A novel smart grid theory for optimal sizing of hybrid renewable energy systems. (February 2016)

• Record Type: Journal Article
• Authors: Eltamaly, Ali M.; Mohamed, Mohamed A.; Alolah, Abdulrahman I.
• Is Part Of: Solar energy. Volume 124(2016)
• Page Start: 26
• Page End: 38
• Publication Date: 2016-02
• Subjects: Smart grid -- Hybrid renewable energy systems -- Load shifting -- Load priority -- Sizing -- Optimization; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2015.11.016
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: Techno-economic sizing-based smart grid for standalone HRES. Load shifting-based load priority technique. Optimum design with minimum cost, minimum dummy energy and highest reliability. Pairing between five Saudi Arabia sites, ten WTs and PV array. Abstract: Smart grid enables interaction between the generation and load to optimally deliver energy based on the operating conditions. Although smart grid solves many of the contemporary problems, it gives rise to new control and optimization problems especially with the growing role of renewable energy sources. Load shifting technique has been applied in this paper by dividing the load into two categories, high priority load (HPL) and low priority load (LPL). HPL is that must be supplied whatever the generation conditions, but LPL can be supplied when the generation from renewable sources is available. This paper introduces a new proposed design and optimization program for techno-economic sizing of standalone hybrid PV/wind/diesel/battery energy systems under smart grid theory for the lowest cost of generated energy at highest reliability. An accurate methodology for pairing between five Saudi Arabia sites and ten wind turbines (WTs) from different manufacturers to maximize energy production and minimize the price of kWh generated has been introduced. The new proposed program is implemented in flexible fashion which is not available in many market available programs. Many valuable results can be extracted from the proposed program that could help researchers and decision makers.