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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.
The main goal of generation expansion planning (GEP) and transmission expansion planning (TEP) is to expand the power system to satisfy the increasing demand of electricity while maintaining efficient operation of the system. The major objective of this study is to propose a dynamic, robust GEP–TEP expansion planning in the presence of wind farms considering both long- and short-term uncertainties. The suggested model allows implementing information-gap decision theory on multi-year long-term uncertainties, such as demand growth and future increase in production capacity to decrease the risk in long-term decisions. Additionally, a scenario-based approach is employed for short-term uncertainties in demand and wind power production in a 1-year time horizon. The main advantage of the proposed model is to enhance the power system robustness against the uncertainties corresponding to forecast errors. To verify the robustness of the suggested expansion planning model, it is applied to the Garver 6-bus and IEEE 24-bus test systems.
Saeid Ahmadi; Hani Mavalizadeh; Ali Asghar Ghadimi; Mohammad Reza Miveh; Abdollah Ahmadi. Dynamic robust generation–transmission expansion planning in the presence of wind farms under long‐ and short‐term uncertainties. IET Generation, Transmission & Distribution 2020, 14, 5418 -5427.
AMA StyleSaeid Ahmadi, Hani Mavalizadeh, Ali Asghar Ghadimi, Mohammad Reza Miveh, Abdollah Ahmadi. Dynamic robust generation–transmission expansion planning in the presence of wind farms under long‐ and short‐term uncertainties. IET Generation, Transmission & Distribution. 2020; 14 (23):5418-5427.
Chicago/Turabian StyleSaeid Ahmadi; Hani Mavalizadeh; Ali Asghar Ghadimi; Mohammad Reza Miveh; Abdollah Ahmadi. 2020. "Dynamic robust generation–transmission expansion planning in the presence of wind farms under long‐ and short‐term uncertainties." IET Generation, Transmission & Distribution 14, no. 23: 5418-5427.
This study deals with multiobjective reactive power planning, considering the uncertainties of load demand and wind power generation. The main feature of the current study is to examine the impact of multiple uncertainties on Reactive Power Planning (RPP), while several objectives exist. To fulfill this goal, the Information Gap Decision Theory (IGDT) is used to handle the uncertainties of load demand and wind power production. In order to cope with the probabilistic optimal RPP problem and to create Pareto optimal solutions, the ε-Constraint method is utilized. Fuzzy Decision Maker (FDM) and min-max approach are jointly applied to find the Best Compromise Solution (BCS). To evaluate the efficiency and the proficiency of the proposed multiobjective RPP model, it is implemented on the IEEE-30 bus test system via the GAMS software environment. To prove the superiority of the proposed model, the obtained results are compared with the scenario-based approach. The results imply that for specific amounts of uncertainty, the IGDT method performs reasonably towards the scenario-based approach.
Amir Hossein Shojaei; Ali Asghar Ghadimi; Mohammad Reza Miveh; Foad H. Gandoman; Abdollah Ahmadi. Multiobjective reactive power planning considering the uncertainties of wind farms and loads using Information Gap Decision Theory. Renewable Energy 2020, 163, 1427 -1443.
AMA StyleAmir Hossein Shojaei, Ali Asghar Ghadimi, Mohammad Reza Miveh, Foad H. Gandoman, Abdollah Ahmadi. Multiobjective reactive power planning considering the uncertainties of wind farms and loads using Information Gap Decision Theory. Renewable Energy. 2020; 163 ():1427-1443.
Chicago/Turabian StyleAmir Hossein Shojaei; Ali Asghar Ghadimi; Mohammad Reza Miveh; Foad H. Gandoman; Abdollah Ahmadi. 2020. "Multiobjective reactive power planning considering the uncertainties of wind farms and loads using Information Gap Decision Theory." Renewable Energy 163, no. : 1427-1443.
