• Energy Research
• 2016-2025close
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In order to achieve paramount economy, hybrid renewable energy sources are gaining importance, as renewable sources are costless. Over the past few years wind energy incorporation drew more consideration in the electricity market, as wind power took an affirmative role in energy saving as well as sinking emission pollutants. Recently developed Grey wolf optimizer (GWO) algorithm has conspicuous behavior for verdicting global optima, without getting ensnared in premature convergence. In the proposed research the exploitation phase of the grey wolf optimizer has been further improved using random exploratory search algorithm, which uses perturbed solutions vectors along with previously generated solution vectors. The paper presents a hybrid version of Grey Wolf Optimizer algorithm combined with random exploratory search algorithm (hGWO-RES) for the solution of combinatorial scheduling and dispatch problem of electric power systems. To validate the feasibility of the algorithm, the proposed algorithm has been tested on 23 benchmark problems. To verify the feasibility and efficacy of operation of proposed algorithm on generation scheduling and dispatch of electric power systems, small and medium scale power systems consisting of 7-, 10-, 19-, 20- and 40-generating units systems taken into consideration. Commitment and scheduling pattern has been evaluated with and without wind integration and it has been experimentally founded that proposed hybrid algorithm provides superior solution as compared to other recently reported meta-heuristics search algorithms.

Abstract Energy storage systems (ESS) are widely used in active distribution networks (ADN) to smoothen the drastic fluctuation of renewable energy sources (RES). In order to enhance the scalability and flexibility of ESS, a virtual energy storage system (VESS), which is composed of battery energy storage system (BESS), RES as well as flexible loads (FL), is developed in this paper to realize the functionalities of ESS in more cost-effective way in ADN. Aiming at achieving voltage regulation, dynamic pricing strategies based on system voltage condition are designed for VESS. A distributed real-time power management model containing dynamic pricing strategies is proposed to accomplish the voltage regulation and economic power sharing in VESS. Moreover, a set of distributed algorithms, over time-varying unbalanced directed networks, are designed for dynamic pricing strategies and optimal power management model. Furthermore, the convergence property, optimality and system voltage stability are explained by detailed mathematical analysis. Three various case studies which were ran on a real time digital simulator (OPAL-RT OP5600) were designed to validate the effectiveness of the strategy. Finally, simulation results show that the economic power dispatch and voltage regulation are achieved among VESS simultaneously, even in the presence of time-varying directed and unbalanced communication networks.

Abstract This research attempted to analyze a triple-tube heat exchanger (TTHE) fitted with innovative crimped-spiral ribs to enhance thermal efficiency. The crimped-spiral rib was placed on the top of the internal tube, and the water–alumina nanofluid was employed as the hot fluid within the ribbed side, whereas the two other fluids were pure water. The numerical solutions were performed through the two-phase mixture method, while the turbulent flow was modeled via the Reynolds Stress Model (RSM). The overall heat transfer coefficient (U), heat transfer rate, effectiveness, and performance index enhanced remarkably by using the nanofluid. The greatest increment in the U and effectiveness reached around 44.91 and 41 %, respectively, by the increment of the volume fraction by 0.02. The crimp intensity had an appreciable contribution to the thermal performance. The main mechanism was stronger swirl flow generated by the crimped-spiral rib that yielded boundary layer destruction. The heat transfer capability was increased via the rib pitch decrement and rib height increment. The performance index showed great values even at low volume fractions, which manifested the great merit of the implemented refinements. The thermal attributes were investigated at the first of the result section and then, the hydraulic characteristics were researched.

In electric power generation and distribution systems, three structures are capable of impacting energy quality: generation, distribution and loads. Currently, the diversity of the latter ranges from purely resistive loads such as heating systems to extremely nonlinear loads such as switched electronic power supplies. This has dramatically affected the quality of electric energy. The operation of these loads contributes to the reduction of the power factor of the installation, the injection of harmonic currents in the electrical network and the imbalance of currents and voltages between the phases in the case of three-phase systems. The implementation of a method capable of recognizing electrical loads and identifying them through algorithms can be used to manage the electric energy consumption, contributing a lot to the improvement of the quality of electric energy. In order to deal with uncertainty in the identification of these loads, probability distributions will be applied, which are able to handle uncertainty through a probabilistic modeling using Bayesian Networks.

Abstract This study investigates the macroeconomic effects of adverse oil price shocks on a small oil-exporting economy — the Azerbaijan economy. We estimate a recursive (near) VAR model by using monthly macroeconomic data from 2006 to 2018. The results indicate the Azerbaijan economy is adversely influenced by an oil price decline. Specifically, we find that a negative oil price shock deteriorates trade balance, causes a currency depreciation, increases inflation and falls economic activity. Furthermore, our findings imply that the oil price-led devaluation shapes the inflationary and recessionary consequences of this shock.

Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

Torrefaction is considered as a method for producing biofuels with improved characteristics compared to those of the “raw” biomass (higher calorific value, moisture resistance, better grindability). The torrefaction process is an endothermic process that is usually carried out in a gaseous atmosphere in the absence of oxygen. To reduce the required heat input, it is proposed to employ the oxidative torrefaction and conduct the process in a fluidized bed agitated with flue gases containing less than 6% oxygen. Preliminary studies of the oxidative torrefaction of sunflower husks, including thermogravimetric analysis of the treated material, have shown that the heat treatment time for the biomass should be at least 5 min. A fluidized bed is a reactor with ideal mixing of the treated material where uniform treatment of raw material particles cannot generally be attained. To overcome this disadvantage of the fluidization technique and achieve the required residence time for biomass in a fluidized bed during a continuous torrefaction process, it was proposed to equip a torrefaction reactor with a series of vertical baffles spaced at 50 mm. These baffles induce a loop-like flow of the processed biomass from the inlet to the outlet of the reactor. To investigate the residence time for husk particles in the reactor, a tracer, which was colored to husk particles' color with a water-soluble dye which did not change the weight and size of the particles, was injected into the bed of uncolored particles. Tracer samples were taken every 30 s at the outlet of the reactor and were analyzed using a special procedure to determine the fraction of colored particles in each sample. This enabled us to gauge the time during which the colored particles injected into the fluidized bed reached the point of their discharge from the bed. Studies performed in a “cold” model of the reactor showed that a series of vertical baffles in the bed can provide the required residence time for biomass in a reactor including commercial reactors. Plates can provide the necessary biomass residence time in the reactor.

Abstract Previous studies have shown that titanium-based glazes containing silicon and calcium tend to crystallize into titanite. In this work, ZnO was found to be an effective additive to produce rutile but not titanite. Images of the micromorphology showed that the glaze doped with 8 wt% ZnO was UV–VIS–NIR of acicular rutile and granular silica. The refractive index of crystalline rutile is higher than that of crystalline titanite, which leads to higher reflectance in the near-infrared range. However, excessive rutile counteracted this improvement in the UV–VIS–NIR spectrum reflectance of solar energy because it decreased the visible spectrum reflectance. As a result, the best ratio of added ZnO was confirmed to be 2 wt%.