisms. Perceived economic instability (U = 1244.50, p = 0.0171; male mean is 3.65 and female mean is 4.14), changes in government policy (U = 1253.00, p = 0.0197; male mean is 3.59 and female mean is 4.10), and public opposition (U = 1234.00, p = 0.0161; male mean is 3.13 and female mean is 3.69) also gave rise to greater concerns among women.
In conclusion, urban and involved respondents in general rated the benefits of energy communities higher, while women expressed greater concern for institutional, financial, and technological barriers. These differences highlight the need for customized policy communication and engagement strategies that address the specific concerns and motivations of different population groups. Furthermore, increasing awareness and access in rural areas can be the key to equitable local energy community’s development and participation.
In the Romanian context, the successful deployment of energy communities faces a combination of financial, regulatory, and institutional challenges that directly influence public perception and willingness to participate. The barriers most frequently reported by survey respondents—including lack of funding, insufficient government support, complex and incomplete regulatory frameworks, high upfront investment costs, bureaucratic hurdles, and policy instability—reflect both structural and procedural gaps in the national energy governance system. Addressing these challenges requires targeted, coherent policy interventions that simultaneously simplify administrative procedures, provide stable and predictable incentives, and offer financial mechanisms tailored to the specific needs of community-led projects.
Table 13 summarizes the key barriers identified and the corresponding policy recommendations that could enhance the viability, scalability, and social acceptance of energy communities in Romania.
Also, the respondents who were already involved in an energy community perceived several potential opportunities and strengths more positively compared to those not yet engaged. Specifically, they expressed a stronger agreement on the environmental benefits of reducing greenhouse gas emissions, the potential for financial savings through lower energy bills and faster return on investment, the enhancement of local energy independence and security, and the opportunities for knowledge and skills development. In terms of barriers, these respondents assessed cost- and funding-related issues as significantly more impactful. They rated the lack of available funding, high upfront investment requirements, and ongoing maintenance costs approximately 0.3 to 0.4 points higher (on a 1–5 Likert scale) than non-involved participants, indicating that direct experience increases awareness of the real financial challenges while simultaneously reinforcing confidence in the broader benefits of community energy initiatives.
These demographic patterns are consistent with broader European findings on energy communities. For example, studies in Sweden have shown that despite the inclusive promises of community-owned projects, women still often face unequal access, barriers to decision-making, and thresholds to participation, highlighting persistent systemic challenges in procedural justice and representation [
47]. Furthermore, the research on European electricity cooperatives shows that women are generally underrepresented in leadership positions, often participating only as volunteers or in administrative roles, which underscores the governance structure [
48]. At the same time, regional studies in Greece show a clear urban–rural divide: urban residents consistently have greater knowledge of renewable technologies and a more positive attitude towards energy projects, while rural respondents often show greater skepticism, which reflects the spatial patterns observed in our Romanian sample [
49]. What distinguishes the Romanian situation is how these demographic differences—by gender, place of residence, and participation—intersect with the legacy of centralized energy systems and changing subsidy regimes. This combination adds a unique historical and institutional dimension to public opinion that is less pronounced in many Western European contexts.
6. Conclusions
This study investigated public perception, interest, and knowledge of the concept of energy communities in Romania, where the transition to decentralized renewable energy sources is still in its early stages. Several historical factors were also mentioned that contributed to public skepticism. The main methodology was an online survey with 118 respondents from different backgrounds and demographics. The data collected are important to gain insights into perceived benefits, barriers, and other factors. They were processed using automated Python scripts and the results are presented in this paper.
The survey results confirm that Romanians generally have a positive opinion of energy communities, which is in line with the European Commission’s goals for renewable energy and community initiatives. Respondents considered solar energy to be the most important renewable energy source, with its most attractive feature being its positive impact on the environment. Favorable climatic conditions were identified as one of the region’s key strengths, further increasing the potential of solar energy. Technological innovations, especially those that improve energy efficiency and reduce costs, were also considered important, reflecting concerns about the economic dimension of energy use. Importantly, the results reveal demographic differences in perceptions. Urban, active, and female respondents consistently place a higher value on the benefits of energy communities and are more aware of existing barriers. This underscores the importance of developing targeted policies, communication efforts, and engagement strategies tailored to different demographic groups. Despite government efforts, several significant barriers have been identified that limit the implementation of these initiatives. The main barriers were lack of funding, lack of government support, regulatory challenges, and high upfront investment. These findings are consistent with the context, laws, and regulations described in the introductory chapter. The perceived importance of education programs underscores the positive perception of renewable energy and the fact that the national education system is unprepared. Increased knowledge can lead to better support.
