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A new method of inter-stage double heat exchange is proposed, which combines compressed air energy storage with traditional coal-fired power unit. It can not only reduce the heat storage investment of compressed air energy storage system, but also broaden the peak regulation margin of coal-fired power unit, and promote the stability of power grid under high proportion of new energy access. In this paper, the characteristics of the coupling system under different working conditions of coal-fired power unit are studied, and the techno-economic calculation and analysis are carried out. The results show that the round-trip efficiency of the compressed air energy storage system coupled with the coal-fired power unit can reach more than 70% under different working conditions, and the return on investment and payback period are optimistic. Among them, the efficiency and economy of the system are the best when the coal-fired power unit is operating at 50%THA. At this time, the rate of return on investment can reach 18.44%, and the payback period is about 5.14 years. • A new method of inter-stage double heat exchange was proposed for coupling. • The thermodynamic model of the CAES system coupled with CFP unit was established. • The coupling performance and economic performance of the system were analyzed. • The round-trip efficiency of each working condition could reach more than 70%. • The payback period of each working condition was within 6 years. [ABSTRACT FROM AUTHOR]

The selection of suitable locations for rooftop photovoltaic projects (RPVP) is critical for optimizing power generation efficiency and return on investment. However, traditional methods of site selection that rely on subjective assessments of index weights can compromise accuracy, while complex calculations may limit adaptability to changing real-world data. In this study, we proposed a data-driven ensemble learning framework that integrates socio-economic, environmental, climate, and geography factors to optimize RPVP site selection. Using data from 1589 counties in China, we mapped eight criteria to feature variables to facilitate machine learning classification. Furthermore, the K-means algorithm was employed to enhance the model's robustness against outliers. The findings indicate that the proposed stacking model exhibits superior performance in comparison to other classifiers, as evidenced by the higher scores of performance metrics. Specifically, for positive instance prediction, the stacking model achieves the highest Precision scores. According to the rankings of Precision scores derived from the four ensembled models, we categorized counties suitable for RPVP development into five priority tiers. The ensemble learning framework provides a valuable and reusable tool for advancing county-level RPVP site selection and serves as a motivation for selecting other renewable power plant sites. • Ensemble learning is used in site selection of rooftop photovoltaic projects. • Stacking model presents the best performance on minimizing the erroneous selection. • The suitability of power plant siting is divided into several levels. • The proposed site selection tool can adapt to changing real-world environments. [ABSTRACT FROM AUTHOR]

It has been estimated that 17% of the recovered hydrocarbon exergy in oil fields [ 1 ] is spent on fluid handling and recovery costs. Therefore, improving the efficiency of oil production can give an some contribution to more efficient energy usage and therefore minimizing to some extent the carbon footprint. By way of example we present in this paper a work-flow, which can serve as a template for computing the fluid handling and recovery costs for natural polymer (Guar-Arabic Gum) flooding. The main contributors to the exergy investment in an Exergy Return on Exergy Investment analysis (ERoEI) are, the fluid circulation costs, the steel costs of the tubing and casing and to some degree the drilling costs. The main contributor to the exergy gain is the exergy of the produced oil. The fluid circulation costs represent the largest exergy investment and usually approximately accounts for 80% of the exergy used for the recovery of oil. For quantifying the circulation costs, the paper uses a 1-D displacement model of polymer flooding of oil to compare the enhanced oil recovery (EOR) history for three scenarios, i.e., (1) water injection, (2) natural-polymer water injection and (3) natural-polymer slug injection. The advantage of a 1-D model is that it allows multiple comparisons of many scenario's avoiding time consuming simulations but this goes at the expense of ignoring 3-D effects. The 1-D model can be extended to a 2-D or 3-D model, which makes it possible to include the improvement of vertical and areal sweep-efficiency. A numerical solution of the EOR model is obtained with COMSOL. We analyze the exergy balance of viscosified water, e.g., with natural-polymer. A comparison as to the displacement efficiency is made between the three scenarios, viz., water, Guar-Arabic gum, and slug injection. The viscosity behavior of Guar-Arabic gum is obtained from laboratory data. It is argued that an ERoEI analysis, which is used on its own or complementary to an economic analysis, can be used to show the advantage of using Guar-Arabic gum slugs with respect to permanent polymer-injection to enhance the oil recovery. Moreover, the analysis shows that at the end of the project, the concept of exergy-zero recovery time or zero-time marks, for each scenario the termination point, i.e., when the circulation exergy costs (exergy investment) become equal to the recovery exergy (exergy return), and thus recovery should be abandoned. For the conditions considered a single polymer injection displacement leads to optimal results. • Using a 1-D model of natural-polymer displacement it is possible to analyse the Exergy Return on Exergy Investment (ERoEI). • The investment costs are frequently mainly due to circulation costs (%80) of the exergy used for the recovery of oil. • A small rock permeability leads to high circulation costs, thus higher invested exergy costs. • The abandonment time occurs before the circulation exergy costs become equal to the recovery exergy costs. • A minimum exergy cost corresponds to minimum greenhouse gas emission. [ABSTRACT FROM AUTHOR]

