Islanded microgrid (MG) is one of the most important challenges in the power system operation as the network can be safe and disconnected from the conjected area. Also, in the case that the market price is high, the islanded MG can have a lower operational cost by islanding from the main grid. However, optimal operation of the islanded MG is very challenging as the MG is a nonlinear problem. Hence, this paper proposed a new heuristic method known as the JAYA optimization algorithm to solve the problem.  Finally, the proposed model is examined on a modified IEEE 30 bus test network to show the merit of the model

Jamaledini, Ashkan

Khazaei, Ehsan

Munich RePEc Personal Archive

Munich Personal RePEc ArchiveOptimal Operation of Islanded MicrogridOperation Based on the JAYAOptimization AlgorithmKhazaei, Ehsan and Jamaledini, AshkanElectrical and Computer Engineering Department, Sazeh SazanPower Company, Iran2 June 2019Online at https://mpra.ub.uni-muenchen.de/94279/MPRA Paper No. 94279, posted 07 Jun 2019 09:09 UTCOptimal Operation of Islanded Microgrid Operation Based on the JAYA Optimization Algorithm  Ehsan Khazaei, Ashkan Jamaledini Electrical and Computer Engineering Department, Sazeh Sazan Power Company, Iran  Abstract: Islanded microgrid (MG) is one of the most important challenges in the power system operation as the network can be safe and disconnected from the conjected area. Also, in the case that the market price is high, the islanded MG can have a lower operational cost by islanding from the main grid. However, optimal operation of the islanded MG is very challenging as the MG is a nonlinear problem. Hence, this paper proposed a new heuristic method known as the JAYA optimization algorithm to solve the problem.  Finally, the proposed model is examined on a modified IEEE 30 bus test network to show the merit of the model.  I. INTRODUCTION  UMMATION of the load and distributed energy resources known as the microgrid (MG) where the generators within a small network should satisfy the demand.  This advantages, can lead to some benefits from both economic and technical perspectives [1-5]. MG has some importance advantages such as closeness to costumers, less transmission lien, higher reliability, higher resiliency, lower operation cost, etc. However, optimal energy management of islanded MG is very complicated. Consequently, this S research proposed a new approach for optimal energy management of islanded MG. That means the small grid is disconnected from the main utility, therefore, the generation units should satisfy the load demand of the small network. Also, in the islanded mode, the MG cannot exchange power with the main grid.  Energy management control of islanded MG is studied in [6], and also a new DC/DC boost converter is developed for islanded MG operation in [7]. Addressing the energy management of islanded MG using evolutionary algorithms, e.g., CDOA, GA, PSO, and TLABO has been investigated in many set of literatures [8-11]. Also, efficient control of MG operation is widely investigated in [12-15]. Utilizing electric vehicles (EVs), MG superconductivity, and MG security are also investigated in [16- 20]. As mentioned, the islanded MG is a nonlinear problem which is hard to solve. Also, the convergence speed is important as well. Therefore, this paper developed a new algorithm which is known as the JAYA optimization algorithm to overcome the complexity of the problem [10].  