Optimum Size of Hybrid Renewable Energy System to Supply the Electrical Loads of the Northeastern Sector in the Kingdom of Saudi Arabia

Round 1

Reviewer 1 Report

Interesting topic.

Well written article.

Author Response

Reviewer-1: Comments and Suggestions for Authors

Interesting topic. Well written article.

Thankyou sir for your valuable decision about our work.

Author Response File: Author Response.docx

Reviewer 2 Report

1. I would like to appreciate the authors for their contribution.

2. The novelty of the paper is good

3.The list of references must be updated with the newest references since 2019.

4- The quality of all the figures should be improved

5-The main results of the research should be included in the abstract and the conclusion

6- The authors should clarify the details of thier control method and what is the causes or  novelty of the selection to this tool of control.

7.I would also recommend the authors to expand the introduction section to describe the reasoning and motivation behind the application of their research and identify their own scientific contribution and hypothesis more clearly.

8.You should extend the abstract to clear the novelty and the contribution of your work.

9.The reviewer recomend the author to make comparison with the latest method from the literatures

Author Response

Reviewer-2: Comments and Suggestions for Authors

1. I would like to appreciate the authors for their contribution.

Thankyou sir for your valuable impression about our work

2. The novelty of the paper is good

Thankyou sir for your impression

3.The list of references must be updated with the newest references since 2019.

This comment is considered in the revised manuscript by adding the following paragraph:

“Abbassi et al. [21] introduced a virus colony search algorithm t mitigate the total cost of electricity generated from PV/WT/battery system. Zhao et al. [22] managed the energy of grid-connected microgrid with renewable energy generating units optimally via a hybrid optimizer comprising shuffled frog leaping and pattern search. A modified moth flame optimizer has been used to identify the optimal size of stand-alone renewable energy generation system such that the total cost of electricity is minimized [23]. Moreover, LPSP has been employed to enhance the selected configuration reliability. Li et al. [24] presented a hybrid approach of gravitational search algorithm and pattern search to implement the energy management of renewable energy-based micro grid with plug-in hybrid electric vehicles (PHEVs). Suresh et al. [25] constructed an optimal configuration of wind-PV system with backup battery bank and DG via particle swarm optimizer (PSO) and GA such that the system total cost is mitigated. Bifacial rooftop, floating solar, wind energy system, and solid waste-based waste energy have been evaluated for smart city using adaptive local attractor-based quantum behaved PSO to achieve economic operation of the constructed system [26]. Al-Othman et al. [27] conducting comprehensive review study about artificial intelligence applications in hybrid renewable energy system. Multi-objective evolutionary algorithm with decision-making has been used to establish wind-PV-battery-thermal energy storage system to minimize the net present cost and LPSP [28].”

Also, the following references are added:

[21] Abbassi, A., Ben Mehrez, R., Abbassi, R., Jerbi, H., Saidi, S., & Jemli, M. (2022). Eco-feasibility study of a distributed power generation system driven by renewable green energy sources. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(2), 3981-3999.

[22] Zhao, L., Jerbi, H., Abbassi, R., Liu, B., Latifi, M., & Nakamura, H. (2021). Sizing renewable energy systems with energy storage systems based microgrids for cost minimization using hybrid shuffled frog-leaping and pattern search algorithm. Sustainable Cities and Society, 73, 103124.

[23] Abbassi, A., Mehrez, R. B., Abbassi, R., Saidi, S., Albdran, S., & Jemli, M. (2022). Improved off‐grid wind/photovoltaic/hybrid energy storage system based on new framework of Moth‐Flame optimization algorithm. International Journal of Energy Research, 46(5), 6711-6729.

[24] Li, N., Su, Z., Jerbi, H., Abbassi, R., Latifi, M., & Furukawa, N. (2021). Energy management and optimized operation of renewable sources and electric vehicles based on microgrid using hybrid gravitational search and pattern search algorithm. Sustainable Cities and Society, 75, 103279.

