• Energy Research
• 7. Clean energy close

Abstract The main hindrances to the large-scale development of renewable-energy projects are the lack of bankability and the inability to align investments and investors with suitable financial instruments or robust policy measures. To illustrate a bankable project, this paper presents a research-based case study on the installation of solar photovoltaic panels on the rooftops of 195 trains of the Indian Railways. Detailed information on the annual running hours, exposure to sunlight, efficiency of solar photovoltaic generation and electrical power demands of each rail coach is considered to conduct a quantitative measure of the tentative amount of fossil fuel savings. The purpose is to provide insight into the types of renewable-energy projects that can be highly attractive to financial institutions and promoters due to their lucrative internal return on investment. As seen in this case study, there are annual savings in diesel of 12 323 088 litres and a CO2 reduction of 32 755 tonnes, with return on investment of 1.3 years. Furthermore, this study conducts a comprehensive analysis of the limitations of existing renewable-energy project financing mechanisms in India. Subsequently, three policy measures are recommended to develop a robust financial mechanism that can effectively meet the needs of investors and investors. These measures include increasing equity injection through a buy-and-hold strategy, providing direct tax benefits to promoters and financing through real-estate investment trusts. The findings are highly relevant to address the challenges associated with bridging the financial gap between access to finance and capital investment in the renewable-energy sector, especially for Asian countries.

Abstract In this work, energy analysis is carried out to account for inputs and outputs of energy and GHG emissions associated with the biodiesel production system. Jojoba oil is obtained by cultivation of the jojoba plant, harvesting of seeds followed by extraction of oil, which is then converted to biodiesel by the process of transesterification. Energy efficiency is expressed in terms of the net energy balance (NEB) and the net energy ratio (NER). The use of the byproducts (husk, cake or meal, waste residues and glycerin) are also included as a part of the system boundary. The results show that the NEB and NER values are calculated at 46724.1 MJ/ha (28.9 MJ/L biodiesel produced) and 2.16, respectively. At the same time, the total amount of GHG emissions are estimated at 2.28 kg-CO2eq/L biodiesel produced (66.0 g CO2eq/MJ biodiesel produced). Nevertheless, if manure is used as fertilizer for jojoba plant cultivation, the primary energy input will fall by 9.52% (to 22.49 MJ/L of biodiesel).

Reduced scale experiments are often employed in engineering because they are much cheaper than real scale testing. Unfortunately, though, it is difficult to design a thermal-hydraulic circuit or equipment in reduced scale capable of reproducing, both accurately and simultaneously, all the physical phenomena that occur in real scale and operating conditions. This paper presents a methodology to designing thermal-hydraulic experiments in reduced scale based on setting up a constrained optimization problem that is solved using genetic algorithms (GAs). In order to demonstrate the application of the methodology proposed, we performed some investigations in the design of a heater aimed to simulate the transport of heat and momentum in the core of a pressurized water reactor (PWR) at 100% of nominal power and non-accident operating conditions. The results obtained show that the proposed methodology is a promising approach for designing reduced scale experiments.

Short-term load forecasting is an essential instrument in power system planning, operation and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance planning for the generators. Overestimation of electricity demand will cause a conservative operation, which leads to the start-up of too many units or excessive energy purchase, thereby supplying an unnecessary level of reserve. On the contrary, underestimation may result in a risky operation, with insufficient preparation of spinning reserve, causing the system to operate in a vulnerable region to the disturbance. In this paper, semi-parametric additive models are proposed to estimate the relationships between demand and the driver variables. Specifically, the inputs for these models are calendar variables, lagged actual demand observations and historical and forecast temperature traces for one or more sites in the target power system. In addition to point forecasts, prediction intervals are also estimated using a modified bootstrap method suitable for the complex seasonality seen in electricity demand data. The proposed methodology has been used to forecast the half-hourly electricity demand for up to seven days ahead for power systems in the Australian National Electricity Market. The performance of the methodology is validated via out-of-sample experiments with real data from the power system, as well as through on-site implementation by the system operator.

This paper examines and optimizes parameters that affect the air cooling of a Lithium-Ion (Li-Ion) battery, used in Electric Vehicles (EVs). A battery pack containing 150 cylindrical type Li-Ion battery cells in a PVC casing is investigated. An equal number of tubes are used in the pack as a medium to cool the battery by using a fan when the vehicle is stationary or with ambient air when in motion. The parameters affecting the air cooling of battery are studied and optimized by considering their practical constraints. The objective function and Number of Transfer Unit (NTU) are developed. Finally, a genetic algorithm method is employed to optimize the decision variables. Analysing the results shows that NTU can be maximized by increasing the diameter of tubes on the battery and keeping the air velocity in a certain range.

AbstractBioenergy projects can lead to direct and indirect land use change (LUC), which can substantially affect greenhouse gas balances with both beneficial and adverse outcomes for bioenergy's contribution to climate change mitigation. The causes behind LUC are multiple, complex, interlinked, and change over time. This makes quantification uncertain and sensitive to many factors that can develop in different directions—including land use productivity, trade patterns, prices and elasticities, and use of by‐products associated with biofuels production. Quantifications reported so far vary substantially and do not support the ranking of bioenergy options with regard to LUC and associated emissions. There are however several options for mitigating these emissions, which can be implemented despite the uncertainties. Long‐rotation forest management is associated with carbon emissions and sequestration that are not in temporal balance with each other and this leads to mitigation trade‐offs between biomass extraction for energy use and the alternative to leave the biomass in the forest. Bioenergy's contribution to climate change mitigation needs to reflect a balance between near‐term targets and the long‐term objective to hold the increase in global temperature below 2°C (Copenhagen Accord). Although emissions from LUC can be significant in some circumstances, the reality of such emissions is not sufficient reason to exclude bioenergy from the list of worthwhile technologies for climate change mitigation. Policy measures to minimize the negative impacts of LUC should be based on a holistic perspective recognizing the multiple drivers and effects of LUC.This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

This paper investigates battery preheating before fast charging, for a battery electric vehicle (BEV) driving in a cold climate. To prevent the battery from performance degradation at low temperatures, a thermal management (TM) system has been considered, including a high-voltage coolant heater (HVCH) for the battery and cabin compartment heating. Accordingly, an optimal control problem (OCP) has been formulated in the form of a nonlinear program (NLP), aiming at minimising the total energy consumption of the battery. The main focus here is to develop a computationally efficient approach, mimicking the optimal preheating behavior without a noticeable increase in the total energy consumption. The proposed algorithm is simple enough to be implemented in a low-level electronic control unit of the vehicle, by eliminating the need for solving the full NLP in the cost of only 1Wh increase in the total energy consumption.

Abstract Flow-accelerated corrosion (FAC) is a degradation mechanism that affects carbon steel piping in power plants. The failures and degradation due to FAC have necessitated numerous replacements in many power plants. Several computer codes around the world were developed as part of a systematic program or process to control FAC in power plant utilities. The typical plant model requires the input of the flow parameters, piping configuration and the plant water chemistry. The results on FAC rate are considered the key to proper selection of components for inspection. The lack of information on the effect of the upstream components located in the proximity limited the accuracy of the FAC prediction tools and hence will affect the accuracy in identifying potential inspection locations. In the present study 211 inspection data for 90° carbon steel elbows from several nuclear power plants were used to determine the effect of the proximity between two components on the FAC wear rate. The effect of the velocity as well as the distance between the elbows and the upstream components is discussed in the present analysis. Based on the analyzed trends obtained from the inspection data, significant increase in the wear rate of approximately 70% on average is identified to be due to the proximity.

The coupling of water-splitting catalysts to silicon photovoltaics enables direct solar-to-fuel conversion. Critical to the performance of such devices is the use of interfaces to protect silicon from the oxygen-evolving reaction (OER) and at the same time to provide Ohmic contact between the buried silicon junction and the immobilised OER catalyst. Presented herein are guidelines for constructing the Si|catalyst interface, which is a crucial building block for efficient direct solar-to-fuel conversion devices. We show that fluorinated-tin-oxide is an especially attractive interface for buried-junction devices.