Statistical tests compared different demographic groups and revealed significant differences in perceptions. In general, urban respondents have a more favorable view of the benefits of energy communities than rural respondents. Urban residents perceived several barriers as having a greater impact, such as lack of funding, insufficient government support, problems with grid integration, and high maintenance costs.
Respondents who were already involved in an energy community scored higher on average, indicating a more positive view of some of the potential opportunities and strengths. Those identified with significant statistical differences are indicated in the results. They also perceive some barriers, such as high initial costs and limited funding, as having a greater impact than those who do not participate. Direct experience with the concept may increase the awareness of both the opportunities and practical difficulties.
Significant differences were also observed between male and female respondents. Female respondents generally perceived barriers as having a greater impact than male respondents. Women also rated the importance of community and local government support as more important.
Also, beyond the urban–rural divide, this study suggests that regions with less developed grid infrastructures and reduced access to local renewable energy initiatives—particularly in parts of the South and Northeast—exhibit higher perceived barriers related to connection feasibility and investment risk, offering a focal point for region-specific policy interventions.
Based on the findings, concrete policy measures for Romania should focus on targeted economic incentives and regulatory streamlining to address the most pressing barriers. Economically, dedicated grant schemes could be established to cover 100% of eligible costs for early-stage community energy projects, including not only equipment, but also legal establishment, feasibility studies, and digital platforms for energy sharing. Additional subsidies or tax deductions could be offered for investments in battery storage, grid reinforcement, and shared infrastructure, while low-interest loans with grace periods could ease the upfront investment burden. On the regulatory side, a national one-stop-shop should be introduced to centralize and expedite all licensing and permitting procedures, with clear deadlines for distribution system operators and standardized documentation across regions. Completing the secondary legislation for energy sharing, virtual metering, and community aggregation would remove current legal uncertainties, while simplified reporting and contracting requirements for small-scale community entities would further reduce administrative burdens and accelerate project deployment.
Also, tailored educational programs should focus on practical, hands-on workshops for local residents and municipal staff, complemented by online toolkits and peer-learning networks, emphasizing financial planning, technical operation of renewable systems, and clear guidance on legal procedures, delivered through the information channels most trusted by each community segment.
The results could be useful for policy-makers, educators, and other stakeholders. To increase participation in energy communities, policies should aim to overcome some of the economic problems and simplify complex licensing procedures. The results also highlight the need for more education on the subject to encourage and educate the next generation. For policy-makers, it is of great importance to help achieve the environmental targets proposed by the European Commission.
Looking ahead, future research should aim to expand the sample size and include a more balanced representation of rural areas to better understand geographical disparities. Behavioral experiments could also be valuable in identifying which incentives and messages most effectively drive participation in energy communities.
Author Contributions
Conceptualization, E.S.L., R.M.D., S.F. and M.B.; methodology, E.S.L., R.A.M. and L.-I.C.; software, E.S.L., R.M.D. and A.V.P.; validation, E.S.L., R.A.M. and L.-I.C.; formal analysis, E.S.L., R.M.D., S.F. and A.V.P.; investigation, R.M.D., S.F., M.B. and A.V.P.; resources, E.S.L.; data curation, R.M.D., S.F., M.B. and A.V.P.; writing—original draft preparation, R.M.D., S.F., M.B. and A.V.P.; writing—review and editing, E.S.L., R.A.M. and L.-I.C.; visualization, supervision, E.S.L., R.A.M. and L.-I.C.; project administration, R.M.D. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by a grant from the Institute for Research in Circular Economy and Environment “Ernest Lupan”, project number 244/17.06.2024/Research on the analysis of energy communities regarding the use of sustainable resources.
