An Optimal Photovoltaic Conversion System for Future Smart Grids

An Optimal Photovoltaic Conversion System for Future Smart Grids

Carlo Makdisie (Tishreen University, Syria), Badia Haidar (Tishreen University, Syria) and Hassan Haes Alhelou (Tishreen University, Syria)
Copyright: © 2018 |Pages: 57
DOI: 10.4018/978-1-5225-3935-3.ch018

Abstract

Smart grid technology is the key for a reliable and efficient use of distributed energy resources. Amongst all the renewable sources, solar power takes the prominent position due to its availability in abundance. In this chapter, the authors present smart grid infrastructure issues and integrating solar PV-sourced electricity in the smart grid. Smart grid has many features, including reliability, flexibility on network topology, efficiency, sustainability, and market-enabling. The authors select a photovoltaic active power line conditioner as a case study. This line conditioner is a device designed to extract the maximum power of a photovoltaic (PV) system and to compensate the nonlinear and unbalanced loads of the electrical power systems. The performance of the PV conditioner with the neuro-fuzzy control designed has been analyzed through a simulation platform.
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Background

Most of the recent researches have tended to use renewable energy sources found in nature such as, solar energy, wind energy, and tidal energy (Alva, et al. 2017). Due to the increasing demands in clean and new energy resources, the solar energy industry is one of the fastest growing forces in the market. In the last decade, there are several major directions for solar technology development (Thornton, 1992; Chaar, et al. 2008; Mohandes, et al. 2009; Al Hanai, et al. 2010). For example, photovoltaic systems directly convert the solar energy into electrical energy while concentrated solar power systems first convert the solar energy into thermal energy and then further convert it into electrical energy through a thermal engine (Chu & Meisen, 2011).

In literatures, many methods have been used of optimal design and operation of PV systems (Nazaripouya, et al. 2015). Evolutionary optimization methods have the major application in solar systems for getting the maximum power operation point (Patcharaprakiti & Premrudeepreechacharn, 2002). Also, different met-heuristic algorithms such as genetic algorithm, PSO, wind driven optimization algorithm have a good performance for designing and operation of PV systems (Injeti & Padma, 2015).

A comprehensive literature reviews and state of arts in these topics could be found in (Ram, et al. 2017; Gordon, J. M. 2013). Due to space consideration, in this chapter, Authors discuss in depth the solar energy system component and the optimization methods used in solar systems to make their operation more effective.

Key Terms in this Chapter

Solar Energy: The energy received to earth from the sun which is usually converted into electrical or thermal energy.

Optimization: The action to find the best or the most effective solution of a problem.

Renewable Energy: This term describes the energy collected from renewable resources such as sunlight, rain, wind, and geothermal heat energies.

Semiconductor: A semiconductor is a substance that can conduct electricity under some conditions but not others, making it a good medium for the control of electrical current.

Photovoltaic: By using photovoltaic cells, the energy from sunlight can be converted to electricity.

Smart Grids: A flexible power system with high penetration level of renewable energy resources provided with a great communication infrastructure and information management.

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