Highlights ► Algae are the fastest growing organisms for biomass production. ► Algae can be used to generate hydrocarbons, ethanol, biogas, or hydrogen. ► Substantial progress has been made in strain ...identification, lipid extraction, and fuel refining. ► Work still needs to be done in harvesting, nutrient utilization and recycling, and crop protection. ► Algae are versatile source of bioenergy with perhaps the best potential as a sustainable energy source.
Buildings consume a vast amount of energy during the life cycle stages of construction, use and demolition. Total life cycle energy use in a building consists of two components: embodied and ...operational energy. Embodied energy is expended in the processes of building material production, on-site delivery, construction, maintenance, renovation and final demolition. Operational energy is consumed in operating the buildings. Studies have revealed the growing significance of embodied energy inherent in buildings and have demonstrated its relationship to carbon emissions.
Current interpretations of embodied energy are quite unclear and vary greatly, and embodied energy databases suffer from the problems of variation and incomparability. Parameters differ and cause significant variation in reported embodied energy figures. Studies either followed the international Life Cycle Assessment (LCA) standards or did not mention compliance with any standard. Literature states that the current LCA standards fail to provide complete guidance and do not address some important issues. It also recommends developing a set of standards to streamline the embodied energy calculation process.
This paper discusses parameters causing problems in embodied energy data and identifies unresolved issues in current LCA standards. We also recommend an approach to derive guidelines that could be developed into a globally accepted protocol.
•We presented change-point modeling for residential interval and energy auditing.•We used energy use data from multi-residential homes in South Korea.•The first phase found the best interval data for ...residential energy use in the case.•The second phase identified the best periods for specific short-term monitoring.
Residential energy use data has become more readily available through the Advanced Metering Infrastructure (AMI). AMI data can have greater impacts in various fields that employ building energy analysis such as energy use prediction, fault detection, model calibration, and short-term monitoring because the AMI data is more meaningful due to granularity. However, this is not always true if we do not properly use the AMI data. In this paper, we evaluated how interval energy use data is useful for the prediction and short-term monitoring for residential buildings. Two phases were applied to multi-residential buildings in a case study apartment in South Korea. Phase I compares the change-point linear regression models between daily, weekly, and monthly interval energy use data. Phase II determines the minimum data period required to determine each coefficient of change-point linear regression models using an advanced analysis method compared to a previous Dry-Bulb Temperature Analysis (DBTA) study. The results from Phase I showed that weekly interval data could be the best option to analyze residential energy use. Phase II demonstrated that the new analysis method, called the coefficient checking method, is useful to find short-term energy monitoring periods for the data logger installation in terms of weather-independent and weather-dependent electricity use as well as the prediction of the whole-building energy use.
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•Development of two Belgian benchmark models for nearly Zero Energy Schools.•Average energy use intensity per school (primary and secondary) was 59 and 42 kWh/m2/year.•Models ...validated with four-year monitoring data on energy consumption.•Nearly Zero Energy Schools needs are cooling and electricity dominated.•Findings on energy needs and use intensity are useful in temperate and continental climates.
The aim of this study is to develop an energy performance data set and two building performance simulation benchmark models for high performance schools in Belgium. The study reports the results of an inventory and field survey conducted on nearly Zero Energy Schools (nZES) and Passive House Schools (PHS) constructed after year 2013. An analysis of energy consumption (electricity and natural gas) and a walkthrough survey were conducted during May 2018. The energy consumption analysis was done for the occupancy period of 2015–2018 based on monthly consumption data. Two building performance simulation models are created in EnergyPlus to benchmark the average energy consumption and building characteristics. The validity of the estimate has been further checked against the public statistics and verified through model calibration and utility bill comparison. The paper provides a timely opportunity to evaluate the real performance of nZES, in relation to design assumptions and how schools’ professionals can turn the energy performance gap challenge to their advantage. The findings on energy needs and use intensity are useful in temperate and continental climates.
Environmental impact of wind energy Saidur, R.; Rahim, N.A.; Islam, M.R. ...
Renewable & sustainable energy reviews,
06/2011, Letnik:
15, Številka:
5
Journal Article
Recenzirano
Since the beginning of industrialization, energy consumption has increased far more rapidly than the number of people on the planet. It is known that the consumption of energy is amazingly high and ...the fossil based resources may not be able to provide energy for the whole world as these resources will be used up in the near future. Hence, renewable energy expected to play an important role in handling the demand of the energy required along with environmental pollution prevention.
The impacts of the wind energy on the environment are important to be studied before any wind firm construction or a decision is made. Although many countries showing great interest towards renewable or green energy generation, negative perception of wind energy is increasingly evident that may prevent the installation of the wind energy in some countries. This paper compiled latest literatures in terms of thesis (MS and PhD), journal articles, conference proceedings, reports, books, and web materials about the environmental impacts of wind energy. This paper also includes the comparative study of wind energy, problems, solutions and suggestion as a result of the implementation of wind turbine. Positive and negative impacts of wind energy have been broadly explained as well. It has been found that this source of energy will reduce environmental pollution and water consumption. However, it has noise pollution, visual interference and negative impacts on wildlife.
Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy ...efficiency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most effective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy efficiency at a very early design stage. On the other hand,efficient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, artificial intelligence (AI) in general and machine learning (ML) techniques in specific terms have been proposed for forecasting of building energy consumption and performance. This paper provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance.
•Climate change and urban setting impact energy use of buildings.•Energy use is higher due to overlapping effect of climate change and microclimate.•A method is proposed to account for future and ...urban environment in thermal simulation.•The results can assist in sizing passive ventilation systems.
Urban settings and climate change both impact on energy use and thermal comfort inside buildings. This paper first presents a study of changes in energy demand in residential buildings considering the overlapping effect of climate change and urban heat island intensity in two European locations; Cadiz (Spain) and London (United Kingdom), representing temperate and hot European climates and moderate and dense urban settings. Future-urban weather files were generated and simulations were run considering energy demand and indoor thermal comfort. In hot climate regions such as the one of Cadiz, future climate will increase the cooling demand and the additional impact of the UHI leads to a further increase of up to +28% of total energy demand compared to the current climate without considering urban effects. Future-urban weather conditions will be detrimental also for buildings in London, where the annual energy demand is predicted to increase by up to the 16% if future climate and urban effects are included. This is due to a higher increase in cooling demand compared to the reduction for the heating need. The paper also presents a method to take into account microclimatic conditions in naturally ventilated buildings, especially the effect of wind variations around the building which impacts natural ventilation rates. Air and surface temperature and wind speeds were studied using ENVImet and the resulting microclimatic conditions were used as inputs to the EnergyPlus Airflow Network model for the calculation of the building ventilation rates. It was found that ventilation rates are reduced (in comparison to meteorological weather files) and this reduction impacts negatively on internal operative temperatures. A thermal comfort analysis was carried out indicating that the selection of a suitable weather file and microclimatic conditions is essential for more accurate predictions of internal thermal comfort and will assist in the sizing of passive and active systems to avoid overheating.
Background: The global focus on improved cookstoves (ICSs) and clean fuels has increased because of their potential for delivering triple dividends: household health, local environmental quality, and ...regional climate benefits. However, ICS and clean fuel dissemination programs have met with low rates of adoption. Objectives: We reviewed empirical studies on ICSs and fuel choice to describe the literature, examine determinants of fuel and stove choice, and identify knowledge gaps. Methods: We conducted a systematic review of the literature on the adoption of ICSs or cleaner fuels by households in developing countries. Results are synthesized through a simple vote-counting meta-analysis. Results: We identified 32 research studies that reported 146 separate regression analyses of ICS adoption (11 analyses) or fuel choice (135 analyses) from Asia (60%), Africa (27%), and Latin America (19%). Most studies apply multivariate regression methods to consider 7-13 determinants of choice. Income, education, and urban location were positively associated with adoption in most but not all studies. However, the influence of fuel availability and prices, household size and composition, and sex is unclear. Potentially important drivers such as credit, supply-chain strengthening, and social marketing have been ignored. Conclusions: Adoption studies of ICSs or clean energy are scarce, scattered, and of differential quality, even though global distribution programs are quickly expanding. Future research should examine an expanded set of contextual variables to improve implementation of stove programs that can realize the "win-win-win" of health, local environmental quality, and climate associated with these technologies.
Characterization of electric loads provides opportunities to incorporate detailed energy usage information into applications such as protection, efficiency certification, demand response, and energy ...management. This paper proposes a low computational cost, but yet accurate method, to extract signatures for load classification and characterization. Instead of utilizing digital signal processing and frequency-domain analysis, this paper abstracts the similarity of voltage-current (V-I) trajectories between loads and proposes to map V-I trajectories to a grid of cells with binary values. Graphical signatures can then be extracted for many applications. The proposed method significantly reduces the computational cost compared with existing frequency-domain signature extraction methods. Test results show that an average of over 99% of success rate can be achieved using the proposed signatures.
•Studies of international workplace energy saving interventions are reviewed.•Enablement, Environmental Restructuring and Modelling most promising interventions.•Coercion, Restriction, and Training ...intervention types have been little researched.•Successful interventions create social and physical opportunities for employees.•Utility of social influence and energy efficient technologies highlighted.
Workplaces worldwide are a major source of carbon emissions and changing energy use behaviour in these environments has the capacity for large carbon savings. This paper reviews and synthesises empirical evidence to identify what types of behaviour change intervention are most successful at saving energy in an office-type workplace. We draw on the field of health-related behaviour change interventions and adopt the Behaviour Change Wheel (Michie et al., 2014) as a framework through which to assess the success of the interventions reviewed here (n=22 studies). We find that interventions creating social and physical opportunities for employees to save energy are the most successful i.e. which constitute Enablement (including direct support and greater control to employees), Environmental Restructuring (particularly automated and retrofitted technologies) and Modelling (various forms of social influence). The communal nature of most workplaces demands scrutiny to understand the effect of social influences. We provide recommendations for future research, including the need to consider forms of intervention not yet researched; Coercion, Restriction, and Training. We conclude by calling for further, well evaluated, energy saving behavioural interventions in a variety of workplaces to identify those techniques which offer the greatest success in saving energy and thus reducing carbon emissions.
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