SWOT Analysis for the Promotion of Energy Efficiency in Rural Buildings: A Case Study of China

Zhang, Lin; Guo, Shan; Wu, Zezhou; Alsaedi, Ahmed; Hayat, Tasawar

doi:10.3390/en11040851

Cited by 25 publications

(39 citation statements)

References 41 publications

(53 reference statements)

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“…A key advantage of SWOT analysis is to "yield useful information about the future viability of the considered system" [40]. Although originally from the business field [41], the use of SWOT has expanded to several other areas, particularly, energy [42][43][44][45][46]. A number of SWOT studies have been conducted in Southeast Asia, both for individual countries [47] and for ASEAN as a whole [48].…”

Section: Methodsmentioning

confidence: 99%

A SWOT Analysis of Utility-Scale Solar in Myanmar

Alvarez

Sugiyama

2020

Energies

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Myanmar remains one of the few exceptions to the rapid diffusion of solar photovoltaics (PV) in power generation mixes. This is surprising considering that Myanmar is one of the countries with the largest technical potential for solar energy among Southeast Asian nations. Solar energy can complement the existing hydropower generation to address endemic energy crisis during the dry season. A continuation of paralysis on investments in solar energy could affect the security and sustainability of the sector in one of the most rapidly growing countries in the region. In this paper, we aimed to identify the barriers preventing solar energy to flourish in Myanmar and to identify policy options to unlock them. We conducted a SWOT (strengths, weaknesses, opportunities, and threats) analysis with inputs from relevant stakeholders from the government, private sector, and civil society organizations. Our analysis suggested a consensus on the merits of solar energy among all factors; however, a policy framework to spur investments that contribute both to the national energy system and local development needs to be developed by considering some particularities of Myanmar, such as securing rightful land ownership and limited experience with market mechanisms (e.g., energy auction), for the promotion of investments in the energy sector.

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Section: Methodsmentioning

confidence: 99%

A SWOT Analysis of Utility-Scale Solar in Myanmar

Alvarez

Sugiyama

2020

Energies

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“…Rural buildings have been analyzed by authors in [20]. Their studies aim to establish an appropriate strategic plan for promoting rural building energy efficiency by conducting a strength-weakness-opportunity-threat analysis.…”

Section: Related Workmentioning

confidence: 99%

“…• Date, holiday (yes or no), week of the year (1-52), month (1-12), 2-month, 3-month, 4-month, 6-month periods; • Daily time slots, i.e., morning [4][5][6][7][8], midday [9][10][11][12][13], afternoon [14][15][16][17], evening [18][19][20][21][22]; during the night, from 22 to 4, the heating system is switched off in the buildings under study.…”

Section: Data Descriptionmentioning

confidence: 99%

METATECH: METeorological Data Analysis for Thermal Energy CHaracterization by Means of Self-Learning Transparent Models

2018

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In the last few years, a large number of smart meters have been deployed in buildings to continuously monitor fine-grained energy consumption. Meteorological data deeply impact energy consumption, and an in-depth analysis of collected and correlated data can uncover interesting and actionable insights to improve the overall energy balance of our communities and to enhance people's awareness of energy wasting. To effectively extract meaningful and interpretable insights from large collections of energy measurements and multi-dimensional meteorological data, innovative data science methodologies should be devised. Research frontiers are addressing self-learning approaches, which allow non-experts to exploit machine learning techniques more easily, and algorithmic transparency of models, hence providing actionable, explicit, declarative knowledge representation. This paper presents METeorological Data Analysis for Thermal Energy CHaracterization (METATECH), a data mining engine based on both exploratory and unsupervised data analytics algorithms, devised to build transparent models correlating weather conditions and energy consumption in buildings. METATECH exploits a joint approach coupling cluster analysis and generalized association rules to allow a deeper yet human-readable understanding of how meteorological data impact heating consumption. First, a partitional clustering algorithm is applied to weather conditions. Then, resulting clusters are characterized by means of generalized association rules, which provide a self-learning explainable model of the most interesting correlations between energy consumption and weather conditions at different granularity levels. The experimental evaluation performed on real datasets demonstrates the effectiveness of the proposed approach in automatically extracting interesting knowledge from data, and provide it transparently to domain experts.

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“…It has also been used to identify and overcome the obstacles to the development of the waste-to-energy incineration industry in China [30]. The latter was applied to reveal the drivers and barriers in the course of implementing rural building energy efficiency in China [31]. A SWOT analysis approach was also used for strategic management and technology enablement of machine learning and advanced analytics in the oil and gas industry [32].…”

Section: Introductionmentioning

confidence: 99%

The Application of Analytical Hierarchy Process in Combination with PESTEL-SWOT Analysis to Assess the Hydrocarbons Sector in Cyprus

et al. 2019

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Natural gas reserves have been recently found offshore of Cyprus. Hence, a new energy sector is under development, creating potential for raised welfare for the small insular EU member. Several social and economic benefits could be achieved from the resources’ exploitation. However, natural gas is a non-renewable energy source, connected with the major environmental issues of fossil fuels. The research goal of this work was to evaluate the sustainability of the new hydrocarbons sector. This was attained using a set of indicators, developed from the combination of PESTEL (Political, Economic, Technical, Social, Environmental, Legal) and SWOT (Strengths, Weaknesses, Opportunities, Threats) analyses. These were quantified using the Analytical Hierarchy Process (AHP) weighting method. They were pairwise compared and evaluated, resulting to a size for each one. The judgements of four evaluators, representing diverse interested parties, were used. The strengths and opportunities of the sector were found to be more than the weaknesses and threats. The relevant indicators quantification demonstrates also that the value of the positives is higher than the negatives. Therefore, if the first are enhanced and the latter are mitigated, there is sustainability potential. The sectors environmental issues are evaluated as the most important, followed by the economic. The other takes lower but comparatively significant values, and must be handled accordingly. These results lead to useful conclusions and could be exploited for decision-making and policies formulation.

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SWOT Analysis for the Promotion of Energy Efficiency in Rural Buildings: A Case Study of China

Cited by 25 publications

References 41 publications

A SWOT Analysis of Utility-Scale Solar in Myanmar

A SWOT Analysis of Utility-Scale Solar in Myanmar

METATECH: METeorological Data Analysis for Thermal Energy CHaracterization by Means of Self-Learning Transparent Models

The Application of Analytical Hierarchy Process in Combination with PESTEL-SWOT Analysis to Assess the Hydrocarbons Sector in Cyprus

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