This paper presents the application of information gap decision theory (IGDT) to deal with uncertainties associated with load forecasting in dynamic, environment constrained, coordinated generation and transmission expansion planning. Traditionally, the gaseous emissions are constrained over the whole system. Conventional methods cannot guarantee a practical expansion plan since huge emissions can still occur on some buses in the power system. This paper introduces a per-bus emission limit to avoid extreme emissions in highly populated areas. The effect of nodal emission limits is fully discussed and compared to a conventional method. The model is kept linear using the big M approach to decrease the model computational burden. Reliability is considered by limiting the estimated load not served in each year over the planning horizon. The cost of fuel transportation and fuel limits are considered in order to make the model more realistic and practical. The effectiveness of the proposed model is verified by implementation on Garver 6 bus, IEEE 30 bus, and 118 bus test systems.
Abdollah Ahmadi; Hani Mavalizadeh; Ali Esmaeel Nezhad; Pierluigi Siano; Heidar Ali Shayanfar; Branislav Hredzak. A robust model for generation and transmission expansion planning with emission constraints. SIMULATION 2020, 96, 605 -621.
AMA StyleAbdollah Ahmadi, Hani Mavalizadeh, Ali Esmaeel Nezhad, Pierluigi Siano, Heidar Ali Shayanfar, Branislav Hredzak. A robust model for generation and transmission expansion planning with emission constraints. SIMULATION. 2020; 96 (7):605-621.
Chicago/Turabian StyleAbdollah Ahmadi; Hani Mavalizadeh; Ali Esmaeel Nezhad; Pierluigi Siano; Heidar Ali Shayanfar; Branislav Hredzak. 2020. "A robust model for generation and transmission expansion planning with emission constraints." SIMULATION 96, no. 7: 605-621.
Current power networks and consumers are undergoing a fundamental shift in the way traditional energy systems were designed and managed. The bidirectional peer-to-peer (P–P) energy transactions pushed passive consumers to be prosumers. The future smart grid or the internet of energy (IoE) will facilitate the coordination of all types of prosumers to form virtual power plants (VPP). The paper aims to contribute to this growing area of research by accumulating and summarizing the significant ideas of the integration of distributed prosumers and small-scale VPP to the internet of energy (IoE). The study also reports the characteristics of IoE in comparison to the traditional grid and offers some valuable insights into the control, management and optimization strategies of prosumers, distributed energy resources (DERs) and VPP. As bidirectional P–P energy transaction by the prosumers is a crucial element of IoE, their management strategies including various demand-response approach at the customers’-levels are systematically summarized. The integration of DERs and prosumers to the VPP considering their functions, infrastructure, type, control objectives are also reviewed and summarized. Various optimization techniques and algorithm, and their objectives functions and the types of mathematical formulation that are used to manage the DERs and VPP are discussed and categorized systematically. Finally, the factors which affect the integration of DERs and prosumers to the VPP are identified.
Khizir Mahmud; Behram Khan; Jayashri Ravishankar; Abdollah Ahmadi; Pierluigi Siano. An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview. Renewable and Sustainable Energy Reviews 2020, 127, 109840 .
AMA StyleKhizir Mahmud, Behram Khan, Jayashri Ravishankar, Abdollah Ahmadi, Pierluigi Siano. An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview. Renewable and Sustainable Energy Reviews. 2020; 127 ():109840.
Chicago/Turabian StyleKhizir Mahmud; Behram Khan; Jayashri Ravishankar; Abdollah Ahmadi; Pierluigi Siano. 2020. "An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview." Renewable and Sustainable Energy Reviews 127, no. : 109840.
Wind energy is one of the most important sources of energy in the world. In recent decades, wind as one of the massive marine energy resources in the ocean to produce electricity has been used. This chapter introduces a comprehensive overview of the efficient ocean wind energy technologies, and the global wind energies in both offshore and onshore sides are discussed. Also, the classification of global ocean wind energy resources is presented. Moreover, different components of a wind farm offshore as well as the technologies used in them are investigated. Possible layouts regarding the foundation of an offshore wind turbine, floating offshore, as well as the operation of wind farms in the shallow and deep location of the ocean are studied. Finally, the offshore wind power plant challenges are described.
Foad H. Gandoman; Abdollah Ahmadi; Shady H.E. Abdel Aleem; Masoud Ardeshiri; Ali Esmaeel Nezhad; Joeri Van Mierlo; Maitane Berecibar. Ocean Wind Energy Technologies in Modern Electric Networks: Opportunity and Challenges. Advances in Modelling and Control of Wind and Hydrogenerators 2020, 1 .
