Renewable energy potential and national policy directions for sustainable development in Morocco

Kousksou, T.; Allouhi, A.; Belattar, M.; Jamil, A.; Rhafiki, T. El; Arid, A.; Zéraouli, Y.

doi:10.1016/j.rser.2015.02.056

Cited by 207 publications

(86 citation statements)

References 27 publications

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“…2. The multi-objective ODGP by GA is introduced in (Singh et al, 2015;Sanchez et al, 2015;Kousksou et al, 2015;Mallol et al, 2015).…”

Section: Genetic Algorithmsmentioning

confidence: 99%

“…Usually, GA uses three simple operators called as selection, recombination or crossover and mutation (Khajehzadeh et al, 2011). The multi-objective ODGP using GA is introduced in Khajehzadeh et al (2011), Singh et al (2015, Sanchez et al (2015), Kousksou et al (2015), Mallol et al (2015), Valipour (2015a,c) and Khoshravesh et al (2015).…”

Section: A Brief Overview Of Gamentioning

confidence: 99%

“…In this paper, GA optimization technique, as developed in the previous work of Holland (1975a,b), Khajehzadeh et al (2011), Singh et al (2015, Sanchez et al (2015), Kousksou et al (2015) and Mallol et al (2015), has been used for finding the best solutions of the MOPIF optimization algorithm.…”

Section: Ga Implementationmentioning

confidence: 99%

“…Depending upon the types and the sizes, Table 2 depicts the existing categories of DGs (Singh et al, 2008; IEEE Task Force on Load Representation for Dynamic Performance, 1993;Quial et al, 2011;Hossein and Morteza, 2012;Kumar and Mittapalli, 2014;Payasi et al, 2012a,b;Chiradeja and Ramakumar, 2014;Holland, 1975a,b;Khajehzadeh et al, 2011;Singh et al, 2015;Sanchez et al, 2015;Kousksou et al, 2015;Mallol et al, 2015). The four broad categories of DGs named as T 1 , T 2, T 3 and T 4 are discussed in details in Singh et al (2008Singh et al ( , 2015, IEEE Task Force on Load Representation for Dynamic Performance (1993), Quial et al (2011), Hossein andMorteza (2012), Kumar and Mittapalli (2014), Payasi et al (2012a,b), Chiradeja and Ramakumar (2014), Holland (1975a,b), Khajehzadeh et al (2011), Sanchez et al (2015, Kousksou et al (2015) and Mallol et al (2015). Valipour (2012aValipour ( ,b, 2013Valipour ( , 2015a and Khoshravesh et al (2015) are also very much useful literatures on the importance of optimization and optimized values (in other fields) to enhance the literature and to indicate advantages of this research work.…”

Section: Introductionmentioning

confidence: 99%

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GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems

Singh¹,

Mukherjee

Tiwari

2017

Journal of Electrical Systems and Information Technology

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Please cite this article in press as: Singh, B., et al., GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems. J. Electr. Syst. Inform. Technol. (2016), http://dx. AbstractIn the present scenario of all over world, the planning of distributed generations (DGs) in distribution power systems are very important issues from power system performances viewpoints. The broad categories of different types of DGs on the basis of their power delivering characteristics are considered T 1 , T 2 , T 3 and T 4 with different load models (DLMs) for the analysis in this paper. This paper presents the impact assessment of optimally placed different types of DGs (such as T 1 , T 2 , T 3 and T 4 ) with DLMs by employing genetic algorithm (GA) in the distribution power systems (DPSs) form total minimum real power loss of the system viewpoint. Different DPS performance parameters such as minimization of real power loss, minimization of reactive power loss, improvement of voltage profile, reduction of the short circuit current or MVA line capacity and reduction of the environmental green house gases like carbon dioxide (CO 2 ), sulphur dioxide (SO 2 ), nitrogen oxide (NO x ) and particulate matters in emergency e.g. under fault, sudden change in field excitation of alternators or load increase in the distribution power system are considered. The contribution of the present work is to investigate the comparisons of different DGs with DLMs by excercizing GA in the distribution systems form minimum total real power loss of the system viewpoint. The effectiveness of the proposed methodology is tested on IEEE-37 bus distribution test system. The different types of DGs (such as T 1 , T 2 , T 3 and T 4 ) with DLMs have shown different behaviours for power system performance indices such as PLI, QLI, VDI, SCCI and EIRI viewpoints. The sequence of overall power system performance indices such as PLI, QLI, VDI, SCCI and EIRI are as follows: T 2 > T 1 > T 4 > T 3 . This paper presents that the overall performance of T 2 type DG is better as compared to T 1 , T 3 and T 4 types DGs in the distribution system form minimum real power loss of the system viewpoint.Please cite this article in press as: Singh, B., et al., GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems. J. Electr. Syst. Inform. Technol. (2016), http://dx.

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“…2. The multi-objective ODGP by GA is introduced in (Singh et al, 2015;Sanchez et al, 2015;Kousksou et al, 2015;Mallol et al, 2015).…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Section: A Brief Overview Of Gamentioning

confidence: 99%

Section: Ga Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems

Singh¹,

Mukherjee

Tiwari

2017

Journal of Electrical Systems and Information Technology

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“…The Kingdom must meet a growing demand (around 7% per year) because of its economic development and population growth [17,18]. To meet these challenges, the Ministry of Energy, Mines, Water and Environment has developed a new national energy strategy to secure energy supplies while adopting a sustainable development approach.…”

Section: Introductionmentioning

confidence: 99%

Auditing and analysis of energy consumption of an industrial site in Morocco

Boharb

Allouhi

Saidur

et al. 2016

Energy

Self Cite

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Sustainable production of wind energy in the main Morocco's sites using permanent magnet synchronous generators

Mourabit¹,

Derouich²,

Allouhi³

et al. 2020

Int Trans Electr Energ Syst

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Summary This paper assesses the behavior of a wind energy conversion system (WECS) under the fuzzy control in several sites located in Morocco. The sites involved in this study are located in coastal areas, namely, Assila, Houceima, Tetouan, Dakhla, Essaouira, and Laayoun. Furthermore, the first part deals with an inventory and state of art of the wind potential, achievements, work in progress, and future projects in the Kingdom of Morocco. Subsequently, a statistical analysis of the wind data and concerning the wind speed and direction in relevant geographical areas was presented in detail. The second part of the paper examines the control of WECS which is based on the direct control of the permanent magnet synchronous generator. Generator connection to the power grid is achieved by two power converters in back‐to‐back configuration controlled by pulse width modulation. The whole system modeling including the generator modeling was discussed. The control development based on (Fuzzy‐proportional‐integral) corrector for the machine‐side converter and the maximization of the power extracted from the wind using the maximum power point tracking technique have been developed. The grid‐side converter ensures the system connection to the grid with good power quality and controls the DC bus voltage. The control strategy is verified through the simulation in the Matlab‐Simulink environment to validate and evaluate the dynamic performance of the system using real wind measurements for the selected sites. The obtained results prove the effectiveness of the intended control. Interestingly, the southern zone of Morocco is more convenient for the exploitation of electricity production compared to the northern zone of the country which it can be beneficial for autonomous applications.

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Renewable energy potential and national policy directions for sustainable development in Morocco

Cited by 207 publications

References 27 publications

GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems

GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems

Auditing and analysis of energy consumption of an industrial site in Morocco

Sustainable production of wind energy in the main Morocco's sites using permanent magnet synchronous generators

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