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The purpose of this paper is to study the life cycle cost (LCC) on the operation of power generation. LCC is the total cost of ownership including the cost of the project or asset acquisition, operation and maintenance, and disposal. LCC includes both deterministic costs (such as acquisition costs, improvement costs and disposal costs) and probabilistic (such as the costs of failure, repairs, spare parts, downtime, lost gross margin). Most of the probabilistic costs are associated directly with the reliability and maintenance characteristics of the system.

To be able to analyze failure data using appropriate cost profile in order to represent the fact that each failure has different prices, in different time periods at an economical cycle the new methodology of LCCA Diagram is proposed. Developing criticality ranking of sub‐system, calculating values of Weibull Shape Factor β and Weibull Characteristic Life η for each sub‐system, calculating the time to failure of sub‐system, calculating the mean time to failure of sub‐system using Monte Carlo simulation, determining several alternatives, failure mode and effects analysis and root cause failure analysis are parts of the methodology.

To give a sample of case study, the LCC on the operation of coal fired power plant (CFPP) 330 MW is analyzed. Five alternatives calculation of LCC will be simulated. Graph of cash flow, break‐even graph, and graph of cost/benefit versus risk made for a period of 30 years can be used to asses an effective management program and costs of power plant with a low risk.

The paper suggests that LCC can be used to asses an effective management program and costs of power plant with a low risk.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

As the storage and processing requirement of digital information is increasing on the cloud, it is very difficult for the single cloud provider (CP) to meet the resource requirement. Multiple providers form a federation for the execution of users’ requests. For the federated cloud, this paper aims to address the issue distribution of users’ request for resources and revenue among the providers by offering fair and stable distribution models for the federated cloud.

This paper uses cooperative game (CG)-theoretical models, i.e. Shapley–Shubik power index (SSPI) and Banzhaf power index (BPI) for distribution. Performance is analysed using variance and monotonicity using a case study.

Numerical analysis is done using two scenarios. Monotonicity is evaluated. Results show that SSPI performs better as compared to BPI in terms of fairness accuracy and the framework provide the fair distribution of revenue among providers in the federated cloud.

The proposed framework works efficiently under the specific defined conditions.

Paper provides the fair distribution. It assist the centralised cloud exchange in managing the users’ request in such a way every CPs, in the federated cloud will get an equal chance of serving the users’ request. The framework also provides the stable federation. Proposed work provides less rejection rate of users’ request. Finally, it assists the providers in increasing their profits in the federation.

This paper presents a CG theoretic-based framework for the distribution of resources required and revenue. The framework analysed the performance of distribution models by considering the variance and monotonicity for multiple users’ requests.

At the current stage of electrical technology development, it is relevant to take into account the quality of electrical energy. It can be implemented if an assessed energy quality indicator is available. The amount of electrical energy is determined by active power, which is transmitted over a certain time period. In some cases, reactive power is included in the metering system. The distortion power is justifiably criticized and is not taken into account. The purpose of this paper consists in the substantiation of the indicator of the distortion of the periodic polyharmonic current electrical energy power, by separating from the instantaneous power such harmonics, which formed by same frequencies current and voltage harmonics.

Using the method of calculating linear polyharmonic current circuits, the following quantities are identified in instantaneous power: active, reactive and apparent powers of each harmonic. These components are known from references as canonical.

By the method of instantaneous power harmonic analysis, the components formed by current and voltage harmonics of the same frequency and different frequencies are distinguished.

The RMS value of the instantaneous power due to current and voltage harmonics of different frequencies is justified in the work. This quantity allows you to distinguish the instantaneous power distortion level in comparison with the existing quantity.

The results can be used to assess the level of instantaneous power distortion level in commercial and technical metering systems.

The definition of instantaneous power distortion by extracting the canonical components from it and determining the root mean square value of the remainder is proposed.

The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models.

Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model.

The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms.

Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.

Power management in households has become the periodic issue for electric suppliers and household occupants. The number of electronic appliances is increasing day by day in every home with upcoming technology. So, it is becoming difficult for the energy suppliers to predict the power consumption for households at the appliance level. Power consumption in households depends on various factors such as building types, demographics, weather conditions and behavioral aspect. An uncertainty related to the usage of appliances in homes makes the prediction of power difficult. Hence, there is a need to study the usage patterns of the households appliances for predicting the power effectively.

Principal component analysis was performed for dimensionality reduction and for finding the hidden patterns to provide data in clusters. Then, these clusters were further being integrated with climate variables such as temperature, visibility and humidity. Finally, power has been predicted according to climate using regression-based machine learning models.

Power prediction was done based on different climatic conditions for electronic appliances in the residential sector. Different machine learning algorithms were implemented, and the result was compared with the existing work.

This will benefit the society as a whole as it will help to reduce the power consumption and the electricity bills of the house. It will also be helpful in the reduction of the greenhouse gas emission.

The proposed work has been compared with the existing work to validate the current work. The work will be useful to energy suppliers as it will help them to predict the next day power supply to the households. It will be useful for the occupants of the households to complete their daily activities without any hindrance.

Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed performance. Notes that 18 papers from the Symposium are grouped in the area of automated optimal design. Describes the main challenges that condition computational electromagnetism’s future development. Concludes by itemizing the range of applications from small activators to optimization of induction heating systems in this third chapter.

Thermal analysis of electrical machines is usually performed by using numerical methods or lumped parameter thermal networks depending on the desired accuracy. The analytical prediction of temperature distribution based on the formal resolution of thermal partial differential equations (PDEs) by the harmonic modeling technique (or the Fourier method) is uncommon in electrical machines. Therefore, this paper aims to present a two-dimensional (2D) analytical model of steady-state temperature distribution for permanent-magnet (PM) synchronous machines (PMSM) operating in generator mode.

The proposed model is based on the multi-layer models with the convolution theorem (i.e. Cauchy’s product theorem) by using complex Fourier’s series and the separation of variables method. This technique takes into the different thermal conductivities of the machine parts. The heat sources are determined by calculating the different power losses in the PMSM with the finite-element method (FEM).

To validate the proposed analytical model, the analytical results are compared with those obtained by thermal FEM. The comparisons show good results of the proposed model.

A new 2D analytical model based on the PDE in steady-state for full prediction of temperature distribution in the PMSM takes into account the heat transfer by conduction, convection and radiation.

Integrated solar combined cycle (ISCC) using parabolic trough collector (PTC) technology is a new power plant that has been installed in few countries to benefit from the use of hybrid solar-gas systems. The purpose of this paper is to investigate the challenges in modeling the thermal output of the hybrid solar-gas power plant and to analyze the factors that influence them.

To validate the proposal, a study was conducted on a test stand in situ and based on the statistical analysis of meteorological data of the year 2017. Such data have been brought from Abener hybrid solar-gas central of Hassi R’mel and used as an input of our model.

The proposal made by the authors has been simulated using MATLAB environment. The simulation results show that the net solar electricity reaches 18 per cent in June, 15 per cent in March and September, while it cannot exceed 8 per cent in December. Moreover, it shows that the power plant responses sensibly to solar energy, where the electricity output increases accordingly to the solar radiation increase. This increase in efficiency results in better economic utilization of the solar PTC equipment in such kind of hybrid solar-gas power plant.

The obtained results would be expected to provide the possibility for designing other power plants in Algeria when such conditions are met (high DNI, low wind speed, water and natural-gas availability).

This paper presents a new model able to predict the thermal solar energy and the net solar-electricity efficiency of such kind solar hybrid power plant.