II. MATHEMATICAL FORMULATIONS OF THE PROBLEM A. Objective function The main objective is to minimize the operational cost as 𝑚𝑖𝑛 ∑ [𝐶𝑖𝑃𝑖𝑡𝐼𝑖𝑡 + 𝑆𝑈𝑖𝑡 + 𝑆𝐷𝑖𝑡]∀𝑖                                                                                                                          (1) I: Binary variable {0,1} SU,SD: Startup and shutdown costs   B. Constraints The proposed problem includes some constraints as follows: Each generation unit has a limited capacity as 𝑃𝑖𝑡,𝑚𝑖𝑛 ≤ 𝑃𝑖𝑡 ≤ 𝑃𝑖𝑡,𝑚𝑎𝑥                                                                                                                        (2)  Each generation unit has a limited ramp up and down as 𝑃𝑖𝑡 − 𝑃𝑖(𝑡−1) ≤ 𝑅𝑈𝑖                                                                                                                           (3) 𝑃𝑖(𝑡−1) − 𝑃𝑖𝑡 ≤ 𝑅𝐷𝑖                                                                                                                            (4) 𝑅𝑈𝑖 , 𝑅𝑈𝑖: Ramp up and ramp down of the ith unit Each generation unit has a limited up and down time as 𝑇(𝑜𝑛)𝑖𝑡 ≥ 𝑈𝑇𝑖(𝐼𝑖𝑡 − 𝐼𝑖(𝑡−1)                                                                                                                 (5) 𝑇(𝑜𝑓𝑓)𝑖𝑡 ≥ 𝐷𝑇𝑖(𝐼𝑖(𝑡−1) − 𝐼𝑖𝑡                                                                                                                (6) 𝑈𝑇𝑖, 𝐷𝑇𝑖: Minimum up and down rates of the ith unit 𝑇(𝑜𝑛), 𝑇(𝑜𝑓𝑓): Number of successive on and off hours                                    III. JAYA ALGORITHM  Islanded MG is a nonlinear optimization problem, which is because of the quadratic objective function (variable times variable). To handle the nonlinearity of the problem, this paper employed the JAYA optimization algorithm [10]. Further explanations of JAYA algorithm are clarified in [10]. General, evolutionary techniques are studied a lot in power system problems because of the fast and precise response [21-24].  IV. RESULTS The IEEE 30 bus test system is tested to prove the merit of the proposed model. However, this model is modified as shown in Fig. 1. Also, the features of the units have been shown in Table I. The day-ahead load demand is shown in Fig. 2.  Fig. 1. Single line model    Table I Features of Units   Minimum output power Maximum output power Unit 1 20 80 Unit 2 20 50 Unit 3 1 25     Fig. 2. Day-ahead (next 24-hour) load demand  DG1DG2DG3The output powers of units have been shown in Fig. 3. As you can see, the cheapest unit is more participated than others; that means economic consideration.   Fig. 3. The output power of Units   The operation cost of the proposed method and it is compared with other well-known models are presented in Table II. Table II Operation cost   Operation cost ($) Computational Time (second)  PSO 5432.1 14.2 GA 5532.5 11.8 Proposed method 5114.7 8.7  V. CONCLUSION A new heuristic method is developed in this paper for the energy management of islanded MG. The results show the fast response and lower operational cost of the proposed method. Furthermore, based on the results, the status of this method is completely different from the well-known methods such as PSO, GA, and TLBO.     