Institutional Review Board Statement
This study was approved by the Ethics Committee of Institute for Research on Circular Economy and Environment “Ernest Lupan” (protocol code No. 499/25.10.2021).
Informed Consent Statement
Informed consent was obtained from all subjects involved in this study.
Data Availability Statement
The data will be made available on request from the corresponding authors.
Conflicts of Interest
The authors declare no conflicts of interest.
Appendix A. All the Results of the Mann–Whitney U Test
Significant differences found when comparing the urban and rural respondents, per item:
Lower energy costs (U = 643.50, p = 0.0004); Urban mean is 4.22 and Rural mean is 2.80.
Increasing energy independence (U = 637, p = 0.007); Urban mean is 4.18 and Rural mean is 3.20.
Environmental benefits (U = 656.00, p = 0.002); Urban mean is 4.22 and Rural mean is 3.00.
Community responsibilities (U = 674.00, p = 0.001); Urban mean is 4.15 and Rural mean is 2.67.
Creation of new jobs (U = 560.50, p = 0.0276); Urban mean is 3.96 and Rural mean is 3.27.
Technological innovation (U = 665.00, p = 0.0001); Urban mean is 4.24 and Rural mean is 2.80.
Lack of founding (U = 545.00, p = 0.0382); Urban mean is 4.27 and Rural mean is 3.27.
Insufficient governmental support (U = 556.50, p = 0.0277); Urban mean is 4.25 and Rural mean is 3.53.
Willingness to invest in a local energy community (U = 549.50, p = 0.0406); Urban mean is 3.89 and Rural mean is 3.27.
Problems related to the grid integration (U = 602.00, p = 0.0050); Urban mean is 3.95 and Rural mean is 2.87.
Energy storage limitations (U = 563.00, p = 0.0227); Urban mean is 4.13 and Rural mean is 3.47.
Technological reliability (U = 599.00, p = 0.0052); Urban mean is 4.00 and Rural mean is 3.13.
High maintenance costs (U = 579.50, p = 0.0118); Urban mean is 4.13 and Rural mean is 3.47.
Complex authorization processes (U = 557.00, p = 0.0233); Urban mean is 4.36 and Rural mean is 3.47.
Unfavorable regulations (U = 578.50, p = 0.0114); Urban mean is 4.29 and Rural mean is 3.53.
Favorable governmental policies (U = 673.50, p = 0.0001); Urban mean is 4.09 and Rural mean is 2.47.
Available regenerable resources (U = 624.50, p = 0.0012); Urban mean is 4.31 and Rural mean is 3.07.
Interest and implication of the community (U = 624.00, p = 0.0016); Urban mean is 4.02 and Rural mean is 2.73.
Technological progress (U = 607.50, p = 0.0033); Urban mean is 4.18 and Rural mean is 3.00.
Favorable climatic conditions (U = 654.00, p = 0.0002); Urban mean is 4.35 and Rural mean is 3.13.
Existing renewable energy infrastructure (U = 619.50, p = 0.0021); Urban mean is 4.04 and Rural mean is 3.07.
Qualified work force (U = 553.50, p = 0.0367); Urban mean is 3.91 and Rural mean is 3.20.
Support from the local administration (U = 575.00, p = 0.0147); Urban mean is 4.07 and Rural mean is 3.20.
Lack of technical expertise (U = 596.00, p = 0.0061); Urban mean is 4.07 and Rural mean is 3.13.
Insufficient public awareness (U = 598.00, p = 0.0057); Urban mean is 4.099 and Rural mean is 3.00.
Regulatory challenges (U = 575.50, p = 0.0134); Urban mean is 4.24 and Rural mean is 3.47.
Growing public awareness towards sustainability (U = 565.50, p = 0.0159); Urban mean is 4.36 and Rural mean is 3.47.
Interest in the development and use of renewable energy (U = 567.00, p = 0.0143); Urban mean is 4.42 and Rural mean is 3.67.
Private sector partnerships (U = 605.50, p = 0.0033); Urban mean is 4.31 and Rural mean is 3.40.