A biomass product and process network that displays how organic waste and other non-traditional biomass feedstocks may be converted into useful bioproducts and biofuels is a necessary addition to the field of biomass conversion and utilization. We develop a processing network of 216 technologies and 172 materials/compounds that contains conversion pathways of agricultural and organic waste biomass sources, such as food peels, animal manure, and grease. To examine the effectiveness and economic feasibility of these conversion pathways, the biomass product and process network is optimized for return on investment. The resulting problem is a data-driven two-stage adaptive robust mixed-integer nonlinear fractional program, which was effectively solved via a tailored optimization algorithm. The proposed approach is applied to two case studies in which traditional agricultural feedstocks are used alongside biological and agricultural waste feedstocks. The selected feedstocks were used to satisfy and, in some cases, even exceed demand for selected products. The optimal pathways have returns on investment of 26.1% and 6.2%, with utilized conversion technologies ranging from hydrocracking to microwave hydrodiffusion. In both cases, we find that profitable processing pathways are utilized at maximum capacities to increase return on investment. Specifically, in the case study where orange peel wastes are used to produce pectin, we find that this pathway is highly profitable at the given market price. The two cases that are run using the proposed model are then compared to additional cases to display differences that arise when uncertainty is not considered and the objective function of the model is changed. • The expanded biomass product and process network is described. • Two-stage data-driven ARO is applied to a biomass product and process network. • Case studies, computational results, and future applications are discussed. • A novel application of the proposed computational algorithm is presented. [ABSTRACT FROM AUTHOR]

The simultaneous design of units and the integration of processes reduce the amount of required equipment and energy consumption. Types of research in recent years have turned their attention to improving the efficiency of thermal and heat recovery systems. This paper aims to develop an integrated structure for simultaneous generation of power and liquefaction of carbon dioxide. The hybrid system consists of four sections: oxy - fuel power plant for power generation with CO 2 capture, pure oxygen production using the air separation unit, carbon dioxide liquefaction system using an absorption refrigeration cycle and heat supply using solar dish collectors. The integrated design has the capacity of producing 26.27 kg/s of liquid carbon dioxide and 179 MW of power. Exergy analysis shows that the maximum exergy destruction belongs to the distillation towers at 24.73%, and the minimum exergy destruction is for air coolers at 0.113% compared to other equipment. Accordingly, the total exergy efficiency of the whole integrated structure is 60.74% and the total exergy destruction is 416 MW. The economic analysis of the integrated structure shows that the period of return is 3.3 years, and the prime cost of the product is 3.04 cents/kWh. Furthermore, by using sensitivity analysis the important and effective parameters of the developed integrated structure was investigated. • Air separation unit, oxy-fuel power generation and CO 2 capture with solar dish collector hybrid system are introduced. • Solar dish collectors produced heat is used as heat source of absorption refrigeration, steam power cycle and ORC power generation. • Total energy and exergy efficiencies of the hybrid system are 37.1% and 60.74%. • Rate and period of investment return were obtained 30.33% and 3.3 years respectively. [ABSTRACT FROM AUTHOR]

With rapid development of information technology, the number and scale of data centers (DCs) increase rapidly. Therefore, cooling energy saving becomes crucial. This study proposes multi-criteria assessments of increasing supply air temperature (SAT) in the air-cooled DCs to analyze the interactions of internal and external factors in cooling systems comprehensively. Impacts of refrigerant charge (RC), evaporation pressure (EP) control limits, and hot aisle containment (HAC) with improvements in SAT are compared and analyzed according to the thermodynamic, economic, and thermoeconomic aspects. Overall, as SAT increases from 20 °C to 32 °C, the power usage effectiveness decreases by 16.8%–19.3%. Increase in RC leads to energy consumption and cost increasing at high SAT ranges, whereas high RC shows obvious advantages at the low SAT from the thermoeconomic aspects. Additionally, releasing EP control limits has significant advantages in reducing energy usage, and cumulative present worth of data center testbed can decrease by 5.2% and 6.0% at low and high RC operations, respectively. Return on investment and payback period analysis are also performed in the testbed with the HAC reform, and the payback period is about 1–3 years with the SAT setting range at 20–32 °C. • Increasing supply air temperature (SAT) is assessed in a tropical data center (TDC). • Impact of refrigerant charge, control limit, and hot aisle containment is analyzed. • Operation parameters are required to regulate with an increase of SAT. • Payback period of TDC with hot aisle containment reform is 1–3 years in this study. [ABSTRACT FROM AUTHOR]

