Researching social acceptability of renewable energy technologies in Finland

Moula, Md. Munjur E.; Maula, Johanna; Hamdy, Mohamed; Fang, Tingting; Jung, Nusrat; Lahdelma, Risto

doi:10.1016/j.ijsbe.2013.10.001

Cited by 103 publications

(54 citation statements)

References 25 publications

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“…The vast majority of this literature are normative and includes descriptive analysis in some countries, such as USA [4,5], the Netherlands [6,7], Denmark [8], Finland [9], Germany [10][11][12], Kazakhstan [13], Europe [14], and UK [15]. However, there is a lack of empirical literature in this field.…”

Section: Literature Reviewmentioning

confidence: 99%

Factors That Influence Renewable Energy Technological Innovation in China: A Dynamic Panel Approach

et al. 2018

Sustainability

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Abstract:We examine the driving effects of various factors on technological innovation to renewables (TIRES), focusing on a set of 29 provinces in China, and apply a dynamic panel approach. China has become a leading player in research and development spending in renewables, and the dynamic panel estimators we use prove themselves to be suitable in handling the persistent effect on TIRES. The level of TIRES in the previous periods is positively and highly correlated with that in the current period and confirmed the need for a stable and consistent policy support for renewables. Electricity consumption is the most important driver for all renewables and wind energy, but the driving effect was weaker for solar energy and biomass. Research and development intensity is the most important driver for biomass, but is only the second most important driver for all renewables, solar energy and wind energy. Unexpectedly, electricity price has had significant negative impacts on TIRES, which reveals that lowering electricity prices will lead to higher innovation in renewables. The driving effect of renewable energy tariff surcharge subsidy is not significant, which means that Chinese subsidy policy has not played the desired role. The driving effect of installed renewable energy capacity is also minimal, which may be due to the fact that overcapacity will hinder TIRES in China. This paper may help policy-makers and the industry understand how to promote TIRES in China effectively based on these above influential factors.

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Section: Literature Reviewmentioning

confidence: 99%

Factors That Influence Renewable Energy Technological Innovation in China: A Dynamic Panel Approach

et al. 2018

Sustainability

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“…The sustainability of RES projects can also receive the benefits of education because education can empower community inhabitants, making them more knowledgeable of the benefits of the technology and more able to operate and maintain the technologies themselves [71,72]. By having more knowledge about the benefits of RES, communities are more likely to accept and embrace them [73][74][75][76][77][78]. Educating the target population about the benefits of RES is vital to counteract any negative preconceptions or scepticism associated with the use of these technologies [79].…”

Section: Human Capitalmentioning

confidence: 99%

“…Level of education [3,5,[68][69][70][73][74][75][76][77][78] "Among other benefits, access to electricity/ . .…”

Section: Factor Articles Excerpts Of Potential Causal Linksmentioning

confidence: 99%

On the Acceptance and Sustainability of Renewable Energy Projects—A Systems Thinking Perspective

et al. 2016

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Rapid population growth and increasing concern related to improving the living standards in impoverished communities without damaging the natural environment have drawn attention to the adoption of renewable energy systems (RES) around the world. Despite this global trend, the implementation of these projects has not succeeded completely in rural poor communities due to several factors, including social barriers faced at the time of their execution. These social barriers lead to poor acceptance of the projects and their consequent abandonment. Acceptance is a social construct that is influenced by several factors that need to be understood to achieve successful and sustainable results in the future. In this paper, we develop a conceptual model, based on principles of sustainability and systems thinking, to understand the interrelationships among the main factors that have been reported in the literature as key to determining the sustainability and community acceptance of RES projects. To do so, we review the existing literature on sustainability and social acceptance of RES and then construct a causal-loop diagram of their driving factors. While doing so, we also view the problem through the lens of the sustainable livelihoods framework, aiming to maintain the perspective of rural communities and observing the impacts of RES on their contextual reality. The resulting model helps to understand the multiple interactions that RES projects have with rural communities as well as identify potential intervention points for future projects. We end the paper with a discussion of the implications of the model and how can it be used to inform future rural energy decision making.