Educational programs (U = 557.00, p = 0.0258); Urban mean is 4.29 and Rural mean is 3.47.
Changes in government policy (U = 571.50, p = 0.0163); Urban mean is 4.15 and Rural mean is 3.33.
Lack of technology (U = 577.50, p = 0.0146); Urban mean is 3.91 and Rural mean is 3.00.
Public opposition (U = 595.50, p = 0.0073); Urban mean is 3.60 and Rural mean is 2.60.
Competition from conventional energy sources (U = 551.00, p = 0.0414); Urban mean is 3.75 and Rural mean is 2.87.
Significant differences found when comparing the “Involved” and “Not-Involved” respondents, per item:
Favorable governmental policies (U = 1254.50, p = 0.0404); “Involved” mean is 4.15 and “Not-Involved” mean is 3.72.
Founds and subventions (U = 1274.50, p = 0.0256); “Involved” mean is 4.35 and “Not-Involved” mean is 3.91.
Strong community support (U = 1258.00, p = 0.0361); “Involved” mean is 4.35 and “Not-Involved” mean is 3.88.
Limited funding sources (U = 1288.50, p = 0.0193); “Involved” mean is 4.18 and “Not-Involved” mean is 3.95.
High upfront costs (U = 1246.00, p = 0.0426); “Involved” mean is 4.35 and “Not-Involved” mean is 4.03.
Growing public interest in sustainability (U = 1247.50, p = 0.0416); “Involved” mean is 4.30 and “Not-Involved” mean is 3.99.
Interest in the development and use of renewable energy (U = 1270.00, p = 0.0237); “Involved” mean is 4.50 and “Not-Involved” mean is 4.18.
Technological innovations (U = 1246.50, p = 0.0322); “Involved” mean is 4.50 and “Not-Involved” mean is 4.08.
Government subsidies and incentives (U = 1238.00, p = 0.0452); “Involved” mean is 4.55 and “Not-Involved” mean is 4.12.
Significant differences found when comparing the male and female respondents, per item:
Lack of founding (U = 1284.00, p = 0.0275); Male mean is 3.87 and Female mean is 4.24.
Insufficient governmental support (U = 1302.00, p = 0.0366); Male mean is 3.85 and Female mean is 4.19.
Problems related to the grid integration (U = 1208.00, p = 0.0100); Male mean is 3.37 and Female mean is 3.90.
Technological reliability (U = 1247.50, p = 0.0184); Male mean is 3.43 and Female mean is 3.88.
High maintenance costs (U = 1359.00, p = 0.0848); Male mean is 3.78 and Female mean is 4.03.
Complex authorization processes (U = 1254.00, p = 0.0189); Male mean is 3.78 and Female mean is 4.21.
Unfavorable regulations (U = 1260.00, p = 0.0210); Male mean is 3.74 and Female mean is 4.17.
Interest and implication of the community (U = 1311.50, p = 0.0475); Male mean is 3.57 and Female mean is 3.93.
Support from the local administration (U = 1168.00, p = 0.0048); Male mean is 3.52 and Female mean is 4.15.
Limited funding sources (U = 1224.00, p = 0.0117); Male mean is 3.67 and Female mean is 4.22.
Lack of technical expertise (U = 1110.00, p = 0.0016); Male mean is 3.48 and Female mean is 4.10.
Economic instability (U = 1244.50, p = 0.0171); Male mean is 3.65 and Female mean is 4.14.
Changes in government policy (U = 1253.00, p = 0.0197); Male mean is 3.59 and Female mean is 4.10.
Lack of technology (U = 1284.50, p = 0.0336); Male mean is 3.43 and Female mean is 3.92.
Public opposition (U = 1234.00, p = 0.0161); Male mean is 3.13 and Female mean is 3.69.
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Table 1.
The questions and the items of the survey.
Table 1.
The questions and the items of the survey.
