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The increasing global demand for the sustainable development of electricity sectors increased the contribution of renewable energy sources (RESs). RESs give the flexibility to install generation units at demand areas and reduce transmission and distribution losses. Selection of appropriate RES is more strategic and decisive area. This is a complex multi-criteria decision making (MCDM) problem of having uncertain and conflicting factors. In this work, we used the recently developed MCDM technique VIKOR method to choose best appropriate RES alternative for installation at Banaras Hindu University (BHU) campus, India. The advantage of VIKOR method is to have a solution closest to the ideal solution having an acceptable compromise of conflicting and non-commensurable criteria. For assigning weights to the different criteria, we used analytical hierarchy process (AHP). The importance of different criteria has been assigned by decision-makers based on their preferences. The result shows that the wind turbine option is the best choice for the case of BHU campus.

Abstract Wind, Solar photovoltaic and solar thermal power systems are emerging renewable energy technologies and can be developed as viable options for electricity generation in future. In this paper, autonomous hybrid generation systems consisting of wind turbine generators (WTGs), solar thermal power system (STPS), solar photovoltaic (PV), diesel engine generators (DEGs), fuel cells (FCs), battery energy storage system (BESS), flywheel (FW), ultra capacitors (UCs) and aqua electrolyzer (AE) have been considered for simulation studies. The power system frequency deviates for sudden changes in load or generation or the both. The comparative performance of the controllers installed to alleviate this frequency deviation for different hybrid systems, is carried out using time domain simulation. In practice, controllers (PI or PID) are tuned manually which is difficult and time consuming. The computational intelligence has opened paths to a new generation of advanced process control. Here, GA is used for optimization of controllers’ gains of the proposed hybrid systems. The simulation results demonstrate the effectiveness of the GA based controllers in terms of reduced settling time, overshoot and oscillations. The results are compared with conventional controllers.

Risk preference is an important factor in electricity market strategy analysis and decision-making. The existing methods of risk preference analysis need to design and execute questionnaires or experiments on the subjects, and hence are costly and time-consuming for bidding in electricity markets. This article proposes a new method of data-driven risk preference analysis for power generation plants based on historical data and inverse reinforcement learning. Historical data are transformed to the transition function model according to the specific market mechanism. An adjusted inverse reinforcement learning model is thereafter proposed along with the optimization objective and technical constraints. The proposed method is tested in a simulated electricity market environment using the Australian Energy Market Operator (AEMO) day-ahead bidding data. Simulation results show that 1) thermal power plants prefer to adjust risk preferences within the day; 2) apart from the thermal power plants, the rest types of power plants are risk-neutral; 3) the daily risk preference trend of the thermal power plants varies in different seasons and is closely related to the load level.

Abstract—Environmental concerns due to emissions from nuclear and fossil fuel based power plants have triggered widespread utilization of renewable energy-based small- and large-scale distributed generation technologies. These technologies have been transforming the energy market towards a deregulated and dispersed entity. To cope with these transformations, and ensure appropriate grid monitoring and control, the conventional power grids across the globe have been enduring a paradigm shift towards a smart grid that is empowered with cutting edge technologies. The operational stability of these emerging smart power grids necessitates sophisticated real-time monitoring and control technologies. This article analyzes various stability concerns in smart power grids pertaining to distributed generations and proposes novel methodologies for ensuring operational stability. The proposed methodologies entail real-time stability monitoring and stability control with the use of wide-area synchrophasor measurements a...

During the Engineering Validation and Engineering Design Activities (EVEDA) phase (2007-2014) of the International Fusion Materials Irradiation Facility (IFMIF), an advanced engineering design of the High Flux Test Module (HFTM) has been developed with the objective to facilitate the controlled irradiation of steel samples in the high flux area directly behind the IFMIF neutron source. The development process addressed included manufacturing techniques, CAD, neutronic, thermal-hydraulic and mechanical anal- yses complemented by a series of validation activities. Validation included manufacturing of 1:1 parts and mockups, test of prototypes in the FLEX and HELOKA-LP helium loops of KIT for verification of the thermal and mechanical properties, and irradiation of specimen filled capsule prototypes in the BR2 test reactor. The prototyping activities were backed by several R&D studies addressing focused issues like han- dling of liquid NaK (as filling medium) and insertion of Small Specimen Test Technique (SSTT) specimens into the irradiation capsules. This paper provides an up-todate design description of the HFTM irradiation device, and reports on the achieved performance criteria related to the requirements. Results of the vali- dation activities are accounted for and the most important issues for further development are identified.

Integrating renewable energy into public space is becoming more common as a climate change solution. However, this approach is often guided by the environmental pillar of sustainability, with less focus on the economic and social pillars. The purpose of this paper is to examine this issue in the speculative renewable energy propositions for Freshkills Park in New York City submitted for the 2012 Land Art Generator Initiative (LAGI) competition. This paper first proposes an optimal electricity distribution (OED) framework in and around public spaces based on relevant ecology and energy theory (Odum’s fourth and fifth law of thermodynamics). This framework addresses social engagement related to public interaction, and economic engagement related to the estimated quantity of electricity produced, in conjunction with environmental engagement related to the embodied energy required to construct the renewable energy infrastructure. Next, the study uses the OED framework to analyse the top twenty-five projects submitted for the LAGI 2012 competition. The findings reveal an electricity distribution imbalance and suggest a lack of in-depth understanding about sustainable electricity distribution within public space design. The paper concludes with suggestions for future research.

Controlling the morphological structure of titanium dioxide (TiO2) is crucial for obtaining superior power conversion efficiency for dye‐sensitized solar cells. Although the sol–gel‐based process has been developed for this purpose, there has been limited success in resisting the aggregation of nanostructured TiO2, which could act as an obstacle for mass production. Herein, we report a simple approach to improve the efficiency of dye‐sensitized solar cells (DSSC) by controlling the degree of aggregation and particle surface charge through zeta potential analysis. We found that different aqueous colloidal conditions, i.e., potential of hydrogen (pH), water/titanium alkoxide (titanium isopropoxide) ratio, and surface charge, obviously led to different particle sizes in the range of 10–500 nm. We have also shown that particles prepared under acidic conditions are more effective for DSSC application regarding the modification of surface charges to improve dye loading and electron injection rate properties. Power conversion efficiency of 6.54%, open‐circuit voltage of 0.73 V, short‐circuit current density of 15.32 mA/cm2, and fill factor of 0.73 were obtained using anatase TiO2 optimized to 10–20 nm in size, as well as by the use of a compact TiO2 blocking layer.

In the thermodynamic analysis of pyrometallurgical processes using coke as a reductant, the data for CO and CO[sub 2] from thermochemical tables, relative to graphite as the standard state for carbon, are used. Since coke is an amorphous form of carbon, its Gibbs energy is expected to be higher than that of graphite. However, there has been no direct measurement of the stability of coke relative to graphite reported in the literature. For an accurate description of the thermodynamics of reactions involving coke, it is necessary to obtain quantitative values for the Gibbs energy difference between coke and graphite as a function of temperature. This communication reports an experimental determination of the activity of carbon in coke relative to graphite using a solid-state galvanic cell incorporating single-crystal CaF[sub 2] as the solid electrolyte. The results obtained in this study indicate a significantly higher solubility of coke compared to graphite in iron. However, metals are known to catalyze graphitization and the surface of coke in contact with the metal is likely to have a graphitelike structure. Thus, the theoretical difference in solubility may not be measurable in practice.