The Algerian government has established an attractive policy to encourage investment in the wind energy by installing 5 GW of wind power by 2030. It has focused on collaborations and calls for investment from outside wind energy companies. However, this energy sector development requires the identification of potentially windy sites. This study was performed in order to determine new optimal sites in Algeria that may be eligible to receive the wind farm projects. Therefore, data from about 74 new sites were identified and assimilated to verify and update the wind resource estimates. Hourly wind speeds data were used for the establishment of the annual and seasonal wind maps at 10 m and 80 m a.g.l. As the wind map updates highlighted important changes in the wind resource, the wind potential sensitivity to the data time period was evaluated. The windy sites were classed on the basis of the NREL international standards. However, In order to ensure an adequate return on investment, the other objective of this study was to identify the optimal sites using a multi-criteria analysis based on the GIS method. Considering additional factors as network availability and wind energy previsions, different strategic scenarios of wind farms planning were proposed. [ABSTRACT FROM AUTHOR]

Energy return on energy invested (EROI) might be considered a measure of net energy, and most current studies focus on standard EROI (EROI ST ). If the energy inputs required to obtain a fuel was extended from a wellhead to the point of use, the energy delivered decreases, and the energy input of delivering the fuel increases. These factors combine to reduce the EROI ST to what is referred to as the point of use EROI (EROI POU ). This study calculates the direct and indirect energy (embodied energy) inputs for energy production sectors (including extraction, processing and delivery) by means of an Input-Output table to calculate China's EROI POU and the net energies from 1987 to 2012. Based on calculations in this study, the EROI POU of China's energy production sector declined from 11.01:1 to 5.26:1 between 1987 and 2012. In 1987, the energy production sectors consumed 1 ton standard coal equivalent (TCE) energy inputs for every 10.01 TCE of produce net energy. However, in 2012, this number declined to 4.25. Additionally, this study simulates and forecast economic Gross Domestic Product (GDP) trends in China using net energy production function. The results reveal how declining EROI POU for Chinese fossil fuels influence China's GDP growth. [ABSTRACT FROM AUTHOR]

Mankind's prosperity has been dependent on availability of affordable energy in the recent centuries. Today, the need of sustainability requires precise energy efficiency evaluation. Unfortunately, the traditional metrics like energy return on investment (EROI) suffer from the system boundaries and from the inability to describe labor and physical capital in terms of energy. Therefore, they tend to omit up to 50% of input energy consumption. The price of energy model (PERM) and cost of energy model (CERM), derived via matrix description of production process, show that the ratio of the average energy input cost to the average useable energy output cost describes energy efficiency completely. The same holds for the ratio of energy prices, if shares of aggregate rents, taxes and subsidies in the input and output prices are similar. The above price (cost) ratio can serve as an EROI check and eliminate the need for a lengthy process analysis. The results enable the extension of energy efficiency metrics by social and environmental effects, measurable mostly in monetary terms. [ABSTRACT FROM AUTHOR]

To consider the environmental impacts of energy resource exploitation and better estimate the energy return of investment (EROI), this paper establishes a new emergy-based method (EmEROI) that can capture the essence of energy resource exploitation. The EmEROI method treats environmental impacts and labor as particular forms of energy, and all forms of energy can be quantified by solar transformity, which is expressed in emjoules as a common unit. The Daqing oilfield is used as an example, and the corresponding EmEROI value is calculated via the proposed method. The results are then compared with standard EROI estimates. Our EmEROI result is much lower than the standard EROI result and presents a more pronounced declining trend. Our results also indicated that the EmEROI estimates conform well to actual conditions and are not as affected by industrial energy intensity levels as the standard EROI. Thus, EmEROI has the potential for use as an integral aspect of energy resource exploitation project evaluations. [ABSTRACT FROM AUTHOR]

