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Dr. Rabiee received a B.Sc. degree in electrical engineering from the Iran University of Science and Technology, Tehran, Iran, in 2006, and M.Sc. and Ph.D. degrees in electrical power engineering from the Sharif University of Technology, Tehran, Iran, in 2008 and 2013, respectively. He is currently an Associate Professor with the Department of Electrical Engineering, University of Zanjan, Iran. His research interests include power system operation and security, renewable energies, and optimization methods. He is an Editor for IET Generation, Transmission, and Distribution. Dr. Rabiee has been awarded the 2019 Premium Award for Best Paper in IET Generation, Transmission, and Distribution.
In this paper, a robust scheduling model is proposed for combined heat and power (CHP)-based microgrids using information gap decision theory (IGDT). The microgrid under study consists of conventional power generation as well as boiler units, fuel cells, CHPs, wind turbines, solar PVs, heat storage units, and battery energy storage systems (BESS) as the set of distributed energy resources (DERs). Additionally, a demand response program (DRP) model is considered which has a successful performance in the microgrid hourly scheduling. One of the goals of CHP-based microgrid scheduling is to provide both thermal and electrical energy demands of the consumers. Additionally, the other objective is to benefit from the revenues obtained by selling the surplus electricity to the main grid during the high energy price intervals or purchasing it from the grid when the price of electricity is low at the electric market. Hence, in this paper, a robust scheduling approach is developed with the aim of maximizing the total profit of different energy suppliers in the entire scheduling horizon. The employed IGDT technique aims to handle the impact of uncertainties in the power output of wind and solar PV units on the overall profit.
Abbas Rabiee; Ali Abdali; Seyed Mohseni-Bonab; Mohsen Hazrati. Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources. Sustainability 2021, 13, 7119 .
AMA StyleAbbas Rabiee, Ali Abdali, Seyed Mohseni-Bonab, Mohsen Hazrati. Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources. Sustainability. 2021; 13 (13):7119.
Chicago/Turabian StyleAbbas Rabiee; Ali Abdali; Seyed Mohseni-Bonab; Mohsen Hazrati. 2021. "Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources." Sustainability 13, no. 13: 7119.
The main goal of distribution network operator is to establish a balance between supply and demand at the lowest cost while considering the technical constraints. Nowadays, distribution network operators exploit various types of flexibilities to minimise operational costs. However, each flexibility resource has its own technical and economic characteristics. This paper proposes a day‐ahead energy dispatch model which allows the distribution network operator to minimise the energy procurement costs on an hourly basis. The developed model considers various flexibility resources such as renewable energy sources, energy storage systems, demand response, optimal distribution system reconfiguration, and on‐load tap changers optimal settings. The proposed model is formulated as a convex mixed‐integer second‐order conic programming model. It is implemented on the IEEE standard 33‐bus and 70‐bus radial systems to demonstrate its capabilities. The obtained numerical results substantiate the role of distributed energy resources in energy procurement cost reduction, while the impact of distribution system reconfiguration and on‐load tap changers on voltage profile improvement.
Ehsan Hooshmand; Abbas Rabiee; Saeid Jalilzadeh; Alireza Soroudi. Optimal flexibility coordination for energy procurement in distribution networks. IET Renewable Power Generation 2021, 1 .
AMA StyleEhsan Hooshmand, Abbas Rabiee, Saeid Jalilzadeh, Alireza Soroudi. Optimal flexibility coordination for energy procurement in distribution networks. IET Renewable Power Generation. 2021; ():1.
Chicago/Turabian StyleEhsan Hooshmand; Abbas Rabiee; Saeid Jalilzadeh; Alireza Soroudi. 2021. "Optimal flexibility coordination for energy procurement in distribution networks." IET Renewable Power Generation , no. : 1.
It is well accepted that combined heat and power (CHP) generation can increase the efficiency of power and heat generation at the same time. With the increasing penetration of CHPs, determination of economic dispatch of power and heat becomes more complex and challenging. The CHP economic dispatch (CHPED) problem is a challenging optimization problem due to non-linearity and non-convexity in both objective function and constraints. Hence, in this paper a novel meta-heuristic algorithm, namely improved artificial bee colony (IABC) algorithm is proposed to solve the CHPED problem. The valve-point effects, power losses as well as the feasible operation region of CHP units are taken into account in the proposed CHPED problem model and the optimal dispatch of power/heat outputs of CHP units is determined via the proposed IABC algorithm. The proposed algorithm is applied on three test systems, in which two of them are large-scale CHPED benchmarks. The obtained results and comprehensive comparison with available methods, demonstrate the superiority of the proposed algorithm for dealing with non-convex and constrained CHPED problem.