Question (Q) | Scale and Items Assessed |
---|
Q1: Are you currently involved in an energy community? | Yes; No |
Q2: Are you familiar with the concept of energy communities? | Scale of 1–5: 1—Not at all familiar; 2—Slightly familiar; 3—Neutral; 4—Familiar; 5—Very familiar |
Q3: Do you intend to get involved in an energy community? | Scale of 1–5: 1—Not at all determined; 2—Slightly determined; 3—Neutral; 4—Quite determined; 5—Very determined |
Q4: What is an attractive benefit gained from participating in an energy community? | Scale of 1–5 (1 = not at all important, 5 = very important): Lower energy costs; Increasing energy independence; Environmental benefits; Community responsibilities; Creation of new jobs; Technological innovation |
Q5: What impact do the following barriers have in the widespread adoption of energy communities? | Scale of 1–5 (1 = minor, 5 = major): Lack of founding; Insufficient governmental support; Lower community awareness; High upfront costs, Limited access to the technology |
Q6: How willing would you be to invest in a local energy community if you had the chance? | Scale of 1–5 (1 = very unlikely 5 = likely) |
Q7: What types of renewable energy sources do you think should be prioritized in the development of energy communities, in your region? | Scale of 1–5 (1 = not at all important, 5 = very important): Solar energy; Wind energy; Biomass; Geothermal energy; Hydroelectric power |
Q8: How do you assess the technical challenges created by the following technological aspects in the energy communities? | Scale of 1–5 (1 = minor, 5 = major): Problems related to the grid integration; Energy storage limitations; Technological reliability; High maintenance cost; Lack of technical expertise |
Q9: What do you think is the degree of impact of the next regulatory or policy barriers on the development of energy communities? | Scale of 1–5 (1 = minor, 5 = major): Complex authorization processes; Unfavorable regulations; Lack of incentives; Bureaucratic obstacles |
Q10: What potential do you see for further development of the energy communities in your region? | Scale of 1–5 (1 = minor objective, 5 = major objective): Favorable governmental policies; Available regenerable resources; Interest and implication of the community; Founds and subventions; Technological progress |
Q11: How do you assess the degree of importance of the following strengths of your region in the development of energy communities? | Scale of 1–5 (1 = not that important, 5 = important): Strong community support; Favorable climatic conditions; Existing renewable energy infrastructure; Qualified work force; Support from the local administration |
Q12: How do you assess the degree of impact of the following weaknesses on the development of energy communities in your region? | Scale of 1–5 (1 = small impact, 5 = big impact): Limited funding sources; Lack of technical expertise; Insufficient public; awareness; Regulatory challenges; High upfront costs |
Q13: What opportunities should your region focus on to promote the energy communities? | Scale of 1–5 (1 = not that important, 5 = important): Growing public interest in sustainability; Interest in the development and use of renewable energy; Technological innovations; Government subsidies and incentives; Private sector partnerships; Educational programs |
Q14: What is the degree of threat of the following aspects to the success of energy communities in your region? | Scale of 1–5 (1 = not a threat, 5 = big threat): Economic instability; Changes in government policy; Lack of technology; Public opposition; Competition from conventional energy sources |
Q15: Would you consider living in a green house? | Yes; No; Other answers |
Table 2.
The socio-demographic composition of the sample.
Table 2.
The socio-demographic composition of the sample.
| N (Number) | % | | N (Number) | % |
---|
Sex | Age |
Male | 72 | 39 | 18–24 years | 21 | 11.9 |
Female | 46 | 61 | 25–34 years | 38 | 21.5 |
| | | 35–44 years | 49 | 27.7 |
| | | 45–54 years | 37 | 20.9 |
Education | 55+ | 32 | 18.1 |
No formal education in the public school system | 2 | 1.7 | | | |
Primary studies | 1 | 0.9 | | | |
Gymnasium studies | 1 | 0.9 | Region |
Highschool | 14 | 11.9 | Macro-region 1 (RO1: NW and Center of Romania) | 101 | 85.6 |
University studies | 62 | 52.5 | Macro-region 2 (RO2: NE and SE of Romania) | 2 | 1.7 |
Post-graduate studies | 25 | 21.2 | Macro-region 3 (RO3: S of Romania and Bucharest) | 3 | 2.5 |
Doctoral studies | 13 | 11.0 | Macro-region 4 (RO4: SW and W of Romania) | 12 | 10.2 |
Total | 118 | 100 | 100 |
Table 3.