AMA StyleFoad H. Gandoman, Abdollah Ahmadi, Shady H.E. Abdel Aleem, Masoud Ardeshiri, Ali Esmaeel Nezhad, Joeri Van Mierlo, Maitane Berecibar. Ocean Wind Energy Technologies in Modern Electric Networks: Opportunity and Challenges. Advances in Modelling and Control of Wind and Hydrogenerators. 2020; ():1.
Chicago/Turabian StyleFoad H. Gandoman; Abdollah Ahmadi; Shady H.E. Abdel Aleem; Masoud Ardeshiri; Ali Esmaeel Nezhad; Joeri Van Mierlo; Maitane Berecibar. 2020. "Ocean Wind Energy Technologies in Modern Electric Networks: Opportunity and Challenges." Advances in Modelling and Control of Wind and Hydrogenerators , no. : 1.
With the growing use of motorized loads, light bulbs, and solar cells, the use of electrical equipment with nonlinear behavior increases the harmonic level of currents and voltages in electrical distribution networks. As a result, analysis of distorted harmonic systems and calculation of overpaying on bills (penalties) due to harmonics consequences play an essential role in controlling harmonics and reactive power compensation in electric distribution networks. Meanwhile, providing a model to calculate the penalty due to harmonics has recently been investigated by many electric companies. The main aim of this work is to provide a decision tool to allow economic assessment of harmonics and its consequences in power systems from a financial point of view supported by a distribution company insight. In this regard, this paper presents a simple model to calculate the rate of the penalty of customers in the presence of harmonic-polluted loads to encourage more efficient use of the power system. One of Sanandaj's commercial projects has been selected as a case study to evaluate the effectiveness of the proposed model. The results obtained show that the presented model calculates and evaluates the problems caused by the existence of harmonics in the studied cases effectively.
Foad H. Gandoman; Shady H.E. Abdel Aleem; Francisco Jurado; Ziad Ali; Abdollah Ahmadi; Kaveh Shamkhani. A methodology for imposing harmonic distortion's penalty in customers bill. Electric Power Systems Research 2020, 183, 106268 .
AMA StyleFoad H. Gandoman, Shady H.E. Abdel Aleem, Francisco Jurado, Ziad Ali, Abdollah Ahmadi, Kaveh Shamkhani. A methodology for imposing harmonic distortion's penalty in customers bill. Electric Power Systems Research. 2020; 183 ():106268.
Chicago/Turabian StyleFoad H. Gandoman; Shady H.E. Abdel Aleem; Francisco Jurado; Ziad Ali; Abdollah Ahmadi; Kaveh Shamkhani. 2020. "A methodology for imposing harmonic distortion's penalty in customers bill." Electric Power Systems Research 183, no. : 106268.
This article proposed a new model for reconfiguration and distributed generation (DG) allocation in the distribution network by considering network loss reduction and power quality improvement. The objective function aims to minimize losses and improve power quality indices by using the new antlion optimizer (ALO) algorithm. The proposed reconfiguration has been investigated on an unbalanced IEEE 33-bus grid with and without DG resources and capacitors. In this study, a branch exchange technique with an optimization method is used to determine the best network arrangement. Simulation results are implemented in different scenarios. In each of the scenarios, power quality indices and network losses before and after the optimization are compared. The results indicate that by using the proposed method, the rate of power quality indices and the losses in the case study are reduced. Also, the results of this study were compared with the results of sample studies. The results show that ALO has better performance with the goal of power loss reduction.
Mohammad Jafar Hadidian Moghaddam; Akhtar Kalam; Juan Shi; Saber Arabi Nowdeh; Foad Heidari Gandoman; Abdollah Ahmadi. A New Model for Reconfiguration and Distributed Generation Allocation in Distribution Network Considering Power Quality Indices and Network Losses. IEEE Systems Journal 2020, 14, 3530 -3538.
AMA StyleMohammad Jafar Hadidian Moghaddam, Akhtar Kalam, Juan Shi, Saber Arabi Nowdeh, Foad Heidari Gandoman, Abdollah Ahmadi. A New Model for Reconfiguration and Distributed Generation Allocation in Distribution Network Considering Power Quality Indices and Network Losses. IEEE Systems Journal. 2020; 14 (3):3530-3538.