A recent upsurge of investment in photovoltaic (PV) industry in China has made outstanding contributions to the adjustment of energy structure. In order to further promote the investment and construction of PV projects, the state has published many fiscal subsidy policies. In addition to unified national subsidy standard, local standards have been developed according to local fiscal revenue. They either have greatly improved return on investment (ROI) or have no significant effect as a result of too many impact factors. This paper utilizes multi dimensional big dates of distributed PV projects to obtain the weight of factors influencing the ROI from the calculation equation of ROI, which is fitted with innovative big data mining method of LSSVM-PSO. Results show that construction cost, sunshine duration, retail electricity tariff and subsidy have the greatest impacts. This study provides decision makers with quantitative basis for more comprehensive understanding on economic aspect of the distributed PV projects. [ABSTRACT FROM AUTHOR]

This paper addresses the deciding under uncertainty of an electricity retailer in order to maximise its total expected rate of return. The developed methodology is based on the modelling of the stochastic evolution of zonal prices that seeks to manage a portfolio of different contracts. Retailer's load and the price at each zone are forecasted using the seasonal autoregressive integrated moving average (SARIMA) model and a clustering technique is used for scenario reduction. Supply sources include the pool, self-production facilities, forward and bilateral contracts. The risk of cost fluctuation due to uncertainties is explicitly modelled using the multi-scenario drawdown methodology. This risk function quantifies in aggregated format the frequency and magnitude of the portfolio drawdowns over planning horizon. In-sample and out-of-sample runs are performed for a portfolio allocation problem. Carried out experimental results on the basis of realistic data, show that imposing risk constraints improve the “real” performance of a portfolio management in out-of-sample runs. [ABSTRACT FROM AUTHOR]

As a carbon reduction technology, CCUS (Carbon Capture, Utilization and Storage) is an important way to achieve the goal of "carbon peak and carbon neutrality" in China. In order to change the situation of slow commercialization and large-scale development of CCUS, this paper proposes to establish a CCUS cooperative alliance. Taking alliance organizers, institutional investors, upstream operators and downstream operators as research objects, the evolutionary game model is developed to reveal the dynamic evolution mechanism of CCUS cooperative alliance and analyze the impact of exogenous variables on the strategic choices of alliance members. The results show that: (1) establishing a strong market-oriented alliance can promote the large-scale deployment and commercialization of CCUS, (2) when return on investment is greater than or equal to 6%, it can effectively promote the investment of institutional investors in CCUS field, (3) when the government subsidy rate is greater than or equal to 75%, the willingness of downstream operators to operate independently is significantly enhanced. This study reveals the operation mechanism of the alliance, provides theoretical and methodological support for the operation and management of the alliance, and is of great significance to promote the cooperative operation and development of the alliance. • A CCUS cooperative alliance with commercial characteristics is proposed. • An evolutionary game model is developed to reveal evolution mechanism of alliance. • ROI of 6% or more can promote institutional investors' investment in CCUS. • Subsidy rate of 75% or more can urge downstream operators to operate independently. [ABSTRACT FROM AUTHOR]

A high gas production rate is critical for commercial exploitation of hydrate. Most marine hydrates deposit in the silty or clay sediments with low permeability, and gas production rate is low. Herein, a novel deployment of well, radial three-branch horizontal well was numerically investigated to enhance the gas production. A 3D geological model was established based on field trial in the Shenhu Area of the South China Sea. The simulation showed similar gas and water production for single and multi-branch horizontal wells with same length of 250 m. The depth in which well deployed dramatically affects the gas and water production, and which increases with the length of multi-branch well. Meanwhile the ratio of free gas originally distributed in three-phase and gas layers also increases with the length, which is 50% for 1200 m well. The interference around the intersection of branches enhances temperature recovery and the dissociation of underlying hydrates. The standard energy return on investment analysis shows that the economic potential increases linearly with the length of multi-branch well and obviously depends on the content of initial free gas. However, the production balances investment confines only to tens or hundreds of days for all model scenarios. • A novel radial three-branch horizontal well is adopted to investigate the enhancement of gas production from hydrate. • Depth of multi-branch well (various contact formation) highly affects gas production. • The deployment of the horizontal well within three-phase layer is feasible for high gas production. • Interference of branches enhances temperature recovery rather than gas recovery. • Cost-benefit balance is analyzed and further technical improvement is needed to meet the economic criterion. [ABSTRACT FROM AUTHOR]

Manufacturers lack the economic tools to properly perform maintenance procedures to increase manufacturing reliability while reducing system energy consumption. A return on investment strategy is developed to provide plant managers with a quantitative method to optimize the maintenance actions that lead to the largest return on investment. Over the long term, this energy economic analysis results in the largest decrease in energy costs for a manufacturing facility. A control methodology is developed to increase profits on a daily basis by inserting energy opportunity windows at various machines thus reducing energy consumption with minimal production impact. A simulation case study is performed to validate the return on investment strategy and to test the control methodology's impact on the overall profit of the facility. [ABSTRACT FROM AUTHOR]