Evaluation of the answers to Q7.
Table 3.
Evaluation of the answers to Q7.
Q7. What types of renewable energy sources do you think should be prioritized in the development of energy communities, in your Region? Scale of 1–5 (1 = not at all important, 5 = very important) |
Items | Mean Core | Mean Deviation | Highest Response Level |
Solar energy | 4.46 | 0.74 | Level 5: 68.64% |
Wind energy | 4.05 | 0.81 | Level 5: 42.34% |
Hydroelectric power | 3.88 | 0.82 | Level 4: 34.86% |
Biomass | 3.52 | 0.93 | Level 4: 33.02% |
Geothermal energy | 3.38 | 1.17 | Level 4: 28.57% |
Table 4.
Evaluation of the answers to Q4.
Table 4.
Evaluation of the answers to Q4.
Q4. What is an attractive benefit gained from participating in an energy community? Scale of 1–5 (1 = not at all important, 5 = very important) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Environmental benefits | 4.08 | 0.86 | Level 5: 46.61% |
Technological innovations | 4.03 | 0.84 | Level 5: 43.22% |
Lower energy costs | 4.02 | 0.83 | Level 5: 42.37% |
Increasing energy independence | 3.96 | 0.77 | Level 4: 35.59% Level 5: 35.59% |
Creation of new jobs | 3.91 | 0.85 | Level 5: 36.44% |
Community responsibilities | 3.83 | 0.86 | Level 4: 36.44% |
Table 5.
Evaluation of the answers to Q5.
Table 5.
Evaluation of the answers to Q5.
Q5. What impact do the following barriers have in the widespread adoption of energy communities? Scale of 1–5 (1 = minor, 5 = major) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Lack of founding | 4.09 | 0.88 | Level 5: 48.31% |
Insufficient governmental support | 4.06 | 0.67 | Level 4: 43.22% |
Lower community awareness | 3.92 | 0.86 | Level 5: 37.29% |
High upfront costs | 3.87 | 0.82 | Level 4: 37.29% |
Limited access to the technology | 3.74 | 0.92 | Level 4: 32.20% |
Table 6.
Evaluation of the answers to Q11.
Table 6.
Evaluation of the answers to Q11.
Q11. How do you assess the degree of importance of the following strengths of your region in the development of energy communities? Scale of 1–5 (1 = not that important, 5 = important) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Favorable climatic conditions | 4.11 | 0.68 | Level 4: 40.68% |
Strong community support | 3.96 | 0.80 | Level 5: 37.29% |
Support from the local administration | 3.91 | 0.86 | Level 5: 36.44% |
Existing renewable energy infrastructure | 3.86 | 0.83 | Level 5: 32.20% |
Qualified work force | 3.84 | 0.84 | Level 4: 34.75% |
Table 7.
Evaluation of the answers to Q13.
Table 7.
Evaluation of the answers to Q13.
Q13. What opportunities should your region focus on to promote the energy communities? Scale of 1–5 (1 = not that important, 5 = important) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Interest in the development and use of renewable energy | 4.24 | 0.76 | Level 5: 50% |
Educational programs | 4.16 | 0.80 | Level 5: 47.46% |
Technological innovations | 4.15 | 0.75 | Level 5: 44.44% |
Growing public interest in sustainability | 4.04 | 0.84 | Level 5: 44.07% |
Private sector partnership | 4.02 | 0.68 | Level 4: 37.29% |
Government subsidies and incentives | 3.98 | 0.77 | Level 4: 37.29% Level 5: 37.29% |
Table 8.
Evaluation of the answers to Q12.
Table 8.
Evaluation of the answers to Q12.
Q12. How do you assess the degree of impact of the following weaknesses on the development of energy communities in your region? Scale of 1–5 (1 = small impact, 5 = big impact) |
Items | Mean Score | Mean Deviation | Highest Response Level |
High initial cost | 4.08 | 0.81 | Level 5: 44.07% |
Regulatory challenges | 4.03 | 0.76 | Level 5: 38.98% |
Limited funding sources | 4.01 | 0.79 | Level 5: 39.83% |
Lack of technical expertise | 3.86 | 0.78 | Level 4: 36.4% |
Insufficient public awareness | 3.86 | 0.87 | Level 5: 34.75% |
Table 9.
