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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.

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

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.

The performance capabilities of an axially laminated anisotropic rotor (ALA) in a high-speed synchronous reluctance motor (SynRM) were studied. A 12 kW ALASynRM was designed as an alternative to a high-speed induction motor (IM) with a solid rotor. The electromagnetic design was implemented taking into account possible issues related to the new manufacturing methods, which require thicker rotor layers than in a typical ALA. The ALASynRM shows a higher efficiency than the corresponding IM with a smooth or slitted solid rotor equipped with copper end rings. To verify the design method, a prototype IM with a smooth solid rotor was built and tested. In the analysis, it was found that, similar to IMs, in an ALASynRM a considerable part of losses takes place in the rotor despite the absence of slip-related losses in the SynRM. The distribution of eddy current losses in the ALA rotor is significantly uneven. The torque ripple in the ALASynRM is considerably larger than the corresponding ripple in IMs.

We present the architecture and design of the IANOS scheduling framework. The goal of the new Grid scheduling system is to provide a general job submission framework allowing optimal positioning and scheduling of HPCN applications. The scheduling algorithms used to calculate best-suited resources are based on an objective cost function that exploits information on the parameterization of applications and resources. This standard-based, interoperable scheduling framework comprises four general web services and three modules. The middleware is complemented with one client and one admin console. The implementation is based on proposed Grid and Web services standards (WSRF, WS-Agreement, JSDL, and GLUE). It is agnostic to a specific Grid middleware. The beta version of IANOS has been tested and integrated with UNICORE. The validation of IANOS is in progress by running different types of HPCN applications on a large-scale Grid testbed.

With the aim to fully exploit the by-products obtained after the industrial extraction of starch from sweet potatoes, a cascading approach was developed to extract high-value molecules, such as proteins and pectins, and to valorize the solid fraction, rich in starch and fibrous components. This fraction was used to prepare new biocomposites designed for food packaging applications. The sweet potato residue was added to poly(3-hydroxybutyrate-co-3-hydroxyvalerate) in various amounts up to 40 wt % by melt mixing, without any previous treatment. The composites are semicrystalline materials, characterized by thermal stability up to 260 °C. For the composites containing up to 10 wt % of residue, the tensile strength remains over 30 MPa and the strain stays over 3.2%. A homogeneous dispersion of the sweet potato waste into the bio-polymeric matrix was achieved but, despite the presence of hydrogen bond interactions between the components, a poor interfacial adhesion was detected. Considering the significant percentage of sweet potato waste used, the biocomposites obtained show a low economic and environmental impact, resulting in an interesting bio-alternative to the materials commonly used in the packaging industry. Thus, according to the principles of a circular economy, the preparation of the biocomposites closes the loop of the complete valorization of sweet potato products and by-products.

Abstract A CFD modelling study has been undertaken to examine the co-firing of pulverised coal and biomass with particular regard to the burnout of the larger diameter biomass particles. Computations were based on a research combustion facility that replicates an industrial coal-fired power station. Three percent, by mass, of pinewood was blended with a bituminous UK coal, and the effects of the wood particle size and shape on the burnout of the combined wood and coal char were investigated. The effect of varying the devolatilisation and char combustion rate constants for the biomass component in the blend was also investigated. It was concluded that the combustion of small (200 μm) wood particles was rapid but the rate of combustion of larger particles was dependent on their composition, size, and shape.

The Severn Estuary has the world's second largest tide range and a barrage across the estuary, located just seawards of Cardiff in Wales and Weston in the South West England, has been proposed for over half a century, with the objective of extracting large amounts of tidal energy. A Severn Barrage, as previously proposed by the Severn Tidal Power Group (STPG), would be the largest renewable energy project for tidal power generation in the world, if built as proposed, and would generate approximately 5% of the UK's electricity needs. However, concerns have been raised over the environmental impacts of such a barrage, including potential increase in flood risk, loss of intertidal habitats etc. In addressing the challenges of maximizing the energy output and minimizing the environmental impacts of such a barrage, this research study has focused on using a Continental Shelf model, based on the modified Environmental Fluid Dynamics Code (EFDC) with a barrage operation module (EFDC_B), to investigate both the far and near field hydrodynamic impacts of a barrage for different operating scenarios. Three scenarios have been considered to simulate the Severn Barrage, operating via two-way generation and using different combinations of turbines and sluices. The first scenario consisted of 216 turbines and 166 sluices installed along the barrage; the second consisted of 382 turbines with no sluices; and the third consisted of 764 turbines and no sluices. The specification of the sluice gates and turbines are the same for all scenarios. The model results indicate that the third scenario has the best mitigating effects for the far-field and near-field flood risks caused by a barrage and produces the most similar results of minimum water depth and maximum velocity distributions to those obtained from simulating the natural conditions of the estuary, i.e. the current conditions. The results also show that the flow patterns around the barrage are closest to those for the existing natural conditions with minimal slight changes in the estuary. Thus, the results clearly indicate that the environmental impacts of a Severn Barrage can be minimized if the barrage is operated for two-way generation and under the third scenario. Although it appears that the energy output for the third scenario is less than that obtained for the other two scenarios, if very low head (VLH) turbines are used, then the third scenario could generate more energy as more turbines could be cited along the barrage structure. Therefore, the study shows that a Severn Barrage, operating in two-way generation and with 764 turbines (ideally VLH turbines), would be the best option to meet the needs of maximizing the energy output, but having a minimal impact on environmental changes in the estuary and far-field.