The use of district heating systems consisting of a combined heat and power (CHP) and a heat only boiler (HOB) is on the rise in South Korea. In this context, monopolistic district heating providers optimise cogeneration capacity composition to maximise their profits under price regulation. Building upon Joskow and Jones (1983), this study develops a theoretical framework to investigate the role of price regulation on the optimal capacity composition of a district heating system for a regional monopolist. Assuming varying heat demand, wherein the maximum heat load may exceed CHP capacity, the effects of price-cap and rate of return regulations on the optimal mix of the district heating system are examined and compared. The results show that the heat production mix is optimal for price-cap regulation. In contrast, the rate of return regulation hinders the monopolist's incentive to reduce costs. Finally, in case of internalising the environmental benefits of cogeneration, the optimal CHP size in the heat production mix should be increased; consequently, the energy efficiency for producing heat and electricity is likely to improve. This study, therefore, has far-reaching implications for policymakers and practitioners alike in terms of addressing the dual goals of energy efficiency and economic efficiency. • Monopolistic district heating providers should choose optimal capacity composition. • We investigate price regulation for capacity composition in a district heating system. • The effects of PC and RoR regulations on the optimal mix are examined. • The heat production mix is optimal under a PC regulation. • The RoR regulation hinders the monopolist from reducing costs. [ABSTRACT FROM AUTHOR]

In this paper we explore the impact of a feed-in tariff (FIT) reduction in combination with the introduction of a renewable portfolio standard (RPS) on the development of distributed photovoltaic generation (DPVG) in China. This is done using system dynamics models that can simulate a DPVG's return on investment, installed capacity, levelized cost of electricity, and grid parity for multiple scenarios. The results show that the FIT reductions have a short-term negative effect on the DPVG installations. However, they can be performed in China without sacrificing the grid parity goal. In fact, FITs could be completely cancelled within the next 2–3 years. It is more effective to simply cancel the FITs after maintaining the current FITs for several years compared to a slow FIT reduction every year. After the FITs are cancelled, an RPS can effectively help continue the trend towards grid parity. However, we also need to consider the relation between the RPS quota, the installed capacity, and the tradable green certificate-supply/demand/price. The DPVG industry has already realized the demand-side grid parity, while residential- and commercial-DPVG are expected to reach the supply-side grid parity within 4–7 years and 5–8 years, respectively. • Development of a system dynamics model of China's distributed PV generation. • Simulation and cost/investment analysis with different scenarios. • Effect of feed-in tariff reductions and introduction of renewable policy standard. • Grid-parity analysis of residential and commercial distributed PV generation in China. [ABSTRACT FROM AUTHOR]

Microwave-assisted wet torrefaction (WT) was investigated for the co-torrefaction of optoelectronic sludge (OS) and fruit waste. The factors of torrefaction temperature (120–180 °C), reaction time (10–40 min), biowaste types of Mangifera indica seeds (MIse) and Passiflora edulis shells (PEsh), and blending ratio of OS and biowaste were investigated. Blending OS with two biowaste types separately at different blending ratios increases the biofuel quality and mitigates the problem of waste disposal. Blending OS with MIse at a ratio of 25/75 under the same WT condition further increased the HHV of 19.0 MJ/kg while retaining a high energy yield of 92.1%. Thermogravimetric analysis and derivative thermogravimetry results confirmed that the properties (particularly dehydration and devolatilization) pertaining to the thermal stability of co-torrefied biochar were superior to the raw OS. Furthermore, the 10%–20% co-torrefied biochar can replace sub-bituminous coal and reduce the global warming potential. Co-firing the obtained biochar with bituminous coal could aid in achieving high combustibility (fuel ratios of 1.60–1.82), high energy efficiency (energy return on investment of 14.7), and environmental sustainability (approximately 6.6%–13.2% less greenhouse gas emissions than bituminous coal). In summary, microwave-assisted WT is a potential technology for producing renewable energy. [Display omitted] • Microwave-assisted wet co-torrefaction of optoelectronic sludge and fruit waste to mitigate the problem of waste disposal. • A higher heating value of 19.0 MJ/kg can increase the biofuel quality. • The energy return on investment of 14.7 can achieve high energy efficiency. • CO 2 emissions reduced 65.8% compared with using biochar for substituting bituminous coal. [ABSTRACT FROM AUTHOR]