Reference [1] Dabbaghjamanesh, M., A. Moeini, M. Ashkaboosi, P. Khazaei, and K. Mirzapalangi. "High Performance Control of Grid Connected Cascaded H-Bridge Active Rectifier Based on Type II-Fuzzy Logic Controller with Low Frequency Modulation Technique." International Journal of Electrical & Computer Engineering (2088-8708) 6, no. 2 (2016). [2] Ashkaboosi, Maryam, Seyed Mehdi Nourani, Peyman Khazaei, Morteza Dabbaghjamanesh, and Amirhossein Moeini. "An optimization technique based on profit of investment and market clearing in wind power systems." American Journal of Electrical and Electronic Engineering 4, no. 3 (2016): 85-91. [3] Zhang, Yan, Fanlin Meng, Rui Wang, Behzad Kazemtabrizi, and Jianmai Shi. "Uncertainty-resistant Stochastic MPC Approach for Optimal Operation of CHP Microgrid." Energy(2019). [4] Chen, Yahong, Changhong Deng, Weiwei Yao, Ning Liang, Pei Xia, Peng Cao, Yiwang Dong et al. "Impacts of stochastic forecast errors of renewable energy generation and load demands on microgrid operation." Renewable Energy 133 (2019): 442-461. [5] Pourbehzadi, Motahareh, Taher Niknam, Jamshid Aghaei, Geev Mokryani, Miadreza Shafie-khah, and João PS Catalão. "Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources: A comprehensive review." International Journal of Electrical Power & Energy Systems 109 (2019): 139-159. [6] Rakhshan, Mohsen, Navid Vafamand, Mokhtar Shasadeghi, Morteza Dabbaghjamanesh, and Amirhossein Moeini. "Design of networked polynomial control systems with random delays: sum of squares approach." International Journal of Automation and Control 10, no. 1 (2016): 73-86. [7] Khazaei, P., S. M. Modares, M. Dabbaghjamanesh, M. Almousa, and A. Moeini. "A high efficiency DC/DC boost converter for photovoltaic applications." International Journal of Soft Computing and Engineering (IJSCE) 6, no. 2 (2016): 2231-2307. [8] Khazaei, Peyman, Morteza Dabbaghjamanesh, Ali Kalantarzadeh, and Hasan Mousavi. "Applying the modified TLBO algorithm to solve the unit commitment problem." In 2016 World Automation Congress (WAC), pp. 1-6. IEEE, 2016. [9] Dabbaghjamanesh, Morteza, Abdollah Kavousi-Fard, and Shahab Mehraeen. "Effective scheduling of reconfigurable microgrids with dynamic thermal line rating." IEEE Transactions on Industrial Electronics 66, no. 2 (2019): 1552-1564. [10] Dabbaghjamanesh, Morteza, Shahab Mehraeen, Abdollah Kavousifard, and Mosayeb Afshari Igder. "Effective scheduling operation of coordinated and uncoordinated wind-hydro and pumped-storage in generation units with modified JAYA algorithm." In 2017 IEEE Industry Applications Society Annual Meeting, pp. 1-8. IEEE, 2017. [11] Dabbaghjamanesh, Morteza, Shahab Mehraeen, Abdollah Kavousi-Fard, and Farzad Ferdowsi. "A New Efficient Stochastic Energy Management Technique for Interconnected AC Microgrids." In 2018 IEEE Power & Energy Society General Meeting (PESGM), pp. 1-5. IEEE, 2018. [12] Tsikalakis, Antonis G., and Nikos D. Hatziargyriou. "Centralized control for optimizing microgrids operation." In 2011 IEEE power and energy society general meeting, pp. 1-8. IEEE, 2011. [13] Dimeas, Aris L., and Nikos D. Hatziargyriou. "Operation of a multiagent system for microgrid control." IEEE Transactions on Power systems 20, no. 3 (2005): 1447-1455. [14] Olivares, Daniel E., Ali Mehrizi-Sani, Amir H. Etemadi, Claudio A. Cañizares, Reza Iravani, Mehrdad Kazerani, Amir H. Hajimiragha et al. "Trends in microgrid control." IEEE Transactions on smart grid 5, no. 4 (2014): 1905-1919. [15] Basak, Prasenjit, A. K. Saha, S. Chowdhury, and S. P. Chowdhury. "Microgrid: Control techniques and modeling." In 2009 44th International Universities Power Engineering Conference (UPEC), pp. 1-5. IEEE, 2009. [16] Taherzadeh, Erfan, Morteza Dabbaghjamanesh, Mohsen Gitizadeh, and Akbar Rahideh. "A new efficient fuel optimization in blended charge depletion/charge sustenance control strategy for plug-in hybrid