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In this study, pyrolysis of residual biomass from the agro-alimentary industry of Argentina was investigated. The studied biomasses were rice husk, peanut shell and wheat straw. The effect of pyrolysis temperature over solid (bio-char), liquid (bio-oil) and gas (bio-gas) fractions weight yields were evaluated for each biomass, in the range of 350-650 °C. The maximum yield of bio-oil was obtained at 550 °C for rice husk (45 wt%) and wheat straw (58 wt%), and at 500 °C for peanut shells (51 wt%). At those temperatures, the data recorded the smallest spread around the mean. Different characterization techniques of raw biomass were reported, namely, thermal behavior; proximate and ultimate analysis; content of Ca, Al, K, Si and Fe; and hemicellulose, cellulose and lignin composition. Bio-oils characterization included water content and chemical compounds identification. Furthermore, bio-char HHV and BET surface area were measured. Rice husk bio-oil showed 21% selectivity towards furans of which 75% corresponded to furfural and 5-HMF. Peanut shell bio-char presented the highest Higher Heating Value (7250 kcal/kg) and BET surface area (215 m2/g). In addition, co-pyrolysis reactions and the synergistic effects over obtained products completed this study. Co-pyrolysis bio-oils yields varied between 41 and 46 wt%, for all the mixtures. Bio-oil water content decreased up to 15% for rice husk mixed with peanut shell or wheat straw. Moreover, 5-HMF was detected in all bio-oils, and furfural selectivity was higher than 5% in the three mixtures investigated.

This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

Abstract Thermal performance of three naturally ventilated public buildings in which the wind tower is an important architectural freature is studied. One of the three builidings as well as it's wind tower is instrumented for temperature, relative humidity and airflow velocity measurements, and the other two are instrumented for temperature measurement. The results have led to a discussion concerning the degree of wind tower effectiveness in achieving thermal comfort.

This paper presents a multi-objective optimization model for a long-term generation mix in Indonesia. The objective of this work is to assess the economic, environment, and adequacy of local energy sources. The model includes two competing objective functions to seek the lowest cost of generation and the lowest CO2 emissions while considering technology diffusion. The scenarios include the use of fossil reserves with or without the constraints of the reserve to production ratio and exports. The results indicate that Indonesia should develop all renewable energy and requires imported coal and natural gas. If all fossil resources were upgraded to reserves, electricity demand in 2050 could be met by domestic energy sources. The maximum share of renewable energy that can be achieved in 2050 is 33% with and 80% without technology diffusion. The least cost optimization produces lower generation costs than the least CO2 emissions, as well as the combined scenario. Total CO2 emissions in 2050 are five to six times as large as current emissions. The least CO2 emissions scenario can reduce almost half of the CO2 emissions of the least cost scenario by 2050. The proposed multi-objective optimization model leads some optimal solutions for a more sustainable electricity system.

Impact loads in large iron and steel enterprise bring the power system reactive power impact, which makes the fluctuation of the system voltage, power factor and other parameters are out of the limitation of the national standard. Substation bus reactive load forecasting in large iron and steel enterprise can be introduced to determine reactive power optimization strategy and the switching of capacitors. In this paper, a combination forecasting model of quadratic self-adaptive exponential smoothing (QSES) model and converse exponential (CE) model has been proposed for substation bus reactive load forecasting. The numerical results in Jinan iron and steel Group show the application of this model is encouraging. Introduction

An all-round supramolecular zwitterionic hydrogel electrolyte with the advantages ofin siturepair, H2O-poor interface, and boosting the desolvation of hydrated Zn2+is proposed to enable the fabrication of environment-adaptive dendrite-free zinc ion capacitors.

Forest soil acidification caused by acid deposition is a serious threat to the forest ecosystem. To investigate the liming effects of biomass ash (BA) and alkaline slag (AS) on the acidic topsoil and subsoil, a three-year field experiment under artificial Masson pine was conducted at Langxi, Anhui province in Southern China. The surface application of BA and AS significantly increased the soil pH, and thus decreased exchangeable acidity and active Al in the topsoil. Soil exchangeable Ca2+ and Mg2+ in topsoil were significantly increased by the surface application of BA and AS, while an increase in soil exchangeable K+ was only observed in BA treatments. The soil acidity and active Al in subsoil were decreased by the surface application of AS. Compared with the control, soluble monomeric and exchangeable Al in the subsoil was decreased by 38.0% and 29.4% after 3 years of AS surface application. There was a minimal effect on soluble monomeric and exchangeable Al after the application of BA. The soil exchangeable Ca2+ and Mg2+ in the subsoil increased respectively by 54% and 141% after surface application of 10 t ha-1 AS. The decrease of soil active Al and increase of base cations in subsoil were mainly attributed to the high migration capacity of base cations in AS. In conclusion, the effect of surface application of AS was superior to BA in ameliorating soil acidity and alleviating soil Al toxicity in the subsoil of this Ultisol.

Successive international commitments relating to energy and climatic change (embodied in the Kyoto Protocol) and the need to rationalise the sources of generated energy, have meant that renewable energies have started to gain a great deal of importance within the worldwide energy network. In the case of Wind Energy, and in terms of production, Spain is the second most important country at European level and the third most important country at global level. Spain holds these positions as a result of the establishment of a stable regulatory framework, better understanding of the resource and improved technology that have afforded considerable cost reduction in terms of initial investment, maintenance and exploitation. This article focuses on these circumstances in view of their relevance at international level, which is due to the highly feasible possibility of exporting Spain's experiences to other countries with guarantees of success.

Flue gas desulfurization (FGD) and selective catalytic reduction (SCR) technologies have been widely used to control the emissions of sulphur dioxide (SO2) and nitrogen oxides (NOX) from coal-fired power plants (CFPPs). Field measurements of emission characteristics of four conventional CFPPs indicated a significant increase in particulate ionic species, increasing PM2.5 emission with FGD and SCR installations. The mean concentrations of PM2.5 from all CFPPs tested were 3.79 ± 1.37 mg/m3 and 5.02 ± 1.73 mg/m3 at the FGD inlet and outlet, respectively, and the corresponding contributions of ionic species were 19.1 ± 7.7% and 38.2 ± 7.8%, respectively. The FGD was found to enhance the conversion of NH3 slip from the SCR to NH4+ in the PM2.5, together with the conversion of SO2 to SO42-, and increased the primary NH4+ and SO42- aerosol emissions by approximately 18.9 and 4.2 times, respectively. This adverse effect should be considered when updating the emission inventory of CFPPs and should draw the attention of policy-makers for future air pollution control.