Författare

Elham Shirazi

Bästsäljande1 verkEngelska

Elham Shirazi är en uppskattad författare inom Naturvetenskap och teknik med totalt 1 bok tillgängliga på Bokkollen, utgivna hos Institution of Engineering and Technology.

Bland verken finns AI-Based Forecasting of Solar Photovoltaics Power Generation, som toppar listan över Elham Shirazis populäraste böcker. Verken spänner över naturvetenskap & teknik och tilltalar läsare som uppskattar genren.

På Bokkollen gör vi det enkelt att navigera i Elham Shirazis författarskap. Vår databas uppdateras ständigt med nya släpp och format, så oavsett om du söker efter en lättläst pocket för semestern, en lyxig inbunden presentutgåva eller en digital ljudbok för pendlingen, har vi rätt utgåva för dig.

Jämför snabbt och smidigt priser på alla böcker av Elham Shirazi hos Sveriges ledande bokhandlare – som Adlibris, Bokus och Akademibokhandeln – och hitta alltid det bästa erbjudandet utan att betala för mycket.

AI-Based Forecasting of Solar Photovoltaics Power Generation
Mest populär

AI-Based Forecasting of Solar Photovoltaics Power Generation

The widespread deployment of photovoltaics (PV) technology has emerged as a key element in the global shift toward a carbon-neutral and sustainable energy system. Driven by a combination of supportive regulatory frameworks, government incentive programs, technical developments, and increasing environmental awareness, the adoption of PV technologies has witnessed remarkable growth in recent years. However, the rapid integration of distributed PV systems into existing electricity grid infrastructure introduces new challenges, particularly concerning voltage regulation, reverse power flow, and congestion within the electricity grid. These issues are intensified when PV systems are integrated without proper strategy. In this context, solar PV power forecasting has become an essential tool for ensuring the reliable and efficient integration of solar PV systems into power systems. Artificial intelligence (AI) and machine learning (ML) offer means to forecast PV power and energy generation based on historical data of PV generation, meteorological data, and/or weather forecasts. AI-Based Forecasting of Solar Photovoltaics Power Generation blends theoretical knowledge with practical case studies, serving as a comprehensive and timely contribution to the rapidly evolving field of solar PV forecasting. It covers topics such as data collection and processing, solar forecasting based on statistical time-series, machine and deep learning, hybrid and probabilistic approaches, model optimization, hyperparameter tuning, and solar PV forecasting for energy system integration and control. As solar PV systems become increasingly integrated into energy systems, a dedicated book on PV generation forecasting is incredibly useful, making this book an important resource for energy system operators, policymakers, researchers, and students seeking to improve the reliability, resiliency, and efficiency of solar PV systems and the broader systems into which they are integrated.

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