electric vehicles." IEEE Transactions on Intelligent Vehicles 3, no. 3 (2018): 374-383. [17] Tajalli, Seyede Zahra, Seyed Ali Mohammad Tajalli, Abdollah Kavousi-Fard, Taher Niknam, Morteza Dabbaghjamanesh, and Shahab Mehraeen. "A Secure Distributed Cloud-Fog Based Framework for Economic Operation of Microgrids." In 2019 IEEE Texas Power and Energy Conference (TPEC), pp. 1-6. IEEE, 2019. [18] Dabbaghjamanesh, Morteza. "Stochastic Energy Management of Reconfigurable Power Grids in the Presence of Renewable Energy by Considering Practical Limitations." (2019). [19] Taherzadeh, Erfan, Shahram Javadi, and Morteza Dabbaghjamanesh. "New Optimal Power Management Strategy for Series Plug-In Hybrid Electric Vehicles." International Journal of Automotive Technology 19, no. 6 (2018): 1061-1069. [20] Sayed, Gehad Ismail, Aboul Ella Hassanien, and Ahmad Taher Azar. "Feature selection via a novel chaotic crow search algorithm." Neural Computing and Applications 31, no. 1 (2019): 171-188. [21] Razavi Arab, Azadeh, S. Abbas Haghshenas, and Farzin Samsami. "Sediment transport and morphodynamic changes in Ziarat Estuary and Mond River Delta, the Persian Gulf." In EGU General Assembly Conference Abstracts, vol. 16. 2014. [22] HAGHSHENAS, SEYED ABBAS, and ARAB AZADEH RAZAVI. "APPLICATION OF SEDIMENT CONSTITUENT ANALYSIS FOR CHARACTERIZING LONGSHORE SEDIMENT TRANSPORT, CASE STUDY OF RAMIN PORT-IRANIAN COASTLINE OF THE OMAN SEA." (2014). [23] Arab, Azadeh Razavi, Afshin Danehkar, S. Abbas Haghshenas, and Gita B. Ebrahimi. "ASSESSMENT OF COASTAL DEVELOPMENT IMPACTS ON CORAL ECOSYSTEMS IN NAIBAND BAY, THE PERSIAN GULF." Coastal Engineering Proceedings 1, no. 33 (2012): 31. [24] Haghshenas, S. Abbas, Azadeh Razavi Arab, Arash Bakhtiari, Morteza Jedari Attari, and Michael John Risk. "Decadal Evolution of Mond River Delta, the Persian Gulf." Journal of Coastal Research 75, no. sp1 (2016): 805-810. [25] Kamali, Rahim, Peyman Khazaei, Pouya Banizamani, and Salar Saadatian. "Stochastic Unit Generation Maintenance Scheduling Considering Renewable Energy and Network Constraints." In 2018 World Automation Congress (WAC), pp. 1-6. IEEE, 2018. [26] Kavousi-Fard, Abdollah, Haidar Samet, and Fatemeh Marzbani. "A new hybrid modified firefly algorithm and support vector regression model for accurate short term load forecasting." Expert systems with applications 41, no. 13 (2014): 6047-6056. [27] Dabbaghjamanesh, Morteza, Abdollah Kavousi-Fard, Shahab Mehraeen, Jie Zhang, and Zhao Yang Dong. "Sensitivity Analysis of Renewable Energy Integration on Stochastic Energy Management of Automated Reconfigurable Hybrid AC-DC Microgrid Considering DLR Security Constraint." [28] Azadeh, Razavi Arab, S. Abbas Haghshenas, Farzin Samsami, and Michael John Risk. "Traces of sediment origin in rheological behaviour of mud samples taken from the North-Western Persian Gulf." In BOOK OF ABSTRACTS. 2015. [29] Razavi Arab, Azadeh, S. Abbas Haghshenas, and Homayoun Zaker. "Deep water current velocity data in the Persian Gulf." In EGU General Assembly Conference Abstracts, vol. 17. 2015. [30] Ghaffari, Saeed, and Maryam Ashkaboosi. "Applying Hidden Markov Model Baby Cry Signal Recognition Based on Cybernetic Theory." IJEIR 5: 243-247. [31] Ashkaboosi, Maryam, Farnoosh Ashkaboosi, and Seyed Mehdi Nourani. "The Interaction of Cybernetics and Contemporary Economic Graphic Art as" Interactive Graphics"." (2016). [32] Ghaffari, Saeed, and M. Ashkaboosi. "Applying Hidden Markov M Recognition Based on C." (2016).     