Holiday cycling refers to the occasional use of bicycle during holidays as an alternative mode of transportation for exploring a destination, comprising a promising line of business for rental services of both conventional and electric bicycles (e-bikes), not only in countries with well-established cycling culture, but also in other tourist destinations. This paper advances the notion that a hotel-based e-bike rental service significantly contributes to the guests' perception on the environmental quality and friendliness of the hotel, particularly if the e-bikes are powered by renewable energy sources, as a tourism product offering in the context of sustainable mobility. To that end, the present work employs a stated preference survey among hotel guests in the city of Mons, Belgium, to capture and analyze the user profile characteristics and preferences. Based on the survey results, it simulates two alternative implementations of the e-bike charging station with a well-established energy systems analysis tool and evaluates the techno-economic feasibility of the proposed service under different usage and pricing scenarios. The findings of this work show that all scenarios lead to positive internal rate of return and return on investment, rendering the proposed e-bike rental service a promising business venture. • A survey on e-bike rental to identify hotel guests' profile and stated preferences. • Environmental friendliness is indicated as the primary reason for e-bike rental. • Dependence on weather conditions is the dominant counter-motive of e-bike rental. • Different system configurations, levels of usage and service pricing are examined. • Techno-economic viability of the proposed e-bike rental service as an investment. [ABSTRACT FROM AUTHOR]

In this investigation, three chemical processes for biodiesel production evaluated based on the financial standpoint. Due to its strongness and flexibility in economic evaluations, the COMFAR III software utilized for assessing processes. The alkali catalyzed process using virgin vegetable oil (process I), an-acid catalyzed process utilizing waste cooking oil (process II), and two-step supercritical methanol process using waste cooking oil (process III) considered as three deferent chemical processes and financial analyzes applied on all processes. The results of financial evaluation revealed that the process II with 2.992 million $, had the lowest manufacturing prices and with 7.541 million $ net present value would be considered as the most attractive proposal for investment. However, concerning total equipment costs of process III (1.141 million $) and its fixed investment prices (2.158 million $), this process selected as the most economically attractive process. In the next step, to evaluate the impacts of increased sales revenue, reduction in fixed assets, and operating costs on net present value, a sensitivity analysis was carried out. Sensitivity evaluation revealed that alteration in operating costs significantly impacts the net present value, and this significant change is more tangible in the process III. • Establishing biodiesel plants from edible oil wastes are investigated. • Three different chemical processes are considered and economically evaluated. • By considering parameters and altering them, processes are analyzed economically. • Regarding the costs of process III, it is selected as the most affordable plant. [ABSTRACT FROM AUTHOR]

The levelized cost of electricity (LCOE) is a metric commonly used in the academic literature. Electricity-supply projects can be financed by the project developer, equity partners, or through debt, with the timing of investments and returns different for all three. The LCOE metric is equally applicable to all three sources of financing although the calculation does not explicitly represent these differences in timing. The LCOE metric implicitly assumes that surplus revenue earned during the operation of a powerplant can be re-invested with a rate of return equal to the return on equity, an assumption that is not valid. A modified LCOE equation that accounts for this difference and for steadily declining output and increasing O&M costs is presented here. The errors entailed in using a simple weighting of the returns to equity and debt (the weighted average cost of capital, WACC) in the non-linear LCOE equation entails an error of less than 0.5% if the interest rate on surplus revenues equals the discount rate. Otherwise, it is necessary to separately consider the equity and debt financing portions (even if returns to equity and debt are the same, as the modified LCOE equation applies only to the debt portion). • The LCOE equation is equally applicable to alternative financing structures. • A modified LCOE equation accounts for interest rate differing from discount rate. • A modified LCOE equation accounts for increasing O&M costs and declining output. • Use of WACC should be abandoned in favor of separate debt and equity calculations. [ABSTRACT FROM AUTHOR]

The objective of this study was to propose a fusion-biomass hybrid system with fuel cell and gas turbine as a technical option for fusion application to generate electricity. Fusion reactor with dual coolants lithium lead (DCLL) blanket design employing SiC f /SiC could provide over 900 °C of high temperature heat for waste biomass gasification process. Waste biomass such as municipal waste solid and residues from agricultural and forestry sites could be sufficiently processed. A small scale conceptual fusion reactor GNOME is designed under the assumption that the system will be deployed in a place where a low amount of waste biomass is generated. Results showed that 364 MW GNOME reactor could produce 410 MW th power through divertor and blanket according to fusion power plant system analysis code (FUSAC). The hybrid system enables to generate 454 MW e with 80% capacity factor which is 7008 h operation in a year. Net electricity of 289 MW e could be produced through solid oxide fuel cell (SOFC) and gas turbine showed 30% of overall system efficiency due to the high self-consumption of GNOME reactor. The levelized cost of electricity (LCOE) is 208 $/MWh and the energy return on investment (EROI) is 3.9. • A conceptual small scale of fusion reactor 364 MW GNOME is designed. • The efficiency of the fusion-biomass hybrid system is 30%. • Levelized cost of electricity (LCOE) is 208 $/MWh. • Energy return on investment (EROI) is 3.9. • Development of promising technologies, fusion and fuel cell, will improve LCOE and EROI. [ABSTRACT FROM AUTHOR]