[25] Suresh, M., Meenakumari, R., Panchal, H., Priya, V., El Agouz, E. S., & Israr, M. (2022). An enhanced multiobjective particle swarm optimisation algorithm for optimum utilisation of hybrid renewable energy systems. International Journal of Ambient Energy, 43(1), 2540-2548.

[26] Nuvvula, R. S., Devaraj, E., Elavarasan, R. M., Taheri, S. I., Irfan, M., & Teegala, K. S. (2022). Multi-objective mutation-enabled adaptive local attractor quantum behaved particle swarm optimisation based optimal sizing of hybrid renewable energy system for smart cities in India. Sustainable Energy Technologies and Assessments, 49, 101689.

[27] Al-Othman, A., Tawalbeh, M., Martis, R., Dhou, S., Orhan, M., Qasim, M., & Olabi, A. G. (2022). Artificial intelligence and numerical models in hybrid renewable energy systems with fuel cells: Advances and prospects. Energy Conversion and Management, 253, 115154.

[28] He, Y., Guo, S., Zhou, J., Ye, J., Huang, J., Zheng, K., & Du, X. (2022). Multi-objective planning-operation co-optimization of renewable energy system with hybrid energy storages. Renewable Energy, 184, 776-790.

4- The quality of all the figures should be improved

This comment is considered, most of figures are redrawn with good quality

5-The main results of the research should be included in the abstract and the conclusion

This comment is considered in the revised manuscript by adding the following paragraphs

In abstract: “The proposed COA succeeded in achieving the best fitness values of 0.03883 $/kWh, 0.03863 $/kWh, and 0.04585 $/kWh for PV/WT/battery, PV/battery, and WT/battery systems respectively.”

In conclusion: “The best optimal design of microgrid is obtained via the proposed CSA with minimum COE of 0.03883 $/kWh and LPSP of 0.9574.”

6- The authors should clarify the details of their control method and what is the causes or novelty of the selection to this tool of control.

• Causes of selecting the CSA are mentioned as follows:

In abstract: The CSA is used as it is simple in implementation, it requires few numbers of parameters, and it has high flexibility.

In introduction: As the reader see, great works have been reported in the field of identifying the optimal size of hybrid renewable energy-based system, however the employed metaheuristic optimization approaches still need more enhancement as some algorithms have low convergence rate and may stuck in local optima. Moreover, some works neglected the reliability factors to assess the constructed system. Furthermore, the approaches employed HOMER required excess detailed data and consumed excess computational time. Therefore, the authors considered all these defects and covered the gaps by suggesting simple and flexible approach with fewer controlling parameters named crow search algorithm (CSA) to construct an optimal configuration of hybrid renewable energy-based system with photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generator (DG) in the northeastern region of the Kingdom of Saudi Arabia.

The details of the proposed approach are given in section 4.2.

7. I would also recommend the authors to expand the introduction section to describe the reasoning and motivation behind the application of their research and identify their own scientific contribution and hypothesis more clearly.

- Regarding to the motivations, the following paragraph is added:

“The motivations of the work are constructing a reliable and economic HRES that helps the people of the north of Saudi Arabia to cover their needs in remote areas in the Saudi desert. The reliable configuration is constructed via simple, flexible, and robust proposed approach incorporated CSA. The proposed approach overcomes many defects in the reported methods like complexity in executing and construction and requirement of many parameters defined by the user which may increase the divergence of the algorithm.”

-Regarding to the contribution, the following paragraph is existing at the end of introduction section:

The work contributes by the following items:

• A new approach of crow search algorithm (CSA) is suggested to evaluate the optimal configuration of HRES installed in the northeastern region of the Kingdom of Saudi Arabia.
• Achieving the most economic and efficient use of RESs is selected as the target.
• Comparison to EHO, GOA, HHO, SOA, and SHO is conducted to assess the proposed CSA.
• The robustness, competence, and preference of the proposed CSA are confirmed via the conducted analyses.