Optimal Operation of Islanded Microgrid Operation Based on the JAYA Optimization Algorithm

Munich Personal RePEc Archive

MPRA
Munich Personal RePEc Archive
Optimal Operation of Islanded Microgrid
Operation Based on the JAYA
Optimization Algorithm
Ehsan Khazaei and Ashkan Jamaledini
Electrical and Computer Engineering Department, Sazeh Sazan
Power Company, Iran
2 June 2019
Online at https://mpra.ub.uni-muenchen.de/94279/
MPRA Paper No. 94279, posted 7 June 2019 09:09 UTC
Optimal Operation of Islanded Microgrid 
Operation Based on the JAYA Optimization 
Algorithm 
 
Ehsan Khazaei, Ashkan Jamaledini 
Electrical and Computer Engineering Department, Sazeh Sazan Power Company, Iran 
 
Abstract: Islanded microgrid (MG) is one of the most important challenges in the power 
system operation as the network can be safe and disconnected from the conjected area. 
Also, in the case that the market price is high, the islanded MG can have a lower 
operational cost by islanding from the main grid. However, optimal operation of the 
islanded MG is very challenging as the MG is a nonlinear problem. Hence, this paper 
proposed a new heuristic method known as the JAYA optimization algorithm to solve the 
problem.  Finally, the proposed model is examined on a modified IEEE 30 bus test 
network to show the merit of the model. 
 
I. INTRODUCTION 
 
UMMATION of the load and distributed energy resources known as the microgrid 
(MG) where the generators within a small network should satisfy the demand.  This 
advantages, can lead to some benefits from both economic and technical perspectives [1-
5]. MG has some importance advantages such as closeness to costumers, less 
transmission lien, higher reliability, higher resiliency, lower operation cost, etc. However, 
optimal energy management of islanded MG is very complicated. Consequently, this 
S 
research proposed a new approach for optimal energy management of islanded MG. That 
means the small grid is disconnected from the main utility, therefore, the generation units 
should satisfy the load demand of the small network. Also, in the islanded mode, the MG 
cannot exchange power with the main grid.  
Energy management control of islanded MG is studied in [6], and also a new DC/DC boost 
converter is developed for islanded MG operation in [7]. Addressing the energy 
management of islanded MG using evolutionary algorithms, e.g., CDOA, GA, PSO, and 
TLABO has been investigated in many set of literatures [8-11]. Also, efficient control of 
MG operation is widely investigated in [12-15]. Utilizing electric vehicles (EVs), MG 
superconductivity, and MG security are also investigated in [16- 20]. As mentioned, the 
islanded MG is a nonlinear problem which is hard to solve. Also, the convergence speed 
is important as well. Therefore, this paper developed a new algorithm which is known as 
the JAYA optimization algorithm to overcome the complexity of the problem [10].  
II. MATHEMATICAL FORMULATIONS OF THE PROBLEM 
A. Objective function 
The main objective is to minimize the operational cost as 
𝑚𝑖𝑛 ∑ [𝐶𝑖𝑃𝑖𝑡𝐼𝑖𝑡 + 𝑆𝑈𝑖𝑡 + 𝑆𝐷𝑖𝑡]∀𝑖                                                                                                                          (1) 
I: Binary variable {0,1} 
SU,SD: Startup and shutdown costs   
B. Constraints 
The proposed problem includes some constraints as follows: 
Each generation unit has a limited capacity as 
𝑃𝑖𝑡,𝑚𝑖𝑛 ≤ 𝑃𝑖𝑡 ≤ 𝑃𝑖𝑡,𝑚𝑎𝑥                                                                                                                        (2) 
 Each generation unit has a limited ramp up and down as 
𝑃𝑖𝑡 − 𝑃𝑖(𝑡−1) ≤ 𝑅𝑈𝑖                                                                                                                           (3) 
𝑃𝑖(𝑡−1) − 𝑃𝑖𝑡 ≤ 𝑅𝐷𝑖                                                                                                                            (4) 
𝑅𝑈𝑖 , 𝑅𝑈𝑖: Ramp up and ramp down of the ith unit 
Each generation unit has a limited up and down time as 
𝑇(𝑜𝑛)𝑖𝑡 ≥ 𝑈𝑇𝑖(𝐼𝑖𝑡 − 𝐼𝑖(𝑡−1)                                                                                                                 (5) 
𝑇(𝑜𝑓𝑓)𝑖𝑡 ≥ 𝐷𝑇𝑖(𝐼𝑖(𝑡−1) − 𝐼𝑖𝑡                                                                                                                (6) 
𝑈𝑇𝑖, 𝐷𝑇𝑖: Minimum up and down rates of the ith unit 
𝑇(𝑜𝑛), 𝑇(𝑜𝑓𝑓): Number of successive on and off hours                                    
III. JAYA ALGORITHM  
Islanded MG is a nonlinear optimization problem, which is because of the quadratic 
objective function (variable times variable). To handle the nonlinearity of the problem, 
this paper employed the JAYA optimization algorithm [10]. Further explanations of JAYA 
algorithm are clarified in [10]. General, evolutionary techniques are studied a lot in power 
system problems because of the fast and precise response [21-24].  
IV. RESULTS 
The IEEE 30 bus test system is tested to prove the merit of the proposed model. 
However, this model is modified as shown in Fig. 1. Also, the features of the units have 
been shown in Table I. The day-ahead load demand is shown in Fig. 2. 
 Fig. 1. Single line model 
 
