This article estimates the minimum energy consumption index in a single story protected farm which would suggest the condition of minimum energy consumption or loss condition. The analytic hierarchy... Show More

This article estimates the minimum energy consumption index in a single story protected farm which would suggest the condition of minimum energy consumption or loss condition. The analytic hierarchy process (AHP), weighted sum method (WSM) and weighted product method (WPM) are used for relative ranking of four energy consumption indicators viz., water pumping, light supplement, CO2 balancing and cooling-heating under three criteria viz., cropping area, daily crop water, and indoor environment. The minimum, maximum and average energy consumption index was predicted by the bacteria foraging optimization (BFO) algorithm and the group method of data handling (GMDH). The minimum energy consumption index (1.4174) predicted by the BFO algorithm gives higher prediction compared energy consumption index (1.114) predicted by the GMDH algorithm.

Water treatment plants (WTPs) are responsible for ensuring supply of healthy water to urban and rural consumers for drinking and other related purposes. But the arbitrary selection of a location for... Show More

Water treatment plants (WTPs) are responsible for ensuring supply of healthy water to urban and rural consumers for drinking and other related purposes. But the arbitrary selection of a location for installation or relocation of WTPs often fails the purpose of the plant. Presently studies in location selection for water treatment plant are rare. Multi-criteria decision making (MCDM) methods and bagged polynomial neural networks (PNN) were found to be exemplary and easy to use tools for prediction, simulation and optimization of decision-making objectives. The present study tries to apply the advantages of MCDM and bagged PNNs in the identification of an ideal location for a surface water treatment plant. The most significant parameter is found to be WQI which represents the overall quality of water suitable for domestic use. The PNN models were developed with all the selected eight alternatives as input and output. The algorithms like GMDH, SFS, SMS, and QC were used to estimate the weight of connections in between the input and hidden; and hidden and output layers separately for each segment. The application of these two soft computation tools provides an opportunity to the decision maker in the selection of optimal location with the help of an objective and cognitive method.

The operational performance of hydropower plants (HPPs) is largely affected as the output from the plant entirely depends on the rainfall and demand from consumers both of which are compromised due... Show More

The operational performance of hydropower plants (HPPs) is largely affected as the output from the plant entirely depends on the rainfall and demand from consumers both of which are compromised due to the vulnerability in climatic patterns and rapid change in urbanization rate. Although, not all the parameters are equally affected and the present study aims to find the degree of impact on the various correlated parameters on which production efficiency of HPPs varies. In this aspect, a neural network concept was used as decision making tool to identify the most significant parameters with respect to change in climate, urbanization along with machine failure because as a combined effect of the first two parameters, the probability of machine failure will also increase. The result from the study provides an opportunity to mitigate the impact that can be caused as a result of climate change impact and change in rate of urbanization. According to the result it was found that Efficiency of Generators is the most significant parameter of impact of climate change and urbanization on operational efficiency of hydropower plant. The result from the scenario analysis suggested that if the A2 scenario becomes true in 2061-70 there will be a maximum decrease in the OE and if land use scenario: PR story line is found to be adopted in the future world of 2020-30 the change in OE will be the greatest (an increase of 6.056%) compared to any other scenario developed for the impact of urbanization followed by land use change scenario of the 2031-40 decade, which will be equal to an increase of 5.247% compared to the baseline.

The overall commitment of hydropower plants (HPP) in providing the interest for power is 1106 TWh. The issue with hydropower lies with the way that its proficiency relies upon numerous indicators... Show More

The overall commitment of hydropower plants (HPP) in providing the interest for power is 1106 TWh. The issue with hydropower lies with the way that its proficiency relies upon numerous indicators which are elements of climatic, pressure driven and financial markets. Every one of these indicators again rely on pressure driven misfortune forced because of the time being used, change in energy requirements, locational interference and quality of the machine installed. As there are numerous indicators having diverse levels of impact on the execution productivity of HPP, a few indicators are exaggerated and some others stay under appraised which brings about incorrect basic leadership. The present study proposes another cross breed show in view of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) with the Analytic Hierarchy Process (AHP). Also in the present investigation rank of each indicator determine by Statistical Process Control (SPC). The needs are dictated by hybrid technique in particular SPC-DEMATEL-AHP. As per the outcomes, effectiveness of turbine is the most noteworthy for impacting general productivity of HPP.

This article addresses methods to adjust operating requirements in water treatment plants (WTPs) in order to increase the efficiency of water treatment plants based on the nature of the water... Show More

This article addresses methods to adjust operating requirements in water treatment plants (WTPs) in order to increase the efficiency of water treatment plants based on the nature of the water inflows into the systems. In the past, various studies have suggested that the quality of water inflow into the WTP has an impact on the efficiency and economic viability of operating treatment plants. Among all other quality parameters, the concentration of dissolved oxygen (DO) is one of the basic indicators about the overall quality of the water. Identification of a temporal pattern can help the engineers to adapt the WTP operations and can save the unnecessary wasting of plant resources. That is why the present article has proposed a new model that can predict the temporal patterns of various chemical parameters with the help of an analytic neuronal network. The model was applied to the case of a WTP that responds to a peri-urban catchment, leading to regular variations in the DO of water inflow. According to the performance metrics utilized the model was able to predict the temporal pattern at a lag of 1 hour.

This article proposes a novel strategy for developing a new structure for a lithium-ion battery pack fast charger which aims to achieve fast DC charging, based on the topology of a boost converter.... Show More

This article proposes a novel strategy for developing a new structure for a lithium-ion battery pack fast charger which aims to achieve fast DC charging, based on the topology of a boost converter. The proposed charger has been designed considering using fewer electronic components at lower cost. Varying initial charging percentage of the Li-ion cells has not been addressed in this article, an equal initial charging percentage of each Li-ion cell is assumed. Performance of the proposed structure of the charger has been tested using a simulation environment. This strategy has shown that this structure ensures scalability of this charger, while using the utility grid (220V, 50Hz) as a main power source for this charger has ensured practical usage flexibility. The results of this research are presented and discussed. These results have shown the outstanding performance and response of this charger.

In this article, the tuning of multiloop Fractional Order PID (FOPID) controller is designed for Two Input Two Output (TITO) processes using an evolutionary algorithm such as the Genetic algorithm... Show More

In this article, the tuning of multiloop Fractional Order PID (FOPID) controller is designed for Two Input Two Output (TITO) processes using an evolutionary algorithm such as the Genetic algorithm (GA), the Cuckoo Search algorithm (CS) and the Bat Algorithm (BA). The control parameters of FOPID are obtained using GA, CS, and BA for minimizing the integral error criteria. The main objective of this article is to compare the performance of the GA, CS, and BA for the multiloop FOPID controller problem. The integer order internal model control based PID (IMC-PID) controller is designed using the GA and the performance of the IMC-PID controller is compared with the FOPID controller scheme. The simulation results confirm that BA offers optimal controller parameter with a minimum value of IAE, ISE, ITAE with faster settling time.