8. You should extend the abstract to clear the novelty and the contribution of your work.

The following paragraph are added to the abstract:

“Due to the unpredictable nature of renewable sources like sun and wind, the integration of such sources to the grid becomes complicated. However, hybrid renewable energy system (HRES) can solve the problem. Constructing a reliable HRES in remote areas is essential. Therefore, this paper proposes a new methodology incorporating crow search algorithm (CSA) for optimizing the scale of HRES installed in remote area. The constructed system comprises photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generators (DG), the target is to achieve the most economical and efficient use of renewable energy sources (RESs). The CSA is used as it is simple in implementation, it requires few numbers of parameters, and it has high flexibility.”

9. The reviewer recommend the author to make comparison with the latest method from the literatures

Dear sir, this is already included in the manuscript as EHO has been used in Ref. [37], GOA was presented in [38], and HHO has been employed in [39]. The authors clarified this by the following paragraph:  

In abstract: “Comparison to reported approaches of elephant herding optimizer (EHO), grasshopper optimization algorithm (GOA), and Harris hawks optimizer (HHO) and other programed of seagull optimization algorithm (SOA), spotted hyena optimizer (SHO).”

In results and discussions: “Comparison to elephant herding optimizer (EHO) [37], grasshopper optimization algorithm (GOA) [38], Harris hawks optimizer (HHO) [39], seagull optimization algorithm (SOA), and spotted hyena optimizer (SHO) is performed.”

Author Response File: Author Response.docx

Reviewer 3 Report

 

1. In the abstract, the sentence: “This paper proposes a new methodology incorporated crow search algorithm (CSA) for optimizing the scale of hybrid renewable energy system (HRES).” Is it more suitable to change the word incorporated by “incorporating”.

2. In the abstract, the sentence: “The constructed system comprising photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generator (DG), the target is achieving the most economical and efficient use of renewable energy sources (RESs).” Contains many mistakes it can at least replaced by:

The constructed system comprises photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generators (DG), the target is to achieve the most economical and efficient use of renewable energy sources (RESs).

Overall, many additional efforts should be made to improve the English of the manuscript.

3. In line 159, “there is a short between …”, what do the authors mean by short! The sentence short circuit should be used.

4. In Figure 1. The constructed hybrid renewable energy microgrid, the word “bud” should be replaced by the right one “bus”, in DC bus and AC bus.

5. The authors have dealt with the case of an autonomous hybrid system, to what extent the elaborated sizing remains adequate for the same configuration connected to the electrical grid?

6. In line 314 “4.2. The proposed methodology incorporated CSA” this section title should be reformulated.

7. In the figures 15 and 17 the zooms should be well located in order to make such figures more significant.

8. In the literature review, the authors should criticize the consulted previous works in order to highlight the knowledge gap and high spot their contribution. The authors are requested to consult these recent works which deal with the same theme and which can help them in improving this paper:

 

Eco-feasibility study of a distributed power generation system driven by renewable green energy sources. https://doi.org/10.1080/15567036.2022.2071504.

 

Sizing renewable energy systems with energy storage systems based microgrids for cost minimization using hybrid shuffled frog-leaping and pattern search algorithm. https://doi.org/10.1016/j.scs.2021.103124

 

Improved off-grid wind/photovoltaic/hybrid energy storage system based on new framework of Moth-Flame optimization algorithm. https://doi.org/10.1002/er.7611

 

Energy management and optimized operation of renewable sources and electric vehicles based on microgrid using hybrid gravitational search and pattern search algorithm. https://doi.org/10.1016/j.scs.2021.103279

 

9. The English is not good enough for publication: the manuscript needs extensive revision for language and grammar. 

10. The authors should avoid using very long sentences.

 

Author Response

Reviewer-3: Comments and Suggestions for Authors

1. In the abstract, the sentence: “This paper proposes a new methodology incorporated crow search algorithm (CSA) for optimizing the scale of hybrid renewable energy system (HRES).” Is it more suitable to change the word incorporated by “incorporating”.

It has been changed to “incorporating” in the revised manuscript

2. In the abstract, the sentence: “The constructed system comprising photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generator (DG), the target is achieving the most economical and efficient use of renewable energy sources (RESs).” Contains many mistakes it can at least replaced by:

The constructed system comprises photovoltaic (PV) panels, wind turbines (WTs), batteries, and diesel generators (DG), the target is to achieve the most economical and efficient use of renewable energy sources (RESs).

