scholarly journals Limiting Distribution of the Three-State Semi-Markov Model of Technical State Transitions of Ship Power Plant Machines and its Applicability in Operational Decision-Making

2020 ◽  
Vol 27 (2) ◽  
pp. 136-144
Author(s):  
Jerzy Girtler
Keyword(s):  
Decision Making ◽  
Statistical Theory ◽  
Power Plant ◽  
Markov Model ◽  
Power Plants ◽  
Preventive Service ◽  
State Transitions ◽  
Gamma Distributions ◽  
Operational Decision Making ◽  
Transition Times

AbstractThe article presents the three-state semi-Markov model of the process {W(t): t ≥ 0} of state transitions of a ship power plant machine, with the following interpretation of these states: s1 – state of full serviceability, s2 – state of partial serviceability, and s3 – state of unserviceability. These states are precisely defined for the ship main engine (ME). A hypothesis is proposed which explains the possibility of application of this model to examine models of real state transitions of ship power plant machines. Empirical data concerning ME were used for calculating limiting probabilities for the process {W(t): t ≥ 0}. The applicability of these probabilities in decision making with the assistance of the Bayesian statistical theory is demonstrated. The probabilities were calculated using a procedure included in the computational software MATHEMATICA, taking into consideration the fact that the random variables representing state transition times of the process {W(t): t ≥ 0} have gamma distributions. The usefulness of the Bayesian statistical theory in operational decision-making concerning ship power plants is shown using a decision dendrite which maps ME states and consequences of particular decisions, thus making it possible to choose between the following two decisions: d1 – first perform a relevant preventive service of the engine to restore its state and then perform the commissioned task within the time limit determined by the customer, and d2 – omit the preventive service and start performing the commissioned task.

scholarly journals Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Ronnason Chinram ◽  
Shahzaib Ashraf ◽  
Saleem Abdullah ◽  
Pattarawan Petchkaew
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Fuzzy Sets ◽  
Wind Power ◽  
Power Plants ◽  
Multicriteria Decision Making ◽  
Detailed Comparison ◽  
Aggregation Operators ◽  
Wind Power Plant ◽  
Operational Laws

The problem of energy crisis and environmental pollution has been mitigated by the generation and use of wind power; however, the choice of locations for wind power plants is a difficult task because the decision-making process includes political, socioeconomic, and environmental aspects. Thus, several adverse consequences have been created by the choice of suboptimal locations. The objective of this paper is to address the integrated qualitative and quantitative multicriteria decision-making framework for the selection of wind power plant locations. Spherical fuzzy sets are the latest extension of the ordinary fuzzy sets. The main characteristic of the spherical fuzzy sets is satisfying the condition that the squared sum of the positive, neutral, and negative grades must be at least zero and at most one. In this research, we establish novel operational laws based on the Yager t-norm and t-conorm under spherical fuzzy environments (SFE). Furthermore, based on these Yager operational laws, we develop list of novel aggregation operators under SFE. In addition, we design an algorithm to tackle the uncertainty to investigating the best wind power plant selection in four potential locations in Pakistan. A numerical example of wind power plant location problem is considered to show the supremacy and effectiveness of the proposed study. Also, a detailed comparison is constructed to evaluate the performance and validity of the established technique.

The Fuzzy Evaluation of Investment Risk Decision-Making of Power Plant Based on the Grey Relation

2012 ◽  
Vol 450-451 ◽  
pp. 981-984 ◽  
Author(s):  
Shu Liang Liu ◽  
Yun Xia Song
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Power Plant ◽  
Power Plants ◽  
Evaluation Method ◽  
Investment Decision ◽  
Correlation Method ◽  
Electric Power Industry ◽  
Fuzzy Evaluation ◽  
Relationship Of

Electric power industry is the basic industries. The power plant will face many risk factors in the investment of time. We need to make these risk factors analyzed, so as to explore the validity and feasibility of the power plant's investment. Based on studying the mutual relationship of risk factors in the power plant investment, the paper puts forward the causal relationship of power plant's risk investment decision-making evaluation, and quoting three power plants uses the grey correlation method, the analytic hierarchy process and fuzzy evaluation method to evaluate reasonably and effectively each risk factors of influencing the investment decision.

scholarly journals The Matter of Decision-Making Control Over Operation Processes of Marine Power Plant Systems with the Use of their Models in the form of Semi-Markov Decision-Making Processes

2021 ◽  
Vol 28 (1) ◽  
pp. 116-126
Author(s):  
Jerzy Girtler ◽  
Jacek Rudnicki
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Transition Process ◽  
Expected Profit ◽  
State Transitions ◽  
Dynamic Programming Method ◽  
Time Interval ◽  
Operation Process ◽  
Operating Decisions ◽  
Device Operation

