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Microalgae have tremendous potential for producing liquid renewable fuel. Many methods for converting microalgae to biofuel have been proposed; however, an economical and energetically feasible route for algal fuel production is yet to be found. This paper presents a review on the comparison of the most promising conversion pathways of microalgae to liquid fuel: hydrothermal liquefaction (HTL), wet extraction and non-destructive extraction. The comparison is based on important assessment parameters of product quality and yield, nutrient recovery, GHG emissions, energy and the cost associated with the production of fuel from microalgae, in order to better understand the pros and cons of each method. It was found that the HTL pathway produces more oil than the wet extraction pathway; however, higher concentrations of unwanted components are present in the HTL oil produced. Less nutrients (N and P) can be recovered in HTL compared to wet extraction. HTL consumes more fossil energy and generates higher GHG emissions than wet extraction, while the production cost of fuel from HTL pathway is lower than wet extraction pathway. There is considerable uncertainty in the comparison of the energy consumption and economics of the HTL pathway and the wet extraction pathway due to different scenarios analysed in the assessment studies. To be able to appropriately compare methodologies, the conversion methods should be analysed from growth to upgradation of oil utilising sufficiently similar assumptions and scenarios. Based on the data in available literature, wet oil extraction is the more appropriate system for biofuel production than HTL. However, the potential of alternative extraction/conversion technologies, such as, non-destructive extraction, need to be further assessed.

Abstract In developed countries, buildings are involved in almost 50% of total energy use and 30% of global green-house gas emissions. Buildings' operational energy is highly dependent on various building physical, operational, and functional characteristics, as well as meteorological and temporal properties. Besides physics-based building energy modeling, machine learning techniques can provide faster and higher accuracy estimates, given buildings' historic energy consumption data. Looking beyond individual building levels, forecasting buildings’ energy performance helps city and community managers have a better understanding of their future energy needs, and plan for satisfying them more efficiently. Focusing on an urban-scale, this study systematically reviews 70 journal articles, published in the field of building energy performance forecasting between 2015 and 2018. The recent literature have been categorized according to five criteria: 1. Learning Method, 2. Building Type, 3. Energy Type, 4. Input Data, and 5. Time-scale. The scarcity of building energy performance forecasting studies in urban-scale versus individual level is considerable. There is no study incorporating building functionality in terms of space functionality share percentages, nor assessing the effects of climate change on urban buildings energy performance using machine learning approaches and future weather scenarios. There is no optimal criteria combination for achieving the most accurate machine learning-based forecast, as there is no universal measure able to provide such global comparison. Accuracy levels are highly correlated with the characteristics of forecasting problems. The goal is to provide a comprehensive status of machine learning applications in urban building energy performance forecasting, during 2015–2018.

In most industrial processes, toxic pollutants and vapors are produced and released, which cause various diseases in people working in industry and irreparable damage to the environment. Industrial ventilation systems are considered as one of the most effective methods of reducing and controlling gaseous pollutants and dust particles. One of the effective systems in industrial ventilation is blowing -suction ventilation systems. In this study, the effect of flow ratio (ratio of blowing flow to suction flow) and direction of blowing jet air on the performance of blowing-suction ventilation system was investigated numerically. The mixing parameter has been used as an indicator to measure the performance of the ventilation system. The results showed that the performance of the ventilation system blowing-sucking by reducing the current ratio improved exponentially. It was also found that one of the ways to improve the performance of the blowing – suction ventilation system is to reduce the direction of the blowing angle.

Abstract Multiple energy generating cycles such as tri-generation cycles, which produce heat and cold in addition to power through burning of a primary fuel, have increasingly been used in recent decades. On the other hand, advanced exergy analysis of thermodynamic systems by splitting exergy destruction into endogenous and exogenous parts identifies internal irreversibilities of each of the components and the effect of these irreversibilities on the performance of other components. Therefore, main sources of exergy destruction in cycles can be highlighted and useful recommendations in order to improve the performance of thermodynamic cycles can be presented. In the present work, a tri-generation cycle with 100 MW power production, 70 MW heat and 9 MW cooling capacity is considered. For this tri-generation cycle, effects of various thermodynamic parameters on the amount of endogenous and exogenous exergy destructions, exergy loss and the amount of fuel consumption, are investigated. The results indicate that, increasing compressor pressure ratio, pre-heater outlet temperature and excess air leads to better combustion and lower exergy loss and fuel consumption. Increasing the mass flow rate of steam generator, while keeping the cycle outlet temperature constant and considering cooling capacity variable, lead to increase the first- and second-law efficiencies of the cycle.

Abstract This study evaluates the performance of 75 clear-sky global irradiance models against 75 ground stations worldwide covering five major Koppen-Geiger climate classifications and overall global performance. After quality control, clear-sky detection and data-availability criteria, there are 4.36 million 1-min valid global horizontal irradiance (GHI) data points for evaluation. This study represents the most encompassing evaluation of its kind in terms of number of models assessed, number of ground stations used, most consistent selection of input variables in terms of temporal and spatial resolution, also using the most rigorous and fair performance assessment criteria and suitable ranking system. A statistically rigorous Principal Component Analysis (PCA) ranking procedure is proposed to replace the conventional ordering method based on single and simple statistics. In particular, it is demonstrated that all 13 error metrics contribute to the variance of GHI estimation and thus must all be accounted for in the ranking procedure. The best performing models in each climate zone of equatorial, arid, temperate, cold and polar are REST2v9.1, REST2v9.1, MAC2, REST2v5 and CLS, respectively. Globally, the top three performing models are MAC2, REST2v5, and REST2v9.1. Many models appear to suffer from over-fitting empirical relationships to training data, resulting in inconsistent worldwide performance. Furthermore, six different formulations of the Linke Turbidity factor (TL) are evaluated through its application to five clear-sky models that require it as an input. The best globally performing TL formulations are either by Ineichen or Gueymard when combined with four of the five Linke-dependent clear-sky models, whilst the Grenier formulation performs best with the Ineichen & Perez model. Significant performance variation is observed depending on the TL formulation selected, hence, careful selection is required for an optimal application. The model codes are available in R [1].

