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This paper considers several alternative forms of an energy imbalance market (EIM) proposed in the nonmarket areas of the Western Interconnection. The proposed EIM includes two changes in operating practices that independently reduce variability and increase access to responsive resources: balancing authority cooperation and sub-hourly dispatch. As the penetration of variable generation increases on the power system, additional interest in coordination would likely occur. Several alternative approaches could be used, but consideration of any form of coordinated unit commitment is beyond the scope of this analysis. This report examines the benefits of several possible EIM implementations--both separately and in concert.

AbstractThis study presents the results obtained from simulated performance monitoring of seven different roof mounted PV systems in Abu Dhabi, the largest of UAE's emirate. Data were analyzed to evaluate the suitability of PV systems for installations in different types of buildings in the UAE. The PV systems consisted of amorphous silicon (a-Si) and polycrystalline silicon (p-Si) PV technologies. Different performance evaluation parameters are presented. The results give an indication of the system performance and provide a basis for economic and environmental assessment of the PV generated electricity.

Charcoal has a large share in the Brazilian market. The production is carried out by pyrolysis of biomass at different temperatures, between 300 and 500 °C. In this study, the corn cob pyrolysis was investigated using thermogravimetric analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR). Samples after pyrolysis were compared with raw biomass to evaluate changes in fuel characteristics. In DTG curves a reduction in the number of degradation peaks in the carbonized material was observed. The FTIR spectra allowed to identify the aromatic ring of the lignin in the charcoals structure, indicating the presence of this compound even in charcoals produced with a temperature of 500 °C. It can be concluded that the temperature of 400 °C was enough to completely degrade the hemicellulose and cellulose of the biomass, resulting the final product (charcoal) less reactive or thermally more resistant than the in natura corn cob.

Load forecasting is very important to manage the electrical power systems. Load forecasting can be analyzed in three different ways as short-term, medium-term and long-term. Long-term load forecasting (LTLF) is in need to plan and carry on future energy demand and investment such as size of energy plant. LTLF is affected by energy consumption, national incoming per year, rates of civilization, increasing population rates and moreover economical parameters. Some of the forecasting models use mathematical formulas and statistical models such as correlation and regression analysis. In this study, a new effective expert-supported dynamic programming algorithm (ESDP) has been improved. Additionally, adaptive neuro-fuzzy inference system (ANFIS) and mathematical modeling (MM) are used to forecast long term energy demand. ANFIS is one of the famous artificial intelligence and has widely used to solve forecasting problems in literature. In addition to numerical inputs, ANFIS has linguistics inputs. The results obtained from ESDP, ANFIS and MM are compared to show availability. In order to show error levels mean absolute percentage error (MAPE) and (MAE) are used. The obtained results show that the proposed algorithms are available.

The Box–Jenkins model is a polynomial model that uses transfer functions to express relationships between input, output, and noise for a given system. In this article, we present a Box–Jenkins linear model for a lithium-ion battery cell for use in electric vehicles. The model parameter identifications are based on automotive drive-cycle measurements. The proposed model prediction performance is evaluated using the goodness-of-fit criteria and the mean squared error between the Box–Jenkins model and the measured battery cell output. A simulation confirmed that the proposed Box–Jenkins model could adequately capture the battery cell dynamics for different automotive drive cycles and reasonably predict the actual battery cell output. The goodness-of-fit value shows that the Box–Jenkins model matches the battery cell data by 86.85% in the identification phase, and 90.83% in the validation phase for the LA-92 driving cycle. This work demonstrates the potential of using a simple and linear model to predict the battery cell behavior based on a complex identification dataset that represents the actual use of the battery cell in an electric vehicle.

Construction involves the use of significant quantities of raw materials and entails high-energy consumption. For the sake of choosing the most appropriate solution that considers environmental and sustainable concepts, tools such as the integrated value model for sustainable assessment (Modelo Integrado de Valor para una Evaluación Sostenible, MIVES) used in Spain, plays a key role in obtaining the best solution. MIVES is a multi-criteria decision-making method based on the value function concept and the seminars delivered by experts. Such tools, in order to show how they may work, require application to case studies. In this paper, two concrete slabs manufactured with differing reinforcements during the construction of the La Canda Tunnels are compared by means of MIVES. The two concrete slabs were reinforced with a conventional steel-mesh and with polyolefin fibres. This research was focussed on the main aspects affecting the construction. That is to say, the environmental, economic, and social factors were assessed by the method, being of special impact the issues related with maintenance of the structure. The results showed that from the point of view of sustainability, the use of polyolefin fibres provided a significant advantage, mainly due to the lower maintenance required.

The operation of gas generators brings relatively high thermo-mechanical loads on the gas generator structure. The objective of this article is to determine the operating conditions, in terms of mechanical loads at extremely high temperatures in very limited and narrow space, of a multifunctional bulkhead for application on specific kinds of gas generators with back-to-back rotor concept. The paper contains numerical analysis and experimental investigation for determining the loads and behavior of the structure. Numerical analysis indicates that there is significant influence of the Tesla turbine effect on flow parameters. Also, uneven pressure distribution and significant thermal loads are identified. With experimental investigation and subsequent exploitation tests, it was concluded that the presented methodology identifies the operating conditions, truthfully simulates the bulkhead stress state and deformations and that the presented design solution satisfied all demands. Regarding results obtained by these numerical simulations, the innovative design solution for the multifunctional bulkhead was proposed.