Chicago/Turabian StyleMohammad Jafar Hadidian Moghaddam; Akhtar Kalam; Juan Shi; Saber Arabi Nowdeh; Foad Heidari Gandoman; Abdollah Ahmadi. 2020. "A New Model for Reconfiguration and Distributed Generation Allocation in Distribution Network Considering Power Quality Indices and Network Losses." IEEE Systems Journal 14, no. 3: 3530-3538.
Abdollah Ahmadi; Ahmad Tavakoli; Pouya Jamborsalamati; Navid Rezaei; Mohammad Reza Miveh; Foad Heidari Gandoman; Alireza Heidari; Ali Esmaeel Nezhad. Power quality improvement in smart grids using electric vehicles: a review. IET Electrical Systems in Transportation 2019, 9, 53 -64.
AMA StyleAbdollah Ahmadi, Ahmad Tavakoli, Pouya Jamborsalamati, Navid Rezaei, Mohammad Reza Miveh, Foad Heidari Gandoman, Alireza Heidari, Ali Esmaeel Nezhad. Power quality improvement in smart grids using electric vehicles: a review. IET Electrical Systems in Transportation. 2019; 9 (2):53-64.
Chicago/Turabian StyleAbdollah Ahmadi; Ahmad Tavakoli; Pouya Jamborsalamati; Navid Rezaei; Mohammad Reza Miveh; Foad Heidari Gandoman; Alireza Heidari; Ali Esmaeel Nezhad. 2019. "Power quality improvement in smart grids using electric vehicles: a review." IET Electrical Systems in Transportation 9, no. 2: 53-64.
This paper presents a new framework, utilizing Information-Gap Decision Theory (IGDT), for multi-objective Robust Security-Constrained Unit Commitment (RSCUC) of generating units in the presence of wind farms and gridable vehicles. Both the wind power and load demand uncertainties are considered, and modeled using a bi-objective model. As the main advantage, the framework enables the system operator to take an appropriate operational decision with respect to the extremity of each uncertainty. The proposed problem is solved using Normal Boundary Intersection (NBI) technique. Subsequently, VIKOR, a decision-making tool, is utilized to choose the best Pareto optimal solution. Finally, the IGDT based framework presented in this paper is validated using a 6-bus test system, the IEEE Reliability Test System (RTS) with 24 buses and the IEEE 118-bus system.
Abdollah Ahmadi; Ali Esmaeel Nezhad; Pierluigi Siano; Branislav Hredzak; Sajeeb Saha. Information-Gap Decision Theory for Robust Security-Constrained Unit Commitment of Joint Renewable Energy and Gridable Vehicles. IEEE Transactions on Industrial Informatics 2019, 16, 3064 -3075.
AMA StyleAbdollah Ahmadi, Ali Esmaeel Nezhad, Pierluigi Siano, Branislav Hredzak, Sajeeb Saha. Information-Gap Decision Theory for Robust Security-Constrained Unit Commitment of Joint Renewable Energy and Gridable Vehicles. IEEE Transactions on Industrial Informatics. 2019; 16 (5):3064-3075.
Chicago/Turabian StyleAbdollah Ahmadi; Ali Esmaeel Nezhad; Pierluigi Siano; Branislav Hredzak; Sajeeb Saha. 2019. "Information-Gap Decision Theory for Robust Security-Constrained Unit Commitment of Joint Renewable Energy and Gridable Vehicles." IEEE Transactions on Industrial Informatics 16, no. 5: 3064-3075.
A multi-objective wind farm integration framework is proposed in this paper which considers the composite generation and reliability assessment and annualized operating and investment cost evaluation. An emission-controlled policy is adopted such that the amount of SOx and NOx decreases in line with renewable resource planning. Since the incorporation of large-scale distant wind farms is a problem of the multi-objective mixed-integer type with nonlinearities and non-convexities, this paper utilizes a fast elicit multi-objective Non-dominated Sorting Genetic Algorithm II (NSGA II) by probabilistic indices. It is noted that the impacts of the unavailability of the transmission system are modeled employing DC Optimal Power Flow (OPF) based on the incidence matrix together with the static security evaluation. Furthermore, in order to assess the performance of the suggested approach, the model is implemented on the Roy Billinton Test System (RBTS). Afterwards, distant wind farms integration into Iran's South-West Regional Grid (ISWRG) is studied.