 
 
Table I 
Features of Units 
 
 Minimum output power Maximum output power 
Unit 1 20 80 
Unit 2 20 50 
Unit 3 1 25 
  
 
 
Fig. 2. Day-ahead (next 24-hour) load demand 
 
DG1
DG2
DG3
The output powers of units have been shown in Fig. 3. As you can see, the cheapest unit 
is more participated than others; that means economic consideration. 
 
 
Fig. 3. The output power of Units 
 
 
The operation cost of the proposed method and it is compared with other well-known 
models are presented in Table II. 
Table II 
Operation cost 
 
 Operation cost ($) Computational Time (second)  
PSO 5432.1 14.2 
GA 5532.5 11.8 
Proposed method 5114.7 8.7 
 
V. CONCLUSION 
A new heuristic method is developed in this paper for the energy management of 
islanded MG. The results show the fast response and lower operational cost of the 
proposed method. Furthermore, based on the results, the status of this method is 
completely different from the well-known methods such as PSO, GA, and TLBO. 
  
 
 
Reference 
[1] Dabbaghjamanesh, M., A. Moeini, M. Ashkaboosi, P. Khazaei, and K. Mirzapalangi. 
"High Performance Control of Grid Connected Cascaded H-Bridge Active Rectifier 
Based on Type II-Fuzzy Logic Controller with Low Frequency Modulation 
Technique." International Journal of Electrical & Computer Engineering (2088-
8708) 6, no. 2 (2016). 
[2] Ashkaboosi, Maryam, Seyed Mehdi Nourani, Peyman Khazaei, Morteza 
Dabbaghjamanesh, and Amirhossein Moeini. "An optimization technique based on 
profit of investment and market clearing in wind power systems." American Journal of 
Electrical and Electronic Engineering 4, no. 3 (2016): 85-91. 
[3] Zhang, Yan, Fanlin Meng, Rui Wang, Behzad Kazemtabrizi, and Jianmai Shi. 
"Uncertainty-resistant Stochastic MPC Approach for Optimal Operation of CHP 
Microgrid." Energy(2019). 
[4] Chen, Yahong, Changhong Deng, Weiwei Yao, Ning Liang, Pei Xia, Peng Cao, 
Yiwang Dong et al. "Impacts of stochastic forecast errors of renewable energy 
generation and load demands on microgrid operation." Renewable Energy 133 
(2019): 442-461. 
[5] Pourbehzadi, Motahareh, Taher Niknam, Jamshid Aghaei, Geev Mokryani, Miadreza 
Shafie-khah, and João PS Catalão. "Optimal operation of hybrid AC/DC microgrids 
under uncertainty of renewable energy resources: A comprehensive 
review." International Journal of Electrical Power & Energy Systems 109 (2019): 139-
159. 
[6] Rakhshan, Mohsen, Navid Vafamand, Mokhtar Shasadeghi, Morteza 
Dabbaghjamanesh, and Amirhossein Moeini. "Design of networked polynomial control 
systems with random delays: sum of squares approach." International Journal of 
Automation and Control 10, no. 1 (2016): 73-86. 