Abbas Rabiee; Mohammad Jamadi; Behnam Mohammadi-Ivatloo; Ali Ahmadian. Optimal Non-Convex Combined Heat and Power Economic Dispatch via Improved Artificial Bee Colony Algorithm. Processes 2020, 8, 1036 .
AMA StyleAbbas Rabiee, Mohammad Jamadi, Behnam Mohammadi-Ivatloo, Ali Ahmadian. Optimal Non-Convex Combined Heat and Power Economic Dispatch via Improved Artificial Bee Colony Algorithm. Processes. 2020; 8 (9):1036.
Chicago/Turabian StyleAbbas Rabiee; Mohammad Jamadi; Behnam Mohammadi-Ivatloo; Ali Ahmadian. 2020. "Optimal Non-Convex Combined Heat and Power Economic Dispatch via Improved Artificial Bee Colony Algorithm." Processes 8, no. 9: 1036.
In the energy distribution networks, the most important and valuable equipment is oil-immersed distribution transformers. Besides, due to the key role of these transformers and their multiplicity, their lifetime monitoring is inevitable. The life of a transformer depends on the weakest solid insulation material (i.e. paper insulation). On the other hand, monitoring the transformer insulation status requires accurate information to be available about the oil temperature at every moment. Therefore, it is important to control and predict the oil temperature rise in the transformer. In this study, a new model based on fundamental heat transfer theory is proposed for thermal behaviour prediction of top oil of indoor distribution transformers using the concept of thermal resistance, namely electro-thermal resistance model (E-TRM). In E-TRM, the thermal resistance network is formed by following three-dimensional heat transfer path and assigning thermal resistance to each path. To evaluate the proposed E-TRM, the results of this model are verified with experimental results. Moreover, the E-TRM is used to predict the thermal behaviour of the indoor transformer in the overloading condition. At the end, the transformer loss of life is estimated based on the oil temperature and a normal cyclic overloading strategy is presented for overloading management.
Ali Asghar Taheri; Ali Abdali; Abbas Rabiee. Indoor distribution transformers oil temperature prediction using new electro‐thermal resistance model and normal cyclic overloading strategy: an experimental case study. IET Generation, Transmission & Distribution 2020, 14, 5792 -5803.
AMA StyleAli Asghar Taheri, Ali Abdali, Abbas Rabiee. Indoor distribution transformers oil temperature prediction using new electro‐thermal resistance model and normal cyclic overloading strategy: an experimental case study. IET Generation, Transmission & Distribution. 2020; 14 (24):5792-5803.
Chicago/Turabian StyleAli Asghar Taheri; Ali Abdali; Abbas Rabiee. 2020. "Indoor distribution transformers oil temperature prediction using new electro‐thermal resistance model and normal cyclic overloading strategy: an experimental case study." IET Generation, Transmission & Distribution 14, no. 24: 5792-5803.
This study develops a three-stage energy management system (EMS) for renewable energy microgrid operation. The core of this framework is based on a unit commitment problem integrated with model predictive control (MPC) to address the problem of uncertainty in renewable sources. Meanwhile, it is shown that an MPC approach may be insufficient to fully address the hurdles for optimal and safe operation of wind power-integrated energy systems due to the severity of wind speed fluctuations within even short time intervals. Spinning reserve resources can have a positive impact to ensure a reliable operation, yet their availability is highly dependent on the existence and capacity of dispatchable energy sources, such as diesel generators, in energy systems. Consequently, a supplementary Constrained Information Gap Decision Theory approach is utilised in this study to optimise the system's robustness against severe uncertainty of wind generations. In order to evaluate the presented framework, a descriptive index is first introduced, and then the model is applied to an isolated microgrid. The results indicate that by deploying these three stages, the renewable energy support index increases, ensuring an optimal, reliable, and safe operation.
Mohamad‐Amin Nasr; Abbas Rabiee; Innocent Kamwa. MPC and robustness optimisation‐based EMS for microgrids with high penetration of intermittent renewable energy. IET Generation, Transmission & Distribution 2020, 14, 5239 -5248.
AMA StyleMohamad‐Amin Nasr, Abbas Rabiee, Innocent Kamwa. MPC and robustness optimisation‐based EMS for microgrids with high penetration of intermittent renewable energy. IET Generation, Transmission & Distribution. 2020; 14 (22):5239-5248.
Chicago/Turabian StyleMohamad‐Amin Nasr; Abbas Rabiee; Innocent Kamwa. 2020. "MPC and robustness optimisation‐based EMS for microgrids with high penetration of intermittent renewable energy." IET Generation, Transmission & Distribution 14, no. 22: 5239-5248.
Microgrids are increasingly affected by volatile wind energy due to the high penetration of this kind of renewable energy sources. This study investigates the impact of wind energy uncertainty on voltage stability and energy management system (EMS) of isolated microgrids in the presence of plugin electric vehicles (PEVs). A stochastic voltage stability constrained microgrid energy management system (SVSC-MEMS) architecture based on a coordinated unit commitment-optimal power flow (UC-OPF) methodology, which simultaneously considers the UC and OPF constraints, is proposed. The proposed model guarantees the system security from the voltage stability standpoint, considering a specific loading margin. Besides, the role of PEVs in the microgrid EMS is examined. In order to validate the performance of the introduced SVSC-MEMS, a CIGRE benchmark test system is used. The numerical results, obtained from the implementation of the proposed model in the general algebraic modeling system (GAMS) environment, demonstrate the importance of voltage stability and wind power uncertainty on the microgrid EMS, and furthermore, the key role of PEVs in the emerging microgrids.
Saman Nikkhah; Mohamad-Amin Nasr; Abbas Rabiee. A Stochastic Voltage Stability Constrained EMS for Isolated Microgrids in the Presence of PEVs Using a Coordinated UC-OPF Framework. IEEE Transactions on Industrial Electronics 2020, 68, 4046 -4055.
AMA StyleSaman Nikkhah, Mohamad-Amin Nasr, Abbas Rabiee. A Stochastic Voltage Stability Constrained EMS for Isolated Microgrids in the Presence of PEVs Using a Coordinated UC-OPF Framework. IEEE Transactions on Industrial Electronics. 2020; 68 (5):4046-4055.
Chicago/Turabian StyleSaman Nikkhah; Mohamad-Amin Nasr; Abbas Rabiee. 2020. "A Stochastic Voltage Stability Constrained EMS for Isolated Microgrids in the Presence of PEVs Using a Coordinated UC-OPF Framework." IEEE Transactions on Industrial Electronics 68, no. 5: 4046-4055.
Distributed energy resources (DERs) and distribution network reconfiguration have considerable effects on both the economic and operational performance of distribution networks. However, the uncertain nature of renewable energy sources (RESs), wind energy, for instance, can bring about serious challenges to the distribution system operators and distribution companies (DisCos). Therefore, a suitable methodology is a matter of the utmost importance to handle the uncertainty of RESs. In addition, DisCos can benefit from the utilisation of energy storage technologies to increase the penetration of RESs into the system. In this regard, this study proposes a risk-averse energy management strategy (RA-EMS) in the presence of DERs, while the impact of uncertainties of RESs on the optimal configuration of the network is investigated. The uncertainty of RESs is modelled through the information gap decision theory, which has significant advantages such as low computational burden, no need for probability density function, and exact results compared to other methodologies for uncertainty handling. The proposed RA-EMS model is implemented on the IEEE 33-bus distribution system, and its superiority over the scenario-based stochastic programming is demonstrated. The robust configuration of the system against RESs’ uncertainty is obtained for different levels of uncertainty radius.
Saman Nikkhah; Abbas Rabiee; Seyed Masoud Mohseni‐Bonab; Innocent Kamwa. Risk averse energy management strategy in the presence of distributed energy resources considering distribution network reconfiguration: an information gap decision theory approach. IET Renewable Power Generation 2020, 14, 305 -312.
AMA StyleSaman Nikkhah, Abbas Rabiee, Seyed Masoud Mohseni‐Bonab, Innocent Kamwa. Risk averse energy management strategy in the presence of distributed energy resources considering distribution network reconfiguration: an information gap decision theory approach. IET Renewable Power Generation. 2020; 14 (2):305-312.
Chicago/Turabian StyleSaman Nikkhah; Abbas Rabiee; Seyed Masoud Mohseni‐Bonab; Innocent Kamwa. 2020. "Risk averse energy management strategy in the presence of distributed energy resources considering distribution network reconfiguration: an information gap decision theory approach." IET Renewable Power Generation 14, no. 2: 305-312.
The optimal generation scheduling of combined heat and power units aims to minimize total cost of generation units satisfying power and heat demands.The combined heat and power economic dispatch problem should be solved considering a series of electrical and operational constraints, which will be more complicated considering valve-point effects of power-only units and nonconvex feasible operating regions of cogeneration units. In such a case, the problem has nonconvex and nondifferential characteristic. In this article, a two-stage model is proposed to handle the nonconvexity and nondifferentiability of valve-point effects in cost functions of power-only units. The proposed model obtains a convex feasible operating region in the first stage using a linear approximation model. In addition, an equivalent formulation is proposed in the second stage to handle the nondifferentiable term of valve-point effects using the obtained convex feasible operating regions. The proposed model is implemented on two case studies to evaluate performance of the proposed model.
Mohammad Moradi-Dalvand; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Sadjad Galavani; Abbas