SCNN Based Electrical Characteristics of Solar Photovoltaic Cell Model

Solar photovoltaic (PV) cell is one of the renewable energy sources and a main component of PV power systems. The design of PV power systems requires accurately its electrical output characteristics. The electrical characteristics of solar PV cell consist of I-V and P-V characteristics. They depend on the parameters of PV cell such as short circuit current, open circuit voltage and maximum power. Solar PV cell model can be described through an equivalent circuit including a current source, a diode, a series resistor and a shunt resistor. In this paper, the development solar PV cell model is built by using self constructing neural network (SCNN) methods. This SCNN technique is used to improve the accuracy of the electrical characteristic of solar PV cell model. SCNN solar PV cell model have three inputs and two outputs. They are respectively solar radiation, temperature, series resistance, current and power. The effectiveness of SCNN technique is verified using simulation results based on different physical and environmental conditions. Simulations are conducted by the change of the solar irradiation, temperature and series resistance. Simulation results show SCNN model can yield the I-V and P-V characteristics according to the characteristics of solar PV cell

Optimal models for planning and managing expences of construction project realisation

Cilj izrade ove disertacije je naučni opis konceptualnog okvira za planiranje i kontrolu realizacije građevinskih projekata baziranog na savremenim metodama usklađenim sa realnim stanjem domaćeg građevinarstva, kako bi se omogućilo uspešno upravljanje projektima u skladu sa zahtevima i standardima međunarodnih ugovora. U prvom delu disertacije definisani su: predmet i ciljevi istraživanja, kao i metodologija izrade disertacije. Nakon toga objašnjene su sadašnje ekonomske karakteristike građevinskog tržišta, predviđanje budućih kretanja i predložene su mere za poboljšanje funkcionisanja građevinskog sektora u Srbiji. U drugom delu disertacije objašnjena je važnost planerskog pristupa pri upravljanju građevinskim projektima, gde su pobrojani i ukratko objašnjeni i načini sprovođenja tenderskih postupaka pri izboru izvođača radova, kao segment kojim najviše može da se utiče na trajanje i uspešnost realizacije projekta. U trećem delu objašnjeni su standardni modeli za kontrolu realizacije projekata, i data je detaljna metodologija za analizu i upravljanje rizicima. Na osnovu analize nedostataka standardnih savremenih metoda formiran je model za planiranje i kontrolu realizacije, baziran na kontroli direktno angažovanih ljudskih resursa sa akcentom na finansijsko planiranje, zasnovan na principima upravljanja lancima snabdevanja (supply chain management), a kontrola realizacije je bazirana na primeni "last planner" metodologije. Ovaj model je predstavljen kao osnova za razvoj i prilagođavanje konkretnim problemima u praksi, pri realizaciji zasnovanoj na transparentnom prikazivanju troškova. U četvrtom poglavlju dat je prikaz primene neuralnih mreža kao osnova za matematičko modeliranje modula za planiranje troškova na građevinskim projektima. Podaci koji su prikupljeni sa projekata gde je primenjena analiza zarađene vrednosti su korišćeni za trening neuralne mreže kako bi se ustanovila zavisnost parametara kojima se meri uspešnost projekata. Međutim, sa raspoloživim uzorkom nije se postigla dovoljna tačnost iako se sa povećanjem broja podataka za trening greška smanjivala, tako da nije moguće koristiti ovakav model, ali ga je moguće unaprediti sa dodatnim podacima za trening, kako bi se povećala tačnost ustanovljenog modela. Na osnovu izvršenih analiza i prikupljenih podataka iz prakse definisane su dve neuralne mreže, jedna za predviđanje uspešnosti kompletnog projekta sa šest ulaznih i dve izlazne varijable, koje predstavljaju % izvršenja i PF faktor na nivou kompletnog projekta, koja nije dala očekivane rezultate, i druga sa deset ulaznih i dve izlazne varijable, koje predstavljaju troškove izgradnje i ostvareni profit izvođača radova, i koje su iskorišćene kao osnova za trening neuralne mreže, u programu MatLab. Kako podaci vezani za troškove građenja predstavljaju praktično linearnu aproksimaciju, sa dovoljnom tačnošću može se razviti model u kome ulazni podaci ne moraju biti visoke tačnosti, već se mogu aproksimirati u unapred određenom opsegu. Ovo je i potvrđeno primenom heksa asocijativne memorije. U šestom poglavlju model je primenjen na 3 karakteristična slučaja iz prakse, i postignuta je dovoljna tačnost za donošenje odluke o razvoju određenih projekata. Na kraju su dati zaključci do kojih se došlo takom izrade ove disertacije.The aim of this dissertation is a scientific description of the conceptual framework for planning and controlling the implementation of construction projects based on modern methods compatible with the real situation of the domestic construction industry, in order to enable successful projects management in accordance with the requirements and standards of international contracts. The first part of the thesis defines the subject and research objectives as well as the methodology of the dissertation. Afterwards the current economic characteristics of the construction market, forecasting future trends are explained and the measures for the improvement of construction sector functioning in Serbia. The second part of the thesis explains the importance of the planning approach in construction projects management, where also the ways of tendering procedures implementation in the selection of contractors are listed and briefly explained as a segment that can mostly affect the duration and success of the project completion. The third section explains the standard models for the control of project implementation, and provides a detailed methodology for the risk analysis and management. Based on the analysis of standard modern methods deficiencies the model for planning and implementation control is formed based on the control of directly involved human resources with the emphasis on financial planning. It is formed on the principles of supply chain management based on "the last planner" methodology. This model is presented as a basis for the development and adaptation of specific problems in practice at the implementation with a transparent presentation of costs. The third chapter gives an overview of neural networks application as a basis for mathematical modeling of modules for planning costs on construction projects. The data collected from the projects where the analysis of earned value is applied have been used for the neural network training to establish the dependence of the parameters which measure the success of projects. However, sufficient accuracy was not achieved with the available sample, although error decreased with the increase of the number of data for training; thus it is not possible to use such a model, but it can be improved with additional data for training in order to increase the accuracy of the established model. Based on the analyses and data collected from the practice defined by the two neural networks, one for predicting the success of the overall project with six input and two output variables that represent the completion percentage as well as PF factor at the level of the overall project, which has not made the expected results, and the other with ten input and two output variables, which represent construction costs and realized contractors’ profit, and which are used as the basis for neural network training in Matlab program. As the data regarding the construction costs are practically a linear approximation with sufficient accuracy the model can be developed in which input data need not be of high accuracy, but can be approximated in a predetermined range. This has been confirmed by using a hex of associative memory. In the sixth chapter this model is applied to three typical case studies, and sufficient accuracy is achieved to make a decision on the development of certain projects. Finally, the conclusions are given reached during the dissertation completion