[7] Khazaei, P., S. M. Modares, M. Dabbaghjamanesh, M. Almousa, and A. Moeini. "A 
high efficiency DC/DC boost converter for photovoltaic applications." International 
Journal of Soft Computing and Engineering (IJSCE) 6, no. 2 (2016): 2231-2307. 
[8] Khazaei, Peyman, Morteza Dabbaghjamanesh, Ali Kalantarzadeh, and Hasan 
Mousavi. "Applying the modified TLBO algorithm to solve the unit commitment 
problem." In 2016 World Automation Congress (WAC), pp. 1-6. IEEE, 2016. 
[9] Dabbaghjamanesh, Morteza, Abdollah Kavousi-Fard, and Shahab Mehraeen. 
"Effective scheduling of reconfigurable microgrids with dynamic thermal line 
rating." IEEE Transactions on Industrial Electronics 66, no. 2 (2019): 1552-1564. 
[10] Dabbaghjamanesh, Morteza, Shahab Mehraeen, Abdollah Kavousifard, and 
Mosayeb Afshari Igder. "Effective scheduling operation of coordinated and 
uncoordinated wind-hydro and pumped-storage in generation units with modified 
JAYA algorithm." In 2017 IEEE Industry Applications Society Annual Meeting, pp. 1-
8. IEEE, 2017. 
[11] Dabbaghjamanesh, Morteza, Shahab Mehraeen, Abdollah Kavousi-Fard, and 
Farzad Ferdowsi. "A New Efficient Stochastic Energy Management Technique for 
Interconnected AC Microgrids." In 2018 IEEE Power & Energy Society General 
Meeting (PESGM), pp. 1-5. IEEE, 2018. 
[12] Tsikalakis, Antonis G., and Nikos D. Hatziargyriou. "Centralized control for optimizing 
microgrids operation." In 2011 IEEE power and energy society general meeting, pp. 
1-8. IEEE, 2011. 
[13] Dimeas, Aris L., and Nikos D. Hatziargyriou. "Operation of a multiagent system for 
microgrid control." IEEE Transactions on Power systems 20, no. 3 (2005): 1447-1455. 
[14] Olivares, Daniel E., Ali Mehrizi-Sani, Amir H. Etemadi, Claudio A. Cañizares, Reza 
Iravani, Mehrdad Kazerani, Amir H. Hajimiragha et al. "Trends in microgrid 
control." IEEE Transactions on smart grid 5, no. 4 (2014): 1905-1919. 
[15] Basak, Prasenjit, A. K. Saha, S. Chowdhury, and S. P. Chowdhury. "Microgrid: 
Control techniques and modeling." In 2009 44th International Universities Power 
Engineering Conference (UPEC), pp. 1-5. IEEE, 2009. 
[16] Taherzadeh, Erfan, Morteza Dabbaghjamanesh, Mohsen Gitizadeh, and Akbar 
Rahideh. "A new efficient fuel optimization in blended charge depletion/charge 
sustenance control strategy for plug-in hybrid electric vehicles." IEEE Transactions on 
Intelligent Vehicles 3, no. 3 (2018): 374-383. 
[17] Tajalli, Seyede Zahra, Seyed Ali Mohammad Tajalli, Abdollah Kavousi-Fard, Taher 
Niknam, Morteza Dabbaghjamanesh, and Shahab Mehraeen. "A Secure Distributed 
Cloud-Fog Based Framework for Economic Operation of Microgrids." In 2019 IEEE 