Mohammad Sadegh Javadi; Seyed-Ehsan Razavi; Abdollah Ahmadi; Pierluigi Siano. A novel approach for distant wind farm interconnection: Iran South-West wind farms integration. Renewable Energy 2019, 140, 737 -750.
AMA StyleMohammad Sadegh Javadi, Seyed-Ehsan Razavi, Abdollah Ahmadi, Pierluigi Siano. A novel approach for distant wind farm interconnection: Iran South-West wind farms integration. Renewable Energy. 2019; 140 ():737-750.
Chicago/Turabian StyleMohammad Sadegh Javadi; Seyed-Ehsan Razavi; Abdollah Ahmadi; Pierluigi Siano. 2019. "A novel approach for distant wind farm interconnection: Iran South-West wind farms integration." Renewable Energy 140, no. : 737-750.
One of methods for loss reduction and reliability improvement of radial distribution system is using of renewable energy generation. In this paper, a new optimal placement and sizing of renewable energy sources based on photovoltaic panels (PVs) and wind turbines (WTs) in the distribution network is presented with the objective of loss reduction and reliability improvement based on energy not-supplied (ENS). A multi-objective evolutionary algorithm based on fuzzy decision-making method, called the Multi-Objective Hybrid Teaching–Learning Based Optimization-Grey Wolf Optimizer (MOHTLBOGWO) is proposed to solve the optimization problem. The proposed hybrid method has a high convergence speed and not trapped at all in local optimal. The proposed method is implemented in the form of single-objective and multi-objective on 33 and 69 bus IEEE radial distribution networks. The simulation results clear that the multi-objective optimization is a more precise approach to network utilization taking into account all objective indices than the single objective method. The results show that the proposed method has better convergence speed and less convergence tolerance in achieving to best solution in comparison with TLBO and GWO methods in loss reduction, reliability improvement and increasing the net saving and also in comparison with last studies. Moreover, the results show that dispersion of the size and location of distributed renewable generation leads to a further reduction in losses and a better improvement of the reliability criterion.
S. Arabi Nowdeh; I. Faraji Davoudkhani; M.J. Hadidian Moghaddam; E. Seifi Najmi; A.Y. Abdelaziz; A. Ahmadi; S.E. Razavi; F.H. Gandoman. Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Applied Soft Computing 2019, 77, 761 -779.
AMA StyleS. Arabi Nowdeh, I. Faraji Davoudkhani, M.J. Hadidian Moghaddam, E. Seifi Najmi, A.Y. Abdelaziz, A. Ahmadi, S.E. Razavi, F.H. Gandoman. Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Applied Soft Computing. 2019; 77 ():761-779.
Chicago/Turabian StyleS. Arabi Nowdeh; I. Faraji Davoudkhani; M.J. Hadidian Moghaddam; E. Seifi Najmi; A.Y. Abdelaziz; A. Ahmadi; S.E. Razavi; F.H. Gandoman. 2019. "Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method." Applied Soft Computing 77, no. : 761-779.
In this chapter, some common methods of maximum power point tracking (MPPT) of the photovoltaic system such as perturb and observe, particle swarm optimization and grey wolf optimizer are described to solve the MPPT problem. Also, a novel method is proposed for MPPT of PV system titled secant incremental gradient based on Newton Raphson (SIGBNR) method. SIGBNR uses the chord slope passing through two points of the function instead of using the explicit derivative of the function, which is equal to tangent line tilt of the function. In addition to high convergence speed, the proposed method requires less computation and also has a higher accuracy in the number of repetitions when it solves MPPT problems. The results arising from the proposed method are compared and analyzed with the other methods to evaluate its performance for solving MPPT problem. The proficiency of the methods is investigated in different scenarios of partial shading condition and compared in view of various features especially efficiency and convergence velocity. The results showed that the proposed method has better performance in achieving to global maximum power point with more tracking efficiency and convergence speed than the other methods. Also, superior capabilities of the proposed method are demonstrated.
Saber Arabi Nowdeh; Mohammad Jafar Hadidian Moghaddam; Manoochehr Babanezhad; Iraj Faraji Davoodkhani; Akhtar Kalam; Abdollah Ahmadi; Almoataz Y. Abdelaziz. A Novel Maximum Power Point Tracking Method for Photovoltaic Application Using Secant Incremental Gradient Based on Newton Raphson. Numerical Methods for Energy Applications 2019, 71 -96.
AMA StyleSaber Arabi Nowdeh, Mohammad Jafar Hadidian Moghaddam, Manoochehr Babanezhad, Iraj Faraji Davoodkhani, Akhtar Kalam, Abdollah Ahmadi, Almoataz Y. Abdelaziz. A Novel Maximum Power Point Tracking Method for Photovoltaic Application Using Secant Incremental Gradient Based on Newton Raphson. Numerical Methods for Energy Applications. 2019; ():71-96.
Chicago/Turabian StyleSaber Arabi Nowdeh; Mohammad Jafar Hadidian Moghaddam; Manoochehr Babanezhad; Iraj Faraji Davoodkhani; Akhtar Kalam; Abdollah Ahmadi; Almoataz Y. Abdelaziz. 2019. "A Novel Maximum Power Point Tracking Method for Photovoltaic Application Using Secant Incremental Gradient Based on Newton Raphson." Numerical Methods for Energy Applications , no. : 71-96.
Solving optimization problems with multiple uncertainties has always been a challenging task in different scopes of science. While different approaches have been developed to take advantage of the stochastic space of the problem, these methods are intensively dependent of the probabilistic information of various variables which are not always available. Relying on the severity of the failure, information-gap decision theory (IGDT) is a robust optimization approach which is entirely autonomous from probabilistic information. In this model, a forecasted amount is presumed for each uncertain variable, and the sensitivity of objective functions is analyzed according to the deviation of each of these uncertain parameters from their forecasted value. In this method, two main types of uncertainty set models including energy-bound model and envelope-bound model are handled. In this chapter, these principles and fundamentals of IGDT are described.
Navid Rezaei; Abdollah Ahmadi; Ali Esmaeel Nezhad; Amirhossein Khazali. Information-Gap Decision Theory: Principles and Fundamentals. Robust Optimal Planning and Operation of Electrical Energy Systems 2019, 11 -33.
AMA StyleNavid Rezaei, Abdollah Ahmadi, Ali Esmaeel Nezhad, Amirhossein Khazali. Information-Gap Decision Theory: Principles and Fundamentals. Robust Optimal Planning and Operation of Electrical Energy Systems. 2019; ():11-33.
Chicago/Turabian StyleNavid Rezaei; Abdollah Ahmadi; Ali Esmaeel Nezhad; Amirhossein Khazali. 2019. "Information-Gap Decision Theory: Principles and Fundamentals." Robust Optimal Planning and Operation of Electrical Energy Systems , no. : 11-33.
Using clean energy sources has contributed to various industries, especially the automotive industry. In this regard, large companies have taken a significant step in the field of renewable energy by introducing Electric Vehicles (EVs). One of the main challenges in the EVs area is evaluating the reliability and safety of these vehicles. Thus, the concept of the reliability and safety of EV's components is considered a significant issue. In general, reliability and safety assessment of important electrical components of EVs, i.e. i) the battery pack, ii) power electronic converters, and iii) the electric motor, plays a significant role in the lifetime performance of EVs’ electrical system. This paper presents a comprehensive review of the reliability of EVs’ components from different points of view. Also, the challenges and future perspective of EVs relating to the reliability and safety, which need to be considered have been investigated.
Foad H. Gandoman; Abdollah Ahmadi; Peter Van Den Bossche; Joeri Van Mierlo; Noshin Omar; Ali Esmaeel Nezhad; Hani Mavalizadeh; Clément Mayet. Status and future perspectives of reliability assessment for electric vehicles. Reliability Engineering & System Safety 2018, 183, 1 -16.
AMA StyleFoad H. Gandoman, Abdollah Ahmadi, Peter Van Den Bossche, Joeri Van Mierlo, Noshin Omar, Ali Esmaeel Nezhad, Hani Mavalizadeh, Clément Mayet. Status and future perspectives of reliability assessment for electric vehicles. Reliability Engineering & System Safety. 2018; 183 ():1-16.
Chicago/Turabian StyleFoad H. Gandoman; Abdollah Ahmadi; Peter Van Den Bossche; Joeri Van Mierlo; Noshin Omar; Ali Esmaeel Nezhad; Hani Mavalizadeh; Clément Mayet. 2018. "Status and future perspectives of reliability assessment for electric vehicles." Reliability Engineering & System Safety 183, no. : 1-16.
The paper presents the info-gap theory for the sake of developing a robust framework for short-term hydrothermal scheduling to tackle severe load uncertainty. Deploying this method, the system operator is provided with a robust decision-making strategy to guarantee the minimum cost under load variation condition while practical and technical limitations such as dynamic ramp rate are taken into consideration. For this purpose, the proposed Unit Commitment (UC) problem considering all above advantages would be modeled in a linear framework, which is in turn taken into account as another outstanding feature of this study as it is compatible to apply to real-world systems. In order to investigate the model efficiency, the modified version of the IEEE 118-bus test system having 54 thermal beside 8 hydro plants is chosen as the case study. Eventually, the results demonstrate how demand fluctuations and errors in the predicted load can be tolerated by allocating additional robust cost.
Seyed-Ehsan Razavi; Ali Esmaeel Nezhad; Hani Mavalizadeh; Fatima Raeisi; Abdollah Ahmadi. Robust hydrothermal unit commitment: A mixed-integer linear framework. Energy 2018, 165, 593 -602.
AMA StyleSeyed-Ehsan Razavi, Ali Esmaeel Nezhad, Hani Mavalizadeh, Fatima Raeisi, Abdollah Ahmadi. Robust hydrothermal unit commitment: A mixed-integer linear framework. Energy. 2018; 165 ():593-602.
Chicago/Turabian StyleSeyed-Ehsan Razavi; Ali Esmaeel Nezhad; Hani Mavalizadeh; Fatima Raeisi; Abdollah Ahmadi. 2018. "Robust hydrothermal unit commitment: A mixed-integer linear framework." Energy 165, no. : 593-602.
In this paper, the optimal design and energy management of the hybrid systems including the photovoltaic (PV) panels, wind turbine (WT) and fuel cell (FC) based on hydrogen storage (HS) (PWFHS) are presented to minimize the total net present cost (TNPC) of northwest region of Iran using intelligent flower pollination algorithm (FPA). The reliability indices that are considered simultaneously as technical constraints are the loss of energy expected (LOEE) and the loss of load expected (LOLE). The FPA performance is compared with well-known optimization methods such as teaching-learning based optimization (TLBO), particle swarm optimization (PSO) and also last researches in hybrid renewable energy designing. The simulation results are presented including decision variables, TNPC, LOEE, LOLE, energy management of generation units in different LOLEmax and LOEEmax and different combination of PWFHS. The results show that the proposed methodology finds the optimal decision variables easily with fast convergence, lower cost and better reliability values in different reliability indices and different PWFHS in comparison to TLBO and PSO.
Mohammad Jafar Hadidian Moghaddam; Akhtar Kalam; Saber Arabi Nowdeh; Abdollah Ahmadi; Manoochehr Babanezhad; Sajeeb Saha. Optimal sizing and energy management of stand-alone hybrid photovoltaic/wind system based on hydrogen storage considering LOEE and LOLE reliability indices using flower pollination algorithm. Renewable Energy 2018, 135, 1412 -1434.
AMA StyleMohammad Jafar Hadidian Moghaddam, Akhtar Kalam, Saber Arabi Nowdeh, Abdollah Ahmadi, Manoochehr Babanezhad, Sajeeb Saha. Optimal sizing and energy management of stand-alone hybrid photovoltaic/wind system based on hydrogen storage considering LOEE and LOLE reliability indices using flower pollination algorithm. Renewable Energy. 2018; 135 ():1412-1434.
Chicago/Turabian StyleMohammad Jafar Hadidian Moghaddam; Akhtar Kalam; Saber Arabi Nowdeh; Abdollah Ahmadi; Manoochehr Babanezhad; Sajeeb Saha. 2018. "Optimal sizing and energy management of stand-alone hybrid photovoltaic/wind system based on hydrogen storage considering LOEE and LOLE reliability indices using flower pollination algorithm." Renewable Energy 135, no. : 1412-1434.
Electric power systems are gradually maturing in the operational and management architecture. The eventual goal of the system operators is to provide more reliable and high-quality energy services in a cost-effective and environmental framework. To that end, new applications and technologies should be innovated and integrated into the system infrastructure sustainably. Energy storage system (ESS) is an essential part of the power system. Various types of ESS technologies, the associated characteristics and benefits are overviewed in this section.
Navid Rezaei; Abdollah Ahmadi; Sara N. Afifi; Ahmed F. Zobaa; Shady H. Aleem. Overview of energy storage technologies. Energy Storage at Different Voltage Levels: Technology, integration, and market aspects 2018, 1 -29.
AMA StyleNavid Rezaei, Abdollah Ahmadi, Sara N. Afifi, Ahmed F. Zobaa, Shady H. Aleem. Overview of energy storage technologies. Energy Storage at Different Voltage Levels: Technology, integration, and market aspects. 2018; ():1-29.
Chicago/Turabian StyleNavid Rezaei; Abdollah Ahmadi; Sara N. Afifi; Ahmed F. Zobaa; Shady H. Aleem. 2018. "Overview of energy storage technologies." Energy Storage at Different Voltage Levels: Technology, integration, and market aspects , no. : 1-29.
Foad H. Gandoman; Shady H.E. Abdel Aleem; Noshin Omar; Abdollah Ahmadi; Faisal Q. Alenezi. Short-term solar power forecasting considering cloud coverage and ambient temperature variation effects. Renewable Energy 2018, 123, 793 -805.
AMA StyleFoad H. Gandoman, Shady H.E. Abdel Aleem, Noshin Omar, Abdollah Ahmadi, Faisal Q. Alenezi. Short-term solar power forecasting considering cloud coverage and ambient temperature variation effects. Renewable Energy. 2018; 123 ():793-805.
Chicago/Turabian StyleFoad H. Gandoman; Shady H.E. Abdel Aleem; Noshin Omar; Abdollah Ahmadi; Faisal Q. Alenezi. 2018. "Short-term solar power forecasting considering cloud coverage and ambient temperature variation effects." Renewable Energy 123, no. : 793-805.
Microgrids face with various uncertainty resources which may put their reliable and beneficial bidding strategy at risk. In the literature, to handle the uncertainties, distinctive methodologies from fuzzy to stochastic techniques have been implemented widely. However, they dominantly suffer from dependency to the uncertainty models and are highly computational. In this paper, to overcome the challenges, a new approach based on information gap decision theory (IGDT) is proposed to provide a promising risk-managing bidding strategy. The uncertainties are modeled effectively without relying on the model in both robust and opportunistic frameworks. The problem is formulated as an effective multi-objective optimization problem considering to the impacts of different uncertainties. Normal boundary intersection technique is utilized to generate evenly distributed Pareto Frontier. Analyzing the IGDT-based numerical results, applied to a test microgrid over a 24 h time horizon, verifies the effectiveness of the proposed bidding strategy structure confronting to the severe uncertainties.
Navid Rezaei; Abdollah Ahmadi; Amirhossein Khazali; Jamshid Aghaei. Multiobjective Risk-Constrained Optimal Bidding Strategy of Smart Microgrids: An IGDT-Based Normal Boundary Intersection Approach. IEEE Transactions on Industrial Informatics 2018, 15, 1532 -1543.
AMA StyleNavid Rezaei, Abdollah Ahmadi, Amirhossein Khazali, Jamshid Aghaei. Multiobjective Risk-Constrained Optimal Bidding Strategy of Smart Microgrids: An IGDT-Based Normal Boundary Intersection Approach. IEEE Transactions on Industrial Informatics. 2018; 15 (3):1532-1543.
Chicago/Turabian StyleNavid Rezaei; Abdollah Ahmadi; Amirhossein Khazali; Jamshid Aghaei. 2018. "Multiobjective Risk-Constrained Optimal Bidding Strategy of Smart Microgrids: An IGDT-Based Normal Boundary Intersection Approach." IEEE Transactions on Industrial Informatics 15, no. 3: 1532-1543.