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In this study, optimal allocation and planning of power generation resources as distributed generation with scheduling capability (DGSC) is presented in a smart environment with the objective of reducing losses and considering enhancing the voltage profile is performed using the manta ray foraging optimization (MRFO) algorithm. The DGSC refers to resources that can be scheduled and their generation can be determined based on network requirements. The main purpose of this study is to schedule and intelligent distribution of the DGSCs in the smart and conventional distribution network to enhance its operation. First, allocation of the DGSCs is done based on weighted coefficient method and then the scheduling of the DGSCs is implemented in the 69-bus distribution network. In this study, the effect of smart network by providing real load in minimizing daily energy losses is compared with the network includes conventional load (estimated load as three-level load). The simulation results cleared that optimal allocation and planning of the DGSCs can be improved the distribution network operation with reducing the power losses and also enhancing the voltage profile. The obtained results confirmed superiority of the MRFO compared with well-known particle swarm optimization (PSO) in the DGSCs allocation. The results also showed that increasing the number of DGSCs reduces more losses and improves more the network voltage profile. The achieved results demonstrated that the energy loss in smart network is less than the network with conventional load. In other words, any error in forecasting load demand leads to non-optimal operating point and more energy losses.
Masoud Zahedi Vahid; Ziad M. Ali; Ebrahim Seifi Najmi; Abdollah Ahmadi; Foad H. Gandoman; Shady H. E. Abdel Aleem. Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm. Energies 2021, 14, 4856 .
AMA StyleMasoud Zahedi Vahid, Ziad M. Ali, Ebrahim Seifi Najmi, Abdollah Ahmadi, Foad H. Gandoman, Shady H. E. Abdel Aleem. Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm. Energies. 2021; 14 (16):4856.
Chicago/Turabian StyleMasoud Zahedi Vahid; Ziad M. Ali; Ebrahim Seifi Najmi; Abdollah Ahmadi; Foad H. Gandoman; Shady H. E. Abdel Aleem. 2021. "Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm." Energies 14, no. 16: 4856.
In this paper optimal designing of two hybrid photovoltaic/wind turbine (PV/WT) systems with different storage include battery and hydrogen is presented with objective of minimising cost of energy generation (COEG) and considering reliability constraint as deficit power probability of the system using improved salp swarm optimisation algorithm (ISSOA) for commercial centre area, for Iran country. Different hybrid systems are compared in view of cost and reliability and the optimal size is determined. The results show that the PV/WT with battery storage has lower COEG than PV/WT with hydrogen storage to supply the commercial centre and also its reliability is better than the system integrated with hydrogen. The average cost of per kW of load supply for the PV/WT system with battery and hydrogen storage is 0.216$ and 0.610$, respectively. Superiority of ISSOA is confirmed in comparison with conventional SSOA and particle swarm optimisation in hybrid systems designing.
Masoud Zahedi Vahid; Mohammad Hajivand; Mahmoud Moshkelgosha; Navid Parsa; Hosain Mansoori. Optimal, reliable and economic designing of renewable energy photovoltaic/wind system considering different storage technology using intelligent improved salp swarm optimisation algorithm, commercial application for Iran country. International Journal of Sustainable Energy 2020, 39, 465 -485.
AMA StyleMasoud Zahedi Vahid, Mohammad Hajivand, Mahmoud Moshkelgosha, Navid Parsa, Hosain Mansoori. Optimal, reliable and economic designing of renewable energy photovoltaic/wind system considering different storage technology using intelligent improved salp swarm optimisation algorithm, commercial application for Iran country. International Journal of Sustainable Energy. 2020; 39 (5):465-485.
Chicago/Turabian StyleMasoud Zahedi Vahid; Mohammad Hajivand; Mahmoud Moshkelgosha; Navid Parsa; Hosain Mansoori. 2020. "Optimal, reliable and economic designing of renewable energy photovoltaic/wind system considering different storage technology using intelligent improved salp swarm optimisation algorithm, commercial application for Iran country." International Journal of Sustainable Energy 39, no. 5: 465-485.
This paper presents a novel scheme for comprehensive planning of reliability-centered maintenance (RCM) in the electrical distribution system to minimize the costs of cable repair and maintenance. To this end, a new formulation is proposed by taking into account the maintenance costs for different cases, repairs, repair-caused load projects, and energy purchase or generation costs. To solve the given complex problem, one of the most powerful and newest particle intelligence techniques called GSO algorithm is employed. Simulations are carried out on a 30-bus test network. Moreover, three scenarios and ten cases are applied in the process of extracting results to analyze the impact of various items on parameters of the objective function.
Mohammad Hajivand; Masoud Zahedi Vahid; Farzad Goudarzvand Chegini; Poorya Rahmati-Kahkha; Reza Hajivand. Optimization of Electrical Distribution System Maintenance Process Based on Failure Modes. International Journal of Reliability, Risk and Safety: Theory and Application 2019, 2, 35 -42.
AMA StyleMohammad Hajivand, Masoud Zahedi Vahid, Farzad Goudarzvand Chegini, Poorya Rahmati-Kahkha, Reza Hajivand. Optimization of Electrical Distribution System Maintenance Process Based on Failure Modes. International Journal of Reliability, Risk and Safety: Theory and Application. 2019; 2 (1):35-42.
