Sustainable Energy Management and Control for Variable Load Conditions Using Improved Mayfly Optimization

Round 1

Reviewer 1 Report

This paper develops a hybrid renewable energy system by combining photovoltaic and wind energy, a battery pack and a variable load. An optimization algorithm is adopted to improve the system performance. In general, this is an interesting paper and the authors are advised to address the following issues before this manuscript can be accepted:

 

1. In the present study, the SOC is defined based on power while the conventional SOC estimation studies generally adopt a current based definition (see State-of-charge estimation of LiFePO4 batteries in electric vehicles: A deep-learning enabled approach). In this regard, the authors are advised to clarify this issue before defining battery SOC.
2. Besides, SOC(t) instead of SOC should appear on the left side of the equations.
3. The efficiencies should be given in tables 1~3.
4. The proposed model is displayed in figure 4 using Matlab Simulink. The authors are advised to add more discussions about the figure or change it to a general plot.
5. Do the authors consider the issue of battery degradation when designing the system?

Author Response

 

1. In the present study, the SOC is defined based on power while the conventional SOC estimation studies generally adopt a current based definition (see State-of-charge estimation of LiFePO4 batteries in electric vehicles: A deep-learning enabled approach). In this regard, the authors are advised to clarify this issue before defining battery SOC.

 

Answer:

Thank you for your useful comment.

Two semi-direct current and voltage estimation techniques are used determining SOC that are simple and inexpensive to apply. As a result, one or both of them are frequently used in practical applications. Unfortunately, since none of these processes is accurate enough, other approaches must be utilized to enhance them. Because the battery SOC is a critical quantity that indicates battery performance, accurate SOC estimation not only protects the battery and prevents overcharging or discharging, but also extends its life. As a result, the ageing cycle procedure is used to examine SOC in terms of power value.

The above information is updated at beginning of section 5.3.

 

1. Besides, SOC (t) instead of SOC should appear on the left side of the equations.

 

Answer:

Thank you for your important comment. As per the reviewer’s comment, we have changed SOC (t) instead of SOC in left side of the equations (13) & (14) at section 5.3.

 

 

1. The efficiencies should be given in tables 1~3.

 

Answer:

Thank you for your useful comment. As per the reviewer’s comment, we have included the efficiencies at table 1, 2 and 3.

 

1. The proposed model is displayed in figure 4 using Matlab Simulink. The authors are advised to add more discussions about the figure or change it to a general plot.

 

Answer:

Thank you for your important comment. As per the reviewer’s comment, we have included brief discussion about the Simulink model (figure 4) at section 7.

 

1. Do the authors consider the issue of battery degradation when designing the system?

 

Answer:

Thank you for your valuable comment.

Yes, the authors consider the issue of battery degradation when designing the system. Because, it is not easy to facilitate the roles of battery without understanding the characteristics which controls charging and discharging power. To set an appropriate management strategy, the technical performance of battery must be evaluated considering forecasting errors that occurred by changes of the customer’s load and intermittent characteristics of renewable energy and battery degradation. Among system-perspective studies, we consider the impact of the battery degradation to the system which is caused by the accumulation of charging and discharging cycles. The brief explanation for this comment is described at the end of section 5.3.

Reviewer 2 Report

Subramani et al. have demonstrated the design of a method of energy management and control using improved mayfly optimization. This method is designed for a hybrid renewable energy system combining various energy sources. Numerical simulations in Simulink are used to evaluate the performance. Several parameters are evaluated such as grid voltage, total harmonic distortion and so on.  The simulated results show that the proposed IMO-MP&O achieves better performance than current controls. Overall, this paper is clearly written, with claims mostly supported. I would thus recommend the acceptance of this paper, if the following questions are addressed.

 

1. The authors spend almost half of the content on background information. Can this be reorganized? Including but not limited to: the model of PV does not need to be discussed for 1 page, and the mayfly optimization algorithm can be introduced more concisely.
2. In page 12, line 456, the authors mentioned that “The proposed IMO-MP&O is calculated through three combined methods including MO-P&O, MO-MP&O and IMO-P&O.” Following this statement, the comparisons among these 4 methods are plotted. How is the proposed IMO-MP&O calculated through the other 3 method? What’s the mathematically prediction and does it match the results plotted? 
3. In this research, the hybrid energy system is a PV+wind system. Does this method apply to other hybrid systems? 
4. In the title, the authors mentioned “variable load conditions”. But it’s not further studied in the paper. Does the load conditions affect the performance of the proposed method?

Author Response

Reviewer 2:

1. The authors spend almost half of the content on background information. Can this be reorganized? Including but not limited to: the model of PV does not need to be discussed for 1 page, and the mayfly optimization algorithm can be introduced more concisely.

 

Answer:

Thank you for your important comment. As per the reviewer’s comment, we have limited the content for PV model at section 5.1. Furthermore, we have briefly introduced the mayfly optimization algorithm at Introduction part as well as section 6.1.

 

 

1. In page 12, line 456, the authors mentioned that “The proposed IMO-MP&O is calculated through three combined methods including MO-P&O, MO-MP&O and IMO-P&O.” Following this statement, the comparisons among these 4 methods are plotted. How is the proposed IMO-MP&O calculated through the other 3 method? What’s the mathematically prediction and does it match the results plotted? 

 

Answer:

Thank you for your valuable comment. According to the reviewer’s comment, the comparisons among these 4 combinations are plotted for all the performance metrics from section 7.1.1 to 7.1.5. The proposed IMO-MP&O is compared with three combinations such as MO-P&O, MO-MP&O and IMO-P&O. Because, MO and P&O are conventional methods, so, by merging these two methods with different combinations, proposed IMO-MP&O is executed and analyzed in the section 7. The Mathematical model for MO, IMO, P&O and MP&O are stated at section 6.1, 6.2 and 6.3 respectively.

The above information is updated at the beginning of section 7.1.

 

1. In this research, the hybrid energy system is a PV+Wind system. Does this method apply to other hybrid systems? 

 

Answer:

Thank you for your useful comment. Yes, this method is applicable for other hybrid system also.

 

 

1. In the title, the authors mentioned “variable load conditions”. But it’s not further studied in the paper. Does the load conditions affect the performance of the proposed method?

 

Answer:

Thank you for your useful comment.

There is no issue with the supplied power under variable load conditions. As load conditions change, power is delivered from hybrid sources. The excess power from the sources are stored in backup batteries; sometimes power from batteries are supplied to other small loads under variable load conditions. Therefore, load conditions does not affect the performance of the proposed method.

The above information is updated at section 7.2.

Author Response File: Author Response.docx