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Abstract Price volatility analysis has been reported in the literature for most competitive electricity markets around the world. However, no studies have been published yet that quantify price volatility in the Ontario electricity market, which is the focus of the present paper. In this paper, a comparative volatility analysis is conducted for the Ontario market and its neighboring electricity markets. Volatility indices are developed based on historical volatility and price velocity concepts, previously applied to other electricity market prices, and employed in the present work. The analysis is carried out in two scenarios: in the first scenario, the volatility indices are determined for the entire price time series. In the second scenario, the price time series are broken up into 24 time series for each of the 24 h and volatility indices are calculated for each specific hour separately. The volatility indices are also applied to the locational marginal prices of several pricing points in the New England, New York, and PJM electricity markets. The outcomes reveal that price volatility is significantly higher in Ontario than the three studied neighboring electricity markets. Furthermore, comparison of the results of this study with similar findings previously published for 15 other electricity markets demonstrates that the Ontario electricity market is one of the most volatile electricity markets world-wide. This high volatility is argued to be associated with the fact that Ontario is a single-settlement, real-time market.

Anaerobic digestion of high solids chicken manure was conducted in a batch screening assay. Different mixtures of the fresh manure and anaerobically digested sludge or pit manure, resulting in different total solids levels, were incubated at 35°C. The efficiency of organic matter conversion to methane was found to decrease with increasing organic loads to the digesters. The highest solids at which the digestion was still feasible was around 10% total solids. Methanogenesis took place at free ammonia (NH3) concentrations of up to 250 mg/l. The efficiency of organic nitrogen conversion to ammonia (NH3+NH+4) ranging from 62·6% to as high as 80·3% was achieved in most digestions.

Abstract Among different techniques for the storage and release of energy, phase change materials hold great promise to satisfy the growing needs of smart thermal energy management and portable thermal energy sectors. However, low thermal conductivity and shape-instability through the phase transition process are two main drawbacks of phase change materials towards industrialization. In this review paper, recent progresses in employing graphene-based nanostructures as a versatile solution for the aforementioned shortcomings are presented in detail. Graphene-based nanostructures, as either graphene nanosheets or graphene-based porous nanostructures, can improve the thermal conductivity of phase change materials and shape stability of these energy storage systems significantly. Moreover, recent studies presented here suggest that graphene-based phase change composites can be considered as promising energy harvesting systems for solar-to-thermal and solar-to-electrical energy conversion and storage applications.

Abstract Lithium-ion batteries (LIBs) have driven the industry of rechargeable batteries in recent years due to their advantages such as high energy and power density and relatively long lifespan. Nevertheless, the dispose of spent LIBs has harmful impacts on the environment which needs to be addressed by recycling LIBs. However, none of the currently developed recycling processes is economical. The physical recycling process of LIBs may be economical if the cathode active materials can be separated, regenerated, and reused to make new LIBs. However, the first barrier for regeneration and reusing is the separation of different types of spent cathode active materials in the filter cake that are mixed with each other and come in the form of very fine powders with various sizes (< 30 μm) from the physical recycling process. The aim of this study is to separate the mixture of cathode active materials by adopting Stokes’ law. The focus will be only on mechanical separation with no thermal or chemical separation methods. For the validation, an experiment was designed and successfully performed where different types of spent cathode materials (e.g., LiCoO2, LiFePO4, and LiMn2O4) were separated from the spent anode materials (e.g., graphite) with high efficiency and reasonable time.

Abstract In this study, the influence of compressor speed, ejector motive nozzle needle position and evaporator inlet metering valve opening on the oil circulation rates (OCRs) of an R744 transcritical standard ejector cycle was experimentally investigated. Significantly higher OCR (∼10%) was observed at the evaporator inlet of the ejector cycle than that at the high pressure side (∼1%) measured in the same cycle under the same conditions. It has been observed that evaporator OCR was increased with increasing compressor speed. When the motive nozzle needle moved towards the nozzle throat, both compressor discharge flow rate and evaporator OCR were observed to be significantly lowered. As the evaporator inlet metering valve opening was adjusted, the compressor mass flow rate did not vary significantly while the evaporator mass flow rate decreased with decreasing metering valve opening. The evaporator OCR decreased from 6.5% to 2.2% as the metering valve opening varied from 86% to 27%. High evaporator OCR results in large evaporator pressure drop and low heat transfer coefficient. In addition to the standard ejector cycle, several alternative ejector cycles were theoretically analyzed to see if there is similar problem of high OCR in the evaporator. In ejector liquid recirculation cycle and multi-stage multi-ejector supermarket refrigeration cycle, similar high OCR problem in the evaporator may exist, while in two evaporator ejector cycle, evaporator OCR is equal to compressor OCR at steady state.