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“…According to a previous literature review conducted by the authors [1], it is concluded that few economic scenarios or design options are addressed in nZEB related studies. None of the studies of Kumbaroglua and Madlener [2], Hasan et al [3], Papadopoulos et al [4], Georges et al [5], Kurnitskia et al, [6], Marszal et al [7], Munjur et al [8]. and Attia [9] investigated comprehensively the impact of the economic assumptions on the cost-optimal energy performance level (CO-EPL) towards nZEBs, in line with the EBPD-recast 2010 [10].…”

Section: Introductionmentioning

confidence: 99%

Impact of financial assumptions on the cost optimality towards nearly zero energy buildings – A case study

Hamdy

Sirén

Attia

2017

Energy and Buildings

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a b s t r a c tThe energy efficiency challenge in Europe is mainly concerned with existing buildings and the investment scenarios to implement deep renovations. The cost-optimal approach imposed on EU-Member states by the European Energy Performance of Buildings Directive aims to identify the investment gap and challenges to transform existing buildings into nearly Zero Energy Buildings (nZEBs). The investment gap is function of several volatile financial parameters including discount rate (r), developing of energy price (e), decline rate of technology price (d), as well as nZEB's incentives like feed-in-tariff (FiT) and investment grant (iG). In this context, the decision making process of individuals or investment institutions is hindered by complexity and uncertainty.In order to assist the decision making process and improve the visibility of financial energy benefits, a novel optimization-based parametric analysis scheme (OptnZEB-I) is developed. The scheme is designed to investigate a large number of economic scenarios (i.e., combinations of financial assumptions) in a short computational time while a holistic optimization approach is adopting for exploring all possible design options including energy conservation measures (ESMs); renewable energy sources (RETs) and mechanical systems (Sys).For demonstration, the scheme is applied to analyse the impact of several financial parameters on the cost-optimal energy performance level (CO-EPL) of a single family house in Finland. In line with the EU-directive, a large number of possible design options (∼3 × 10 9 million) are optimized for 4608 cases of economic scenarios. The results of the address case study show that, in average, the CO-EPL ranges from 90 to 160 [kWh/m 2 ]. The range has most frequent value of 145 kWh/m 2 . The CO-EPL is significantly sensitive to the e, f, then i, respectively. Less sensitivity is found to the other financial parameters.The robustness of the optimization results are verified by solving the addressed design problem by using four different optimization algorithms (i.e., pattern search, interior-point, simulated annealing and genetic algorithms).© 2017 Elsevier B.V. All rights reserved.Abbreviations: ASHP, air source heat pump; c, calculatioin period; CO-EPL, cost-optimal energy performance level; CO-IC, cost-optimal investment cost; CO-TM, costoptimal technology mix; d, decline rate of technology price; dIC, additional investment cost (initial costs higher than 21kD ); e, escalation rate of energy price; ESMs, energy saving measures; EPBD, European Energy Performance of Buildings Directive; f, inflation rate; FiT, feed-in-tariff; GA, genetic algorithm; GSHP, ground source heat pump; HVAC, heating ventilation and air conditioning system; i, nominal interest rate; iG, investment grants (25% discount of additional investment); LCC, life cycle cost; MG, money gain from exporting the surplus electricity to the grid; CHP, micro-heating and power plants; nZEB, nearly zero energy buildings; NZEB, Nearly zero energy buildings; PHU, primar...

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Researching social acceptability of renewable energy technologies in Finland

Cited by 103 publications

References 25 publications

Factors That Influence Renewable Energy Technological Innovation in China: A Dynamic Panel Approach

Factors That Influence Renewable Energy Technological Innovation in China: A Dynamic Panel Approach

On the Acceptance and Sustainability of Renewable Energy Projects—A Systems Thinking Perspective

Impact of financial assumptions on the cost optimality towards nearly zero energy buildings – A case study

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