Abstract The article presents the possibility to control the real operation process of an arbitrary device installed in the marine power plant based on the four-state semi-Markov process, being the model of the process, which describes the transition process of operational states of the device (ek, k = 1, 2, 3, 4), and the transition process of its technical states (sl, l = 1, 2, 3). The operational states ek (k = 1, 2, 3, 4) have the following interpretation: e1 – active operation state resulting from the task performed by the device, e2 – state of ready-to-operate stop of the device, e3 – state of planned preventive service of the device, e4 – state of unplanned service of the device, forced by its damage. Whereas the interpretation of the technical states sl (l = 1, 2, 3) is as follows: s1 – state of full serviceability of the device, s2 – state of partial serviceability of the device, and s3 – state of unserviceability of the device. All these states are precisely defined for the ship main engine (SG). A hypothesis is proposed which justifies the use of this model to examine real state transitions in marine power plant device operation processes. The article shows the possibility to make operating decisions ensuring a rational course of the device operation process when the proposed model of this process and the dynamic programming method based on the Bellman’s principle of optimality are applied. The optimisation criterion adopted when making operating decisions is the expected profit to be gained as a result of functioning of the device in the time interval [τ0, τm], being the sum of the expected profit gained in interval [τ0, τ1] and to be gained in interval [τ1, τm].

scholarly journals Decision Support Technique Based on Neutrosophic Yager Aggregation Operators: Application in Solar Power Plant Locations—Case Study of Bahawalpur, Pakistan

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Shabeer Khan ◽  
Saleem Abdullah ◽  
Shahzaib Ashraf ◽  
Ronnason Chinram ◽  
Samruam Baupradist
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Power Plants ◽  
Solar Power ◽  
Multicriteria Decision Making ◽  
Detailed Comparison ◽  
Aggregation Operators ◽  
Solar Power Plant ◽  
Neutrosophic Sets ◽  
Operational Laws

The problem of energy crisis and environmental pollution has been mitigated by the generation and use of solar power; however, the choice of locations for solar power plants is a difficult task because the decision-making process includes political, socio-economic, and environmental aspects. Thus, several adverse consequences have been created by the choice of suboptimal locations. The objective of this paper is to address the integrated qualitative and quantitative multicriteria decision-making framework for the selection of solar power plant locations. Neutrosophic sets (NSs) are the latest extension of the ordinary fuzzy sets. The main characteristic of the neutrosophic sets is satisfying the condition that the sum of the truth, indeterminacy, and falsity grades must be at least zero and at most three. In this research, we establish novel operational laws based on the Yager t-norm and t-conorm under neutrosophic environments (NE). Furthermore, based on these Yager operational laws, we develop a list of novel aggregation operators under NE. In addition, we design an algorithm to tackle the uncertainty to investigating the best solar power plant selection in five potential locations in Pakistan. A numerical example of solar power plant location problem is considered to show the supremacy and effectiveness of the proposed study. Also, a detailed comparison is constructed to evaluate the performance and validity of the established technique.

Analysis on Electricity-Coal Quality Problems Based on Trust Game Model

2014 ◽  
Vol 521 ◽  
pp. 777-781
Author(s):  
Shu Xia Yang ◽  
Ruo Yang Li ◽  
Yi Lin Liu ◽  
Yuan Cao
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Thermal Power Plant ◽  
Power Plants ◽  
Thermal Power ◽  
Trust Game ◽  
Benefit Sharing ◽  
Test Accuracy ◽  
Game Model

The quality of the electricity-coal affected the economic benefit of the thermal power plant and brought hidden risks to the safe operation of unit. Firstly, we analyze the impacts of thermal power plants test accuracy on electricity-coal suppliers decision-making. Secondly, we present the trust game model and studied the long-term cooperative relationship in electricity-coal suppliers decision-making. Finally, we make a calculation example about the game between the electricity-coal suppliers and the thermal power plant, and it shows that if both sides cooperate to establish a reasonable benefit-sharing mechanism, information asymmetry will be made up, and the quality of the electricity-coal can be ensured fundamentally.

scholarly journals Hydrogen Power Plant Site Selection Under Fuzzy Multicriteria Decision-Making (FMCDM) Environment Conditions

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 596 ◽  
Author(s):  
Chia-Nan Wang ◽  
Ming-Hsien Hsueh ◽  
Da-Fu Lin
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Site Selection ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Multicriteria Decision Making ◽  
Biomass Energy ◽  
Multicriteria Decision ◽  
Decision Making Unit ◽  
Plant Site

Fuel and energy are basic resources necessary to meet a country’s socioeconomic development needs; further, countries rich in these resources have the best premise for meeting the inputs of an economic system; however, this also poses many political challenges and threats to national security. Vietnam is located in the Southeast Asian monsoon-humid tropical region and has diverse fuel-energy resources such as coal, petroleum, and hydropower, along with renewable energy sources such as solar energy, biomass energy, and geothermal energy. However, the reality of economic development in recent years shows complex fluctuations in fuel and energy usage, i.e., besides the export of coal and crude oil, Vietnam still has imported processed oil products. To overcome this issue, many hydrogen power plants will be built in the future. This is why we propose fuzzy multicriteria decision-making (FMCDM) for hydrogen power plant site selection in this research. All criteria affecting location selection are determined by experts and literature reviews, and the weight of all criteria are defined by a fuzzy analytic hierarchy process (FAHP). The technique for order of preference by similarity to an ideal solution (TOPSIS) is a multicriteria decision analysis method, which is used for ranking potential locations in the final stage. As a result, the decision-making unit, DMU010 (DMU010), has become the optimal solution for building hydrogen power plants in Vietnam. A multicriteria decision-making (MCDM) model for hydrogen power plant site selection in Vietnam under fuzzy environment conditions is a contribution of this study. This research also provides useful tools for other types of renewable energies in Vietnam and other countries.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Human Factors ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Cooling System ◽  
Human Reliability ◽  
Non Destructive ◽  
Plant Components

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.

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