Abstract This paper presents the application of the process of KDD (knowledge discovery in databases) for the forecasting of the electrical power demand of a supply fan of an AHU (air handling unit). The case study uses trend data from the BAS (Building Automation System), which is recorded every 15 min in an office building. Data mining techniques are used as a preprocessing step in the development of the forecasting model. A clustering analysis detects atypical operations and then partitions the whole dataset into three subsets of typical daily profiles of the supply fan modulation. A hybrid model, combining a closed-loop nonlinear ANN (autoregressive neural network) model and a physical model, forecasts the electric power demand over a horizon of up to 6 h. The optimum architecture of ANN, found by using a Simple Genetic Algorithm, is composed of 13 input neurons, 1 hidden neuron and 23-day training set size, for the cluster corresponding to working days except Mondays. The results show good agreement between the forecasts and measurements of fan modulation, and electric demand, respectively. The fan modulation was forecasted over the testing period with RMSE (Root Mean Squared Error) of 5.5% and CV(RMSE) of 17.6%. The fan electric demand was forecasted with a RMSE of 1.4 kW, CV(RMSE) of 30% over a 6-h time horizon. The sensitivity analysis indicated that the reduction of training data set size from 23 days to 4 or 8 days does not have a negative impact of the value of RMSE.

Abstract This paper deals with the problem of an infinite cylindrical heat source embedded into a saturated porous medium and subject to a cross-axial Darcian flow. Only forced convection is considered. We derived the transient dimensionless solution through a combined analytical – numerical method consisting of four steps: (a) a preliminary dimensional analysis of the constitutive equations of the problem in order to find the dimensionless groups governing the solution; (b) the identification of the validity range of the model as a function of the just-mentioned dimensionless groups; (c) the numerical resolution of the problem; (d) the synthesis of the numerical results in a general dimensionless form. Specifically, we provide several dimensionless maps of the 2D thermal field evolution for six different orders of magnitude of the Peclet number ( 10 - 3 – 10 2 ) . The evolution of the temperature of the heat source is fully illustrated and discussed through plain dimensionless criteria. Then, we discuss the time, space and fluid velocity scales in which the solution is practically equivalent to the ones given by a linear heat source and a purely conductive model. We conclude that the present model has to be employed to evaluate the temperature in proximity of the heat source when the reference Peclet number is greater than 0.5. On the contrary, the linear model can be successfully used for radial distances 5–10 times greater that the heat source radius, depending on the reference Peclet number.

Abstract The background to the first standards for digital recorders for high-voltage impulse measurements is reviewed briefly. The emphasis in the first issues is given and the import of the decisions made in these early documents presented. The changes in the latest revision of Institute of Electrical and Electronics Engineers (IEEE) Std. 1122-1998 are reviewed briefly and contrasted with the approach in the latest Committee Draft for Voting on the revision of International Electrotechnical Commission (IEC) Document 1083-1. The importance of the changes in these documents is discussed. New work in the field is summarized and recent developments in digital recorders are discussed. The present status of digital measurements is summarized and proposals for future improvements to the standards are put forward.

In the present work an equilibrium model (gas-solid), based on the minimization of the Gibbs energy, has been used in order to estimate the theoretical yield and the equilibrium composition of the reaction products (syngas and char) of biomass thermochemical conversion processes (pyrolysis and gasification). The data obtained from this model have also been used to calculate the heating value of the fuel gas, in order to evaluate the overall energy efficiency of the thermal conversion stage. The proposed model has been applied both to partial oxidation and steam gasification processes with varying air to biomass (ER) and steam to carbon (SC) ratio values and using different feedstocks; the obtained results have been compared with experimental data and with other model predictions obtaining a satisfactory agreement.