The techno-economic feasibility of three biogas utilization processes was assessed through computer simulations on commercial process simulator Aspen HYSYS: HPC (biogas to methanol), BioCH 4 (biogas to biomethane) and CHP (biogas to heat & electricity). The last two processes are already used commercially with the aid of subsidy policies. The economic analysis indicates that, without these policies, none of these attain economic self-sustainability due to high overall manufacturing costs. The estimated minimum support cost (MSCs) were 108, 62 and 109 €/MWh for the HPC, BioCH 4 and CHP processes, respectively. The model could explain currently practised government subsidies in Italy and Germany. It was seen that the newly proposed HPC process is economically comparable to the traditional CHP process. Therefore, the HPC process is a possible alternative to biogas usage. A support policy was proposed: 50, 66, 158 and 148 €/MWh for available heat, methane, electricity and methanol (respectively); the proposed energy policy results in a 10% OpEx rate of return for any of the processes, thus avoiding a disparity in the production of different products. Image 1 • Techno-economic analysis of three different biogas utilization concepts. • HPC (methanol) Vs BioCH4 (biomethane) Vs CHP (heat & electricity). • Computer simulations are performed using commercial process simulator Aspen HYSYS. • BioCH4 process is the most competitive (62 €/MWh minimum support cost). • A support policy is proposed; it gives equal economic opportunity to all processes. [ABSTRACT FROM AUTHOR]

Shale oil produced from oil shale pyrolysis is regarded as an important alternative to crude oil. There is the conventional oil shale pyrolysis technology represented by Fushun-type, which suffers from low utilization efficiency of oil shale and low shale oil production. The development of the indirectly heated moving bed technology can solve these problems. However, this new technology requires extra heat for oil shale pyrolysis which means low pyrolysis efficiency and it also suffers from the production of low quality shale oil. The driving force for the efficient pyrolysis of oil shale and high-value conversion of shale oil calls for the involvement of high-value fuel to supply heat for pyrolysis and hydrogen source for shale oil upgradation. Coal is produced in the process of oil shale mining. A new process of coal-assisted oil shale refinery is therefore proposed in this study. Coal is used for gasification to produce syngas. Part of the syngas is used as fuel to supply additional heat for oil shale pyrolysis and the remaining syngas is used to produce hydrogen, which is then used for shale oil hydrogenation to increase the quality of shale oil. Results show that the energy efficiency of the new process is increased by 5%–24% and has a 53%–75% increase of the return on investment, comparing to those of the conventional Fushun-type technology. Image 1 • Proposed a new process of coal-assisted oil shale efficient pyrolysis and high-value conversion of pyrolysis oil. • Improved energy efficiency by 5%–24% in the new process. • The integrating process resulted in 53%–75% increase of return on investment. [ABSTRACT FROM AUTHOR]

The improvement in the efficiency of an energy plant depends on a rational development of its flowchart and choice of parameters along with the load schedule, equipment reliability, operating mode, etc. It is advisable to study such complex technical systems with the methods of mathematical modeling and optimization. The paper presents an approach to the development of optimal flowcharts and selection of parameters of energy plants. The approach is based on the combination of a method for optimization of the most complex flowchart and a method for solving discrete-continuous problems of nonlinear mathematical programming. A case study of the co-optimization of design parameters, operating parameters and equipment mix for the integrated gasification combined-cycle plant is demonstrated. The optimization calculations were carried out by the criterion of the minimum price of electricity for a given internal rate of return on investment and the maximum energy efficiency of the plant. Several optimal solutions meeting the different criteria are obtained. The proposed approach can be used for optimization of flowcharts and parameters of other complicated energy plants (high-efficiency combined-cycle plants, ultra-supercritical steam cycles, integrated power plants for electricity and synthetic liquid fuel co-production from coal, etc.). • An original approach to the optimization of energy plant flowchart is proposed. • The approach is based on modeling the most complex flowcharts. • The branch-and-bound method is used in flowchart optimization. • The focus is made on the optimization of an integrated gasification combined cycle plant. • Several optimal solutions meeting the different criteria are obtained. [ABSTRACT FROM AUTHOR]