This comment is considered in the revised manuscript, and the recommended paragraph is written.

Overall, many additional efforts should be made to improve the English of the manuscript.

The manuscript is revised well and all grammar errors and typos are corrected

3. In line 159, “there is a short between …”, what do the authors mean by short! The sentence short circuit should be used.

It has been modified to “this means there is a short circuit between the two ends of the panel”

4. In Figure 1. The constructed hybrid renewable energy microgrid, the word “bud” should be replaced by the right one “bus”, in DC bus and AC bus.

It has been changes in both buses

5. The authors have dealt with the case of an autonomous hybrid system, to what extent the elaborated sizing remains adequate for the same configuration connected to the electrical grid?

Dear sir, the work dealt with off-grid hybrid system that may installed in remote area. While when the grid is considered the configuration of the constructed system becomes different. Also, the analysis will be different as design variables may be changed to new ones. However, the future work will be extended to the area of on-grid connected microgrid with HRES. This is clarified in the conclusion section as follows:

“The future work will be extended to construct the HRES microgrid connected to the electrical grid.”

6. In line 314 “4.2. The proposed methodology incorporated CSA” this section title should be reformulated.

The title is changed to “The proposed CSA-based methodology”

7. In the figures 15 and 17 the zooms should be well located in order to make such figures more significant.

Figures 15 and 17 are redrawn and zoomed sub-figures are included in them

8. In the literature review, the authors should criticize the consulted previous works in order to highlight the knowledge gap and high spot their contribution. The authors are requested to consult these recent works which deal with the same theme and which can help them in improving this paper:

 Eco-feasibility study of a distributed power generation system driven by renewable green energy sources. https://doi.org/10.1080/15567036.2022.2071504.

 Sizing renewable energy systems with energy storage systems based microgrids for cost minimization using hybrid shuffled frog-leaping and pattern search algorithm. https://doi.org/10.1016/j.scs.2021.103124

 Improved off-grid wind/photovoltaic/hybrid energy storage system based on new framework of Moth-Flame optimization algorithm. https://doi.org/10.1002/er.7611

 Energy management and optimized operation of renewable sources and electric vehicles based on microgrid using hybrid gravitational search and pattern search algorithm. https://doi.org/10.1016/j.scs.2021.103279

This comment is considered in the revised manuscript by adding the following paragraph:

“Abbassi et al. [21] introduced a virus colony search algorithm t mitigate the total cost of electricity generated from PV/WT/battery system. Zhao et al. [22] managed the energy of grid-connected microgrid with renewable energy generating units optimally via a hybrid optimizer comprising shuffled frog leaping and pattern search. A modified moth flame optimizer has been used to identify the optimal size of stand-alone renewable energy generation system such that the total cost of electricity is minimized [23]. Moreover, LPSP has been employed to enhance the selected configuration reliability. Li et al. [24] presented a hybrid approach of gravitational search algorithm and pattern search to implement the energy management of renewable energy-based micro grid with plug-in hybrid electric vehicles (PHEVs). Suresh et al. [25] constructed an optimal configuration of wind-PV system with backup battery bank and DG via particle swarm optimizer (PSO) and GA such that the system total cost is mitigated. Bifacial rooftop, floating solar, wind energy system, and solid waste-based waste energy have been evaluated for smart city using adaptive local attractor-based quantum behaved PSO to achieve economic operation of the constructed system [26]. Al-Othman et al. [27] conducting comprehensive review study about artificial intelligence applications in hybrid renewable energy system. Multi-objective evolutionary algorithm with decision-making has been used to establish wind-PV-battery-thermal energy storage system to minimize the net present cost and LPSP [28].”

9. The English is not good enough for publication: the manuscript needs extensive revision for language and grammar.

The manuscript is revised well and all grammar errors and typos are corrected

10. The authors should avoid using very long sentences.

This comment is considered in the revised manuscript

 

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Accept.