https://eva.fing.edu.uy/pluginfile.php/55828/mod_resource/content/1/kalogiru.pdf

Solar thermal collectors and applications

Renewable technologies are considered as clean sources of energy and optimal use of these resources minimize environmental impacts, produce minimum secondary wastes and are sustainable based on current and future economic and social societal needs. Sun is the source of all energies. The primary forms of solar energy are heat and light. Sunlight and heat are transformed and absorbed by the environment in a multitude of ways. Some of these transformations result in renewable energy flows such as biomass and wind energy. Renewable energy technologies provide an excellent opportunity for mitigation of greenhouse gas emission and reducing global warming through substituting conventional energy sources. In this article a review has been done on scope of CO2 mitigation through solar cooker, water heater, dryer, biofuel, improved cookstoves and by hydrogen.

https://www.beren.sakarya.edu.tr/sites/beren.sakarya.edu.tr/file/1380752545-07-RenewEn.pdf.pdf

Role of renewable energy sources in environmental protection: A review

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, the operation of sub-level components like lighting and HVAC systems, occupancy and their behavior. This complex situation makes it very difficult to accurately implement the prediction of building energy consumption. This paper reviews recently developed models for solving this problem, which include elaborate and simplified engineering methods, statistical methods and artificial intelligence methods. Previous research work concerning these models and relevant applications are introduced. Based on the analysis of previous work, further prospects are proposed for additional research reference.

A review on the prediction of building energy consumption

A review of computer tools for analysing the integration of renewable energy into various energy systems

Due to the increasing need for intelligent systems, the Adaptive Neuro-fuzzy Inference System (ANFIS) has recently attracted the attention of researchers in various scientific and engineering areas. The purpose of this work is to present the modeling of a Photovoltaic Power Supply PVPSsystem using an ANFIS. For the modeling of the PVPS-system, it is required to find suitable models for its different components (ANFIS-PV-array, ANFIS-battery and ANFIS-regulator) under variable climatic conditions. A database of measured weather data (global radiation and temperature) and electrical signals (photovoltaic, battery and regulator voltage and current) of a PVPS system installed in Tahifet (south of Algeria) has been recorded for the period from 1992 to 1997 using a data acquisition system. These data have been used for the modeling and simulation of the PVPS-system. The ANFIS for the PV-array, battery and regulator have been trained by using 8 signals recorded from the different components of the PVPS system. Each signal is represented by 365*5 values (complete 5-years). A set of data for 4-years have been used for the training of the ANFIS, and data for 1-year has been used for the testing of the ANFIS. In this way, the ANFIS was trained to accept and handle a number of unusual cases. The comparison between actual and estimated values obtained from the ANFIS gave satisfactory results. The correlation coefficient between measured values and those estimated by the ANFIS gave good prediction accuracy of 98%. In addition, test results show that the ANFIS performed better than the neural networks. The results obtained from ANFIS can also be used for the prediction of the optimal configuration of PV systems, for the control of PV systems and for the prediction of the performance of the systems.

/pdf/an-anfis-based-modeling-for-a-photovoltaic-power-supply-pvps-511t8lx4pu.pdf

An ANFIS-based Modeling for a Photovoltaic Power Supply (PVPS) System

In this work, hourly measurements of global solar irradiances obtained from pyranometers and sunshine duration data using either Kipp & Zonen CSD3 automatic sensors or Campbell–Stokes sunshine recorders were assessed through an extensive quality control procedure and statistical analysis on the measured and derived solar parameters for all the actinometric stations installed in various locations over the island of Cyprus, covering mainly the period 2019–2021. This information is useful for engineers concerning the solar energy capture systems and energy efficiency who can therefore take knowledge of the local radiation levels. Monthly mean hourly values of global radiation and sunshine duration are calculated and shown through isoline diagrams. During June or July, daily global irradiations ranged between 25 MJ/m2 and 30 MJ/m2, with the lowest occurring in the mountainous locations. On the other hand, in January or December, they ranged between 6.5 MJ/m2 and 10.5 MJ/m2. The total annual number of hours of sunshine duration ranged between 2500 and 3500, with the lowest values recorded at the mountainous sites. The clearness index and relative sunshine duration were used for the classification of the weather conditions over the island. Furthermore, the interrelationships between the said indices were used for the estimation of global radiation. This work has specifically contributed to the characterization and analysis of hourly and daily solar global radiation. Furthermore, the measurements on the ground level could be compared with satellite observations in order to improve the geographical distribution of global radiation, especially in areas where no measurements exist. The analysis could be also extended for the other shortwave radiation components (Direct, Diffuse and Photosynthetic Active Radiation (PAR)) in order to assess the solar radiation regime over the island.

Geographical Distribution of Global Radiation and Sunshine Duration over the Island of Cyprus

Building integration of a BIPV and a BIPV/T system on a double skin façade: Design optimization and energy analysis of a one-bedroom studio apartment and its semi-open space

Soteris A. Kalogirou

Papers

An ANFIS-based Modeling for a Photovoltaic Power Supply (PVPS) System

Geographical Distribution of Global Radiation and Sunshine Duration over the Island of Cyprus

Building integration of a BIPV and a BIPV/T system on a double skin façade: Design optimization and energy analysis of a one-bedroom studio apartment and its semi-open space