Energy Return on Investment (EROI) is an indicator of how efficient is an energy supply system. In the present study, the conventional approach of EROI assessment is extended to include the equivalent energy investment needed for offsetting the life cycle environmental impacts. Moreover, the issue of allocation of the invested energy among different by-products is addressed. The EROI of multiple products has been specified using different benchmarks of price, energy content, exergy content, and exergy costs. The application of the concept is demonstrated through a case study of an Iranian oil production unit. The overall conventional and environmentally-extended EROI values of the produced oil in Iran is estimated to be 26.8:1, 23.3:1, respectively. Also, when taking the downstream environmental emissions into account, the EROI will be as low as 6.8:1. This shows that the EROI may be overestimated by 75% if the embodied costs are not taken into account. The comparison of the aggregated EROI estimates based on state-properties (price, energy, and exergy) and disaggregated process-property (exergy cost), gives a measure of the error of aggregation. It is shown that this error may be as high as 11.5% in the case of the multi-product energy system of the studied case. Image 1 • The EROI of a multi-product oil and gas production unit in Iran is assessed. • LCA is used to obtain environmental externalities as an embodied energy investment. • Consideration of LCA emissions and indirect energy investments reduces EROI by 75%. • The exergy cost-based allocation of the invested energy is investigated. • Improper allocation of invested energy results in an error of aggregation of 11.3%. [ABSTRACT FROM AUTHOR]

An analysis of Brazilian public costs indicates that, although a significant part of its financial resources is destined for electricity consumption, only a small portion of the distributed generation belongs to public institutions. A technical and economic analysis of a PV power plant in the Brazilian public sector was proposed and various scenarios were evaluated, indicating that a change in the Brazilian tariff policy could be an alternative for boosting PV generation in the public sector. Risk analysis demonstrated that the minimum acceptable rate of return is the variable that most affects the system's viability. In addition, a Monte Carlo Simulation (MCS) showed that the proposed PV system has a viability probability higher than 92%. A statistical analysis indicated that the system has a probability of at least 80% for supplying more than 25% of the building's peak demand for all seasons. Finally, such systems have also been found to represent an alternative for improving the electricity grid's stability, while supplying part of the building's energy demand. • A PV power plant was projected for a building of a Brazilian public university. • The variable that most affected the system viability is the MARR. • Changes in the tariff policy could boost the PV generation in the public sector. • There is an 87% chance of the maximum inverter power being reduced in at least 25%. • Similar systems can reduce the summer peak consumption in public buildings. [ABSTRACT FROM AUTHOR]

This study aimed to identify the financial indicators that strongly affect the return on equity (ROE) in the Romanian energy industry. Literature has revealed that firms that benefit from a higher ROE ratio often have some competitive advantage that allows for greater profit and thus greater return for investors. In this context, it seems absolutely necessary to identify and study those factors that have the strongest influence on ROE. The research was carried out on a sample of 1253 companies from the Romanian energetic industry. To identify the most powerful drivers of ROE we used a linear regression model. Also, the analysis was performed on three groups of companies, divided by their size to see any differences in drivers of ROE, depending on the company's belonging to a particular group. Other financial ratios were introduced into the research. Thus, the study involved the use of five indicators/ratios that were believed to have a major influence on ROE. According to the results we have obtained, asset turnover, price to earnings, price to book and financial leverage were the most relevant ratios to determine ROE, with the indication that asset turnover and price to earnings have had the strongest influence. • We analyzed the impact of some financial indicators on the return on equity ratio. • The research was performed for the energy industry using a DuPont based analysis. • Asset turnover, price to earnings, price to book, financial leverage influence ROE. • Asset turnover and price to earnings have the strongest influence on the ROE ratio. [ABSTRACT FROM AUTHOR]

Smart homes have the potential to achieve efficient energy consumption: households can profit from appropriately scheduled consumption. By 2020, 35% of all households in North America and 20% in Europe are expected to become smart homes. Developing a smart home requires considerable investment, and the householders expect a positive return. In this context, this work addresses the following question: what and/or when equipment should be bought for a specific site to gain a positive return on the investment? This work proposes a framework to guide the smart-home transition considering customized electricity usage. The framework is based on linear models and gives a simple payback analysis of each combination of equipment acquisition for any specific user taking into account geographical location and local conditions. It also possible to use the framework for equipment sizing. The results quantify the dependence of the simple payback on the site and the application. • Modeling and optimization of the integration of smart home components. • General framework for the optimal set of smart appliances and investment timing. • Maximization of the return on investment. • Economic feasibility shown for three case studies in different countries using real data. • Quantification of the payback for each site and application. [ABSTRACT FROM AUTHOR]