Abstract There are instances in remote areas where heat is being wasted, e.g., in internal combustion, engines, etc. Some of this heat can be recovered to produce distilled water in solar stills. The solar still replaces the cooling tower, ponds, or radiators normally used to control the engine temperature. The diesel cooling water in such a system remains separate from the saline water in the solar still. The advantages of using such a system compared with a conventional solar still are: 1. (a) water costs are very much reduced 2. (b) the area occupied is much less, i.e., about 1 5 th 3. (c) production has much less seasonal variation 4. (d) the efficiency of the solar still is improved due to the higher operating temperatures. From experiments conducted at Highett using a Mk VI solar still fitted with a simple heat exchanger and a separate electrically-heated source of hot water to simulate the waste heat, design data are not available for application to working systems. The information required to match a solar still to a diesel's cooling requirement is: 1. (a) engine efficiency 2. (b) hourly fuel consumption 3. (c) hourly solar radiation 4. (d) hourly ambient temperatures. A by-product of this work has been the production of a “solar water heater” which costs less than that of the cheapest conventional system. This “solar” hot water system uses a heat exchanger similar to what is used to transfer the waste heat to the saline water. It is envisaged to have hot water productions approximately the same as the distilled water productions. The influence of hot water production on the output of the waste heat solar still is discussed.

Concentrating solar power plant will be a key component of the future energy systems in which the share of renewable energy is extremely high. A major challenge of this technology is, however, its intermittent power output, slowing down its rate of implementation in the global energy matrix. As such, waste incineration is a popular technology in the developed countries as a smart measure for the disposal of municipal waste and generating free energy. In this study, a hybrid configuration of a concentrating solar power plant accompanied with a waste incineration unit is proposed. In the proposed system, the waste incinerator offers a variable heating duty in order to regulate the power output of the concentrating solar power plant. The hybrid plant is designed for a case study in Denmark and is thermodynamically analyzed. The results of the simulations are presented and discussed. It is shown that the hybrid system can pave the bed for increasing the share of solar thermal power and bringing more waste incinerators to the electricity market. A 10 MWe hybrid power plant may prevent up to 8000 tonnes of carbon dioxide equivalent emission per month. The overall efficiency of the hybrid system is expected to be 24%.

Iran, endowed with abundant renewable and non-renewable energy resources, particularly non-renewable resources, faces challenges such as air pollution, climate change and energy security. As a leading exporter and consumer of fossil fuels, it is also attempting to use renewable energy as part of its energy mix toward energy security and sustainability. Due to its favorable geographic characteristics, Iran has diverse and accessible renewable sources, which provide appropriate substitutes to reduce dependence on fossil fuels. Therefore, this study aims to examine trends in energy demand, policies and development of renewable energies and the causal relationship between renewable and non-renewable energies and economic growth using two methodologies. This study first reviews the current state of energy and energy policies and then employs Granger causality analysis to test the relationships between the variables considered. Results showed that renewable energy technologies currently do not have a significant and adequate role in the energy supply of Iran. To encourage the use of renewable energy, especially in electricity production, fuel diversification policies and development program goals were introduced in the late 2000s and early 2010s. Diversifying energy resources is a key pillar of Iran’s new plan. In addition to solar and hydropower, biomass from the municipal waste from large cities and other agricultural products, including fruits, can be used to generate energy and renewable sources. While present policies indicate the incorporation of sustainable energy sources, further efforts are needed to offset the use of fossil fuels. Moreover, the study predicts that with the production capacity of agricultural products in 2018, approximately 4.8 billion liters of bioethanol can be obtained from crop residues and about 526 thousand tons of biodiesel from oilseeds annually. Granger’s causality analysis also shows that there is a unidirectional causal relationship between economic growth to renewable and non-renewable energy use. Labor force and gross fixed capital formation cause renewable energy consumption, and nonrenewable energy consumption causes renewable energy consumption.

Abstract In Australia, the government spending on public buildings’ energy and water consumption is considerable; however the building energy and water retrofit market potential has been diminished by a number of barriers, especially financial. In contrast, in other advanced economies there are several reported financing strategies that have been shown to accelerate retrofit projects implementation. In this study, a coupled Bayesian Network – System Dynamics model was developed with the core aim to assess the likely influence of those novel financing options and procurement procedures on public building retrofit outcomes scenarios in the Australian context. A particular case-study focusing on Australian public hospitals was showcased as an example in this paper. Stakeholder engagement was utilised to estimate likely preferences and to conceptualise causal relationships of model parameters. The scenario modelling showed that a revolving loan fund supporting an energy performance contracting procurement procedure was preferred. Subsequently, the specific features of this preferred framework were optimised to yield the greatest number of viable retrofit projects over the long term. The results indicated that such a financing scheme would lead to substantial abatement of energy and water consumption, as well as carbon emissions. The strategic scenario analysis approach developed herein provides evidence-based support to policy-makers advocating novel financing and procurement models for addressing a government’s sustainability agenda in a financially responsible and net-positive manner.