Solar Power System Planning & Design: Resource Assessment, Site Evaluation, System Design, Production Forecasting  and Feasibility Studies

doi:10.3390/books978-3-03943-638-5

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Solar Power System Planning & Design: Resource Assessment, Site Evaluation, System Design, Production Forecasting and Feasibility Studies

Resource Assessment, Site Evaluation, System Design, Production Forecasting and Feasibility Studies

Edited by

December 2020

308 pages

ISBN978-3-03943-637-8 (Hardback)
ISBN978-3-03943-638-5 (PDF)

https://doi.org/10.3390/books978-3-03943-638-5

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This book is a reprint of the Special Issue Solar Power System Planning & Design: Resource Assessment, Site Evaluation, System Design, Production Forecasting and Feasibility Studies that was published in

Biology & Life Sciences

Chemistry & Materials Science

Computer Science & Mathematics

Engineering

Environmental & Earth Sciences

Physical Sciences

Summary

Photovoltaic (PV) and concentrated solar power (CSP) systems for the conversion of solar energy into electricity are technologically robust, scalable, and geographically dispersed, and they possess enormous potential as sustainable energy sources. Systematic planning and design considering various factors and constraints are necessary for the successful deployment of PV and CSP systems. This book on solar power system planning and design includes 14 publications from esteemed research groups worldwide. The research and review papers in this Special Issue fall within the following broad categories: resource assessments, site evaluations, system design, performance assessments, and feasibility studies.

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Keywords

solar tower power plants; direct normal irradiation; energy projects; system advisor model; solar irradiance forecasting; wavelet decomposition; convolutional neural network; recurrent neural network; long short term memory; DSER; evaluation model; geographic information; commonality indexes; individuality indexes; photovoltaic; optimum sizing; design; renewable energy; stand alone; grid connected; solar output power forecasting; combined prediction model; variational model decomposition; deep belief networks; auto-regressive and moving average model; PV-thermal collector; nanofluid; particle shape; finite volume method; photovoltaic systems; thin film modules; performance assessment; PV efficiency; floating photovoltaic system; renewable energy; solar energy; photovoltaic energy; greenhouse gas; distributed PV generation; microgrid; irradiance forecasting; all-sky imager; Raspberry Pi; optical flow; machine learning; cloud-computing; SmartGrid; Internet of Things (IoT); irradiance nowcasting; Sun detection; sky dynamics; image processing; particle filtering; net load forecasting; phase space reconstruction; deep neural network; offshore PV; tilt angle; wind incidence angle; wind load; economic–energy–environment (3E) analysis; solar pumping; renewable energy source (RES) integration; net-metering; sustainable rural development; geographic information system; solar energy; resource mapping; site evaluation; potential assessment; photovoltaic; concentrated solar power; n/a