Texas Power and Energy Conference (TPEC), pp. 1-6. IEEE, 2019. 
[18] Dabbaghjamanesh, Morteza. "Stochastic Energy Management of Reconfigurable 
Power Grids in the Presence of Renewable Energy by Considering Practical 
Limitations." (2019). 
[19] Taherzadeh, Erfan, Shahram Javadi, and Morteza Dabbaghjamanesh. "New Optimal 
Power Management Strategy for Series Plug-In Hybrid Electric 
Vehicles." International Journal of Automotive Technology 19, no. 6 (2018): 1061-
1069. 
[20] Sayed, Gehad Ismail, Aboul Ella Hassanien, and Ahmad Taher Azar. "Feature 
selection via a novel chaotic crow search algorithm." Neural Computing and 
Applications 31, no. 1 (2019): 171-188. 
[21] Razavi Arab, Azadeh, S. Abbas Haghshenas, and Farzin Samsami. "Sediment 
transport and morphodynamic changes in Ziarat Estuary and Mond River Delta, the 
Persian Gulf." In EGU General Assembly Conference Abstracts, vol. 16. 2014. 
[22] HAGHSHENAS, SEYED ABBAS, and ARAB AZADEH RAZAVI. "APPLICATION OF 
SEDIMENT CONSTITUENT ANALYSIS FOR CHARACTERIZING LONGSHORE 
SEDIMENT TRANSPORT, CASE STUDY OF RAMIN PORT-IRANIAN COASTLINE 
OF THE OMAN SEA." (2014). 
[23] Arab, Azadeh Razavi, Afshin Danehkar, S. Abbas Haghshenas, and Gita B. 
Ebrahimi. "ASSESSMENT OF COASTAL DEVELOPMENT IMPACTS ON CORAL 
ECOSYSTEMS IN NAIBAND BAY, THE PERSIAN GULF." Coastal Engineering 
Proceedings 1, no. 33 (2012): 31. 
[24] Haghshenas, S. Abbas, Azadeh Razavi Arab, Arash Bakhtiari, Morteza Jedari Attari, 
and Michael John Risk. "Decadal Evolution of Mond River Delta, the Persian 
Gulf." Journal of Coastal Research 75, no. sp1 (2016): 805-810. 
[25] Kamali, Rahim, Peyman Khazaei, Pouya Banizamani, and Salar Saadatian. 
"Stochastic Unit Generation Maintenance Scheduling Considering Renewable Energy 
and Network Constraints." In 2018 World Automation Congress (WAC), pp. 1-6. IEEE, 
2018. 
[26] Kavousi-Fard, Abdollah, Haidar Samet, and Fatemeh Marzbani. "A new hybrid 
modified firefly algorithm and support vector regression model for accurate short term 
load forecasting." Expert systems with applications 41, no. 13 (2014): 6047-6056. 
[27] Dabbaghjamanesh, Morteza, Abdollah Kavousi-Fard, Shahab Mehraeen, Jie Zhang, 
and Zhao Yang Dong. "Sensitivity Analysis of Renewable Energy Integration on 
Stochastic Energy Management of Automated Reconfigurable Hybrid AC-DC 
Microgrid Considering DLR Security Constraint." 
[28] Azadeh, Razavi Arab, S. Abbas Haghshenas, Farzin Samsami, and Michael John 
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Optimal Operation of Islanded Microgrid Operation Based on the JAYA Optimization Algorithm

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