Chicago/Turabian StyleMohammad Hajivand; Masoud Zahedi Vahid; Farzad Goudarzvand Chegini; Poorya Rahmati-Kahkha; Reza Hajivand. 2019. "Optimization of Electrical Distribution System Maintenance Process Based on Failure Modes." International Journal of Reliability, Risk and Safety: Theory and Application 2, no. 1: 35-42.
In this paper, an optimal, reliable, and cost-effective framework for designing a renewable hybrid photovoltaic-wind-battery system is presented to minimize the total net present cost (TNPC) and to consider reliability constraint as loss of load probability (LPP) for the city of Ahvaz, Iran, considering the components outage rate (COR). The decision variables include the number of photovoltaic panels, wind turbines, batteries, and the angle of the photovoltaic panel optimized by the grey wolf optimizer (GWO) algorithm. The performance of the proposed method is compared with the particle swarm optimization (PSO) method. The results of a system designed in different combinations with and without considering COR are evaluated. The simulation results confirm that the GWO algorithm is superior to the PSO method by yielding lower TNPC (1.199 M$ for GWO and 1.201 M$ for PSO) and better LPP (0.653% for GWO and 0.655% for PSO) for optimal combination (photovoltaic-battery system). The results also showed that a photovoltaic-wind combination is not the most cost-effective and reliable for the Ahvaz region, and the implementation of hybrid systems based on wind power is not cost-effective in this region. In addition, the results showed that considering COR gives the designers of these systems a more accurate view of the cost and reliability. Moreover, considering COR increases the cost of load supply and undermines the load reliability.
Amirreza Naderipour; Zulkurnain Abdul-Malek; Masoud Zahedi Vahid; Zahra Mirzaei Seifabad; Mohammad Hajivand; Saber Arabi Nowdeh. Optimal, Reliable and Cost-Effective Framework of Photovoltaic-Wind-Battery Energy System Design Considering Outage Concept Using Grey Wolf Optimizer Algorithm—Case Study for Iran. IEEE Access 2019, 7, 182611 -182623.
AMA StyleAmirreza Naderipour, Zulkurnain Abdul-Malek, Masoud Zahedi Vahid, Zahra Mirzaei Seifabad, Mohammad Hajivand, Saber Arabi Nowdeh. Optimal, Reliable and Cost-Effective Framework of Photovoltaic-Wind-Battery Energy System Design Considering Outage Concept Using Grey Wolf Optimizer Algorithm—Case Study for Iran. IEEE Access. 2019; 7 (99):182611-182623.
Chicago/Turabian StyleAmirreza Naderipour; Zulkurnain Abdul-Malek; Masoud Zahedi Vahid; Zahra Mirzaei Seifabad; Mohammad Hajivand; Saber Arabi Nowdeh. 2019. "Optimal, Reliable and Cost-Effective Framework of Photovoltaic-Wind-Battery Energy System Design Considering Outage Concept Using Grey Wolf Optimizer Algorithm—Case Study for Iran." IEEE Access 7, no. 99: 182611-182623.
Masoud Zahedi Vahid; Mahmoud Oukati Sadegh. An intelligent method to reduce losses in distribution networks using self-adaptive harmony search algorithm. Journal of Intelligent & Fuzzy Systems 2016, 30, 1393 -1402.
AMA StyleMasoud Zahedi Vahid, Mahmoud Oukati Sadegh. An intelligent method to reduce losses in distribution networks using self-adaptive harmony search algorithm. Journal of Intelligent & Fuzzy Systems. 2016; 30 (3):1393-1402.
Chicago/Turabian StyleMasoud Zahedi Vahid; Mahmoud Oukati Sadegh. 2016. "An intelligent method to reduce losses in distribution networks using self-adaptive harmony search algorithm." Journal of Intelligent & Fuzzy Systems 30, no. 3: 1393-1402.
Loss reduction planning is considered one of the most significant and sensitive distribution system designing studies. The planning process to reduce losses along with distributed generation sources results in a non-convex, non-linear optimization problem, mixed with integer variables, which requires complicated calculations. To solve this problem, evolutionary optimization algorithms can be used. In the present paper, loss reduction is carried out by reconfiguration the network in the light of distributed generation sources, and as a solution, a new set of harmony search algorithms, called self-adaptive algorithms are used. To verify the efficiency of the algorithm the results have been analyzed in the IEEE standard system. The findings show the strength and efficiency of this algorithm in comparison to other optimization algorithms.
Masoud Zahedi Vahid; Mahmoud Oukati Sadegh. A new method to reduce losses in distribution networks using system reconfiguration with distributed generations using self-adaptive harmony search algorithm. 2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) 2015, 1 -5.
AMA StyleMasoud Zahedi Vahid, Mahmoud Oukati Sadegh. A new method to reduce losses in distribution networks using system reconfiguration with distributed generations using self-adaptive harmony search algorithm. 2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS). 2015; ():1-5.
Chicago/Turabian StyleMasoud Zahedi Vahid; Mahmoud Oukati Sadegh. 2015. "A new method to reduce losses in distribution networks using system reconfiguration with distributed generations using self-adaptive harmony search algorithm." 2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) , no. : 1-5.