Evaluation of the answers to Q9.
Table 9.
Evaluation of the answers to Q9.
Q9. What do you think is the degree of impact of the next regulatory or policy barriers on the development of energy communities? Scale of 1–5 (1 = minor, 5 = major) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Complex authorization processes | 4.04 | 0.80 | Level 5: 41.53% |
Lack of incentives | 4.03 | 0.79 | Level 5: 40.68% |
Unfavorable regulations | 4.00 | 0.68 | Level 4: 37.29% |
Bureaucratic obstacles | 3.97 | 0.82 | Level 4: 38.98% |
Table 10.
Evaluation of the answers to Q10.
Table 10.
Evaluation of the answers to Q10.
Q10. What potential do you see for further development of the energy communities in your region? Scale of 1–5 (1 = minor opportunity, 5 = major opportunity) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Available regenerable resources | 4.04 | 0.81 | Level 5: 41.37% |
Founds and subventions | 3.98 | 0.77 | Level 4: 37.29% Level 5: 37.29% |
Technological progress | 3.88 | 0.84 | Level 4: 33.90% |
Favorable governmental policies | 3.80 | 0.96 | Level 5: 34.75% |
Interest and implication of the community | 3.79 | 0.89 | Level 4: 34.75% |
Table 11.
Evaluation of the answers to Q8.
Table 11.
Evaluation of the answers to Q8.
Q8. How do you assess the technical challenges created by the following technological aspects in the energy communities? Scale of 1–5 (1 = minor, 5 = major) |
Items | Mean Score | Mean Deviation | Highest Response Level |
High maintenance cost | 3.93 | 0.72 | Level 4: 37.29% |
Energy storage limitations | 3.88 | 0.71 | Level 4: 42.37% |
Lack of technical expertise | 3.87 | 0.72 | Level 4: 44.07% |
Technological reliability | 3.70 | 0.83 | Level 3: 33.05% Level 4: 33.05% |
Problems related to the grid integration | 3.69 | 0.88 | Level 4: 35.59% |
Table 12.
Evaluation of the answers to Q14.
Table 12.
Evaluation of the answers to Q14.
Q14. What is the degree of threat of the following aspects to the success of energy communities in your region? Scale of 1–5 (1 = minor, 5 = major) |
Items | Mean Score | Mean Deviation | Highest Response Level |
Economic instability | 3.95 | 0.80 | Level 5: 36.44% |
Changes in government policy | 3.90 | 0.80 | Level 5: 35.59% |
Lack of technology | 3.73 | 0.94 | Level 5: 30.51% |
Competition from conventional energy sources | 3.66 | 0.92 | Level 4: 32.20% |
Public opposition | 3.47 | 0.97 | Level 4: 32.20% |
Table 13.
Barrier and policy recommendations for energy communities in Romania.
Table 13.
Barrier and policy recommendations for energy communities in Romania.
Identified Barrier | Policy Recommendation |
---|
Lack of funding | Create dedicated grant lines for community organization costs (legal setup, IT platforms, feasibility studies) in addition to equipment; allow 100% coverage for eligible costs in early-stage projects. |
Lack of government support | Establish a clear, stable national strategy for energy communities with consistent incentives and long-term targets; integrate support schemes into national energy and climate plans. |
Regulatory challenges (complex authorizations, incomplete norms) | Implement a one-stop-shop for authorizations; finalize secondary legislation for energy sharing, virtual metering, and aggregation; set clear, short deadlines for grid connection. |
High upfront investment | Provide grants or subsidies for grid reinforcement, battery storage, and shared infrastructure; reduce or eliminate co-financing requirements for community-led projects. |
Bureaucracy | Standardize and digitize procedures across regions and distribution operators; simplify reporting and contract requirements for small-scale community entities. |
Policy instability | Avoid frequent changes in compensation and tariff mechanisms; introduce multi-year policy commitments to increase investor and community trust. |
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