Location and investment factors of hydropower plants

Li, Yongsong; Saraçoğlu, Burak Ömer

doi:10.1080/15567036.2021.1963015

Cited by 6 publications

(5 citation statements)

References 84 publications

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“…All of these robots and platforms are open-science so some specific studies are also necessary to find out the best way to present them as re-runnable, repeatable, reproducible, reusable, and replicable, simple, traceable, transparent, and trustworthy manner. They will evolve into open-science humanoid robots after their very long-term RD3&D periods (Li & Saracoglu, 2021;Saracoglu, 2022a;Saracoglu, 2022b).…”

Section: Discussionmentioning

confidence: 99%

“…Many scientific methods can be used/implemented in the investment selection research topic (Li & Saracoglu, 2021;Saracoglu, 2022a). Type-2 Mamdani's type fuzzy inference systems (FISs) or fuzzy rule base systems (FRBSs) can effectively be used in several models for many problems and adopted in all automatized systems.…”

Section: Introductionmentioning

confidence: 99%

“…It is just an academic study so nothing is commercial in this publication like the author's previous publications. In addition, this study is only a small part of a huge research, development, demonstration, deployment, and diffusion (RD3&D) activity to present some open-science robots and platforms called Global Power Robots and Platforms: GPRP/ GPRAP (Global Power Plants Developers: GP2D/G2PD/GPPD, Global Power Plants Engineers: GP2E/G2PE/GPPE, Global Power Plants Owners: GP2O/G2PO/GPOO, Global Power Prediction Systems: GP2S/G2PS/GPPS), Global Profile Analyses Systems (GPAS) and Global Social Network Analyses Systems (GSNAS)) (Li & Saracoglu, 2021;Saracoglu, 2022a;Saracoglu, 2022b). Thus, it must be understood very well that nothing can be accepted as a final model/product/software.…”

Section: Introductionmentioning

confidence: 99%

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An Experimental Private Small Hydropower Plant Investments Selection Classification System

Saracoglu

2023

JDSIS

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Investment selection problems and models are crucial for humans, communities, and states. Private small hydroelectric power/hydropower plant investments (PSHPPIs) selection problem is a unique one in those problems and models. Many available scientific methods can be implemented on this research topic. One of them is type-2 Mamdani's type fuzzy inference systems (FISs). This study presents an experimental one-node general type-2 4-zslices Mamdani's type FIS model for PSHPPIs selection. There are 3 input variables (total estimated electricity generation: M1, total estimated cost: M2, change in the average runoff: M3), 1 output variable (O1: selected/unselected, selection classification of PSHPPIs), and 49 rules. M1 is designed in 5 triangular and trapezoidal general type-2 4-zslices fuzzy membership functions (MFs), M2 in 5 triangular and trapezoidal general type-2 4-zslices fuzzy MFs, M3 in 5 Gaussian type-2 4-zslices fuzzy MFs, and O1 in 2 Gaussian type-2 4-zslices fuzzy MFs. All modeling details are finalized by a human-expert decision process. JuzzyOnline V2.0, a browser-based platform of Juzzy (a Java-based library: Juzzy toolkit), is used for all FIS modeling and calculation activities. 5 PSHPPI options assumed to be in their very early investment stages in Turkiye are evaluated in an experimental application. It is clear that an improved, tuned, and fine-tuned version of this model will help private investors to take more convenient/satisfying actions/decisions in a very short evaluation period in their PSHPPIs decision processes. An automatic investment selection classification system can be built in an appropriate development period after experiencing many methods and models. This study is one of the open-science humanoid robot, robot and platform development activities entitled Global Power Robots and Platforms: GPRP/GPRAP (Global Power Plants Developers: GP2D/G2PD/GPPD, Global Power Plants Engineers: GP2E/G2PE/GPPE, Global Power Plants Owners: GP2O/G2PO/GPOO, Global Power Prediction Systems: GP2S/G2PS/GPPS), Global Profile Analyses Systems (GPAS), and Global Social Network Analyses Systems (GSNAS).

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Experimental Private Small Hydropower Plant Investments Selection Classification System

Saracoglu

2023

JDSIS

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“…However, alternative energy sources must be sustainable so that it could be used for a long term and they do not compete with other (Almutairi et al, 2023;Ilham et al, 2022). As reported in literature, the existing renewable energy sources such hydropower (Forouzi Feshalami, 2018;Li and Saracoglu, 2021), wind (Chen et al, 2022;Hassoine et al, 2022), solar (Shahzad Nazir et al, 2021;Shi and Luo, 2018), biomass (Duc Bui et al, 2023;Ortiz-Alvarez et al, 2022), and hydrogen (Kharisma et al, 2022; S. J. are available and abundant. Additionally, the population in the world is increasing, showing a large number of wastes could be released into environment every day that also cause the threat to the living environment (Bigdeloo et al, 2021;Wowrzeczka, 2021).…”

Section: Introductionmentioning

confidence: 99%

Simulation and experimental study of refuse-derived fuel gasification in an updraft gasifier

Nguyen-Thi

Bui

2023

Int. J. Renew. Energy Dev.

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Refuse-derived fuel (RDF) made from the mixture of wood and loose rice husk increases the porosity of the fuel in the furnace to facilitate the gasification process. Simulation results show that CO is concentrated in the incomplete combustion zone and CO2 forms mainly in the fully burned area; CH4 forms in the reduction region, while H2 forms in the region of high temperature of the furnace. When the mixture composition was f=0.3, the CO concentration in the syngas reached about 21%, the H2 concentration reached about 2% and the CH4 concentration was too low to be ignored. When the mixture composition increased to f = 0.5, the CO concentration reached about 26%, the H2 concentration remained almost unchanged and the CH4 content increased to 6%. The calorific value of the syngas reached a maximum when f = 0.5 and the temperature of the reduction zone is in the range of 900K to 1200K. Air humidity affects CO concentration but not much on CH4 and H2 concentration as well as the syngas calorific value. The difference between simulation and experimental results is not more than 10% for CH4 concentration and not more than 14% for CO2 concentration. The power of the spark ignition engine is reduced by 30% when running on syngas compared to when running on gasoline.

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“…The weighted method (Y. Li & Saracoglu, 2021) and center of gravity (Xiang et al, 2017) were selected.…”

Section: Methodologies and Methodsmentioning

confidence: 99%

Location of a coconut processing industry in the context of the agri-food chain

Proceedings of the International Conference on Industrial Engineering and Operations Management

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Location problems remain a practical necessity, despite their extensive theoretical development. The objective of the research is to identify the location of a coconut plant and its derivatives in the context of the Manabí agrifood chain. A procedure for locating a coconut derivatives processing industry was developed using a mathematical model. In the first stage: characterization of the variables of the value chain, it helps to determine the most feasible location of a coconut plant in the province of Manabí. The actors and links in the chain are identified. Along with the description of these. In the second stage: selection of the location method, each location method is analyzed with its risks and potential for decision-making on the location of the coconut derivatives processing plant in the province of Manabí. The methods selected for the location of the plant are applied and the one with the highest performance is chosen. The weighted method and center of gravity were selected. In the third stage, the model that best fits the one carried out 379

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Location and investment factors of hydropower plants

Cited by 6 publications

References 84 publications

An Experimental Private Small Hydropower Plant Investments Selection Classification System

An Experimental Private Small Hydropower Plant Investments Selection Classification System

Simulation and experimental study of refuse-derived fuel gasification in an updraft gasifier

Location of a coconut processing industry in the context of the agri-food chain

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