• Energy Research
• 7. Clean energy close
• 11. Sustainability close
• 3. Good health close
• 1. No poverty close
• US close
• AU close
• CA close

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

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.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.

Abstract The combination of biomass gasification with fuel cells, especially high temperature Solid Oxide Fuel Cells (SOFCs) promises sustainable and highly efficient (decentralized and modular) energy conversion systems. This review encompasses the components of biomass integrated gasification–SOFC technology including biomass characteristics, the thermochemical conversion in gasifiers and the factors affecting the gasification process, the cleaning technologies for raw producer gas and its conditioning and finally the integration of gasifier with SOFCs. The influence of impurities present in biomass producer gas such as particulates, tar, H 2 S, HCl and alkali compounds based on recent experimental studies and their tolerance limits towards SOFCs are presented. Even though analysis based on the probable tolerance limits of impurities towards SOFCs and a comprehensive overview of the cleaning technologies for producer gas impurities indicate that producer gas cleaning at various temperatures using current technologies to meet SOFC requirements is possible, more experimental studies are still needed to acquire the detailed information on the tolerance limits of impurities for SOFCs. The recent theoretical modeling and experimental studies of biomass integrated gasification–SOFC systems are also presented.

Aggregate and limestone mining in San Antonio’s Bexar and Comal counties in Texas, USA, has caused considerable health concerns as of late. Aggregate mining actions can result in localized air quality issues in any neighborhood. Furthermore, heavy truck traffic, hauling, and transportation of the mined material contribute to pollution. In this research, PM species were sampled at four locations north of the San Antonio city limits. The data were collected using a TSI Air Quality Sampler that sampled PM1, PM2.5, PM4, PM10, wind speed, wind direction, temperature, and relative humidity. Continuous data with 1 min averages were recorded during the study period from August to September 2019. The instrument was stationed at every location for a period of 7 days each. The four locations were a ranch, an open field, a residential compound, and an elementary school. PM1 and PM2.5 concentration levels were lower compared to PM10 concentrations at all four studied sites. Our results suggest that PM concentrations are primarily impacted by mining activities. PM species were highest at the residential compound due to its proximity to an active mining area, resulting in deleterious health effects for neighbors living in the vicinity of the sampled site.

Abstract This paper investigates the performance of a variable ratio gearbox (VRG) used in a small fixed-speed wind turbine with active blades. The major components of the VRG-enabled drivetrain are an automatic-manual gearbox and squirrel cage induction generator that connects directly to the grid. The simplicity of this system may be appealing for applications when cost and reliability are of concern. It is an alternative to variable speed systems, which necessitate a modified generator and power conditioning equipment. During partial load operation the VRG provides a discrete set of rotor speeds. This allows the controller to track the wind speed and to achieve a greater efficiency. This study suggests three VRG ratios are sufficient to improve performance when used with active blades. A case study is presented where the performance is simulated using three different wind data sets. The study suggests that the VRG can improve production between 7 and 8.5% in low wind areas. The design procedure also illustrates a technique for finding the lowest and highest gear ratios needed for VRG design. These ratios allow the system to achieve the lowest cut-in and rated speeds. The approach also has useful implications for the design of a continuously variable transmission.

With the integration of a high penetration of wind power into distribution system, the ability to cope with the voltage fluctuation issue arising from the intensified uncertainty should be improved. Energy storage system (ESS) with effective control strategies keeps a key role in smoothing the voltage fluctuation caused by the uncertainty of wind turbine generators (WTGs). Considering the constraints of state of charge (SOC), charge-discharge efficiency and continuous operation of ESS, this paper proposes a novel approach to determine the minimum capacity of ESS to satisfy the voltage fluctuation limit based on unbalanced three-phase interval power flow. An unbalanced forward-backward sweep interval power flow considering the constraints of ESS and the voltage fluctuation limit is proposed. The interval model of uncertain WTG output is established on basis of wind speed fluctuation curve. The interval model of the practical ESS output is obtained on basis of the present SOC, nominal capacity and comprehensive efficiency. The output voltages of power flow can directly demonstrate the voltage fluctuation rate due to their interval forms. Therefore, a feedback mechanism is established between the output voltage fluctuation rate and the input ESS practical power, which is used to determine the minimum capacity of ESS to satisfy the fluctuation limit. A modified IEEE 33-bus system with high penetration of WTGs is implemented to test the proposed method. Results demonstrate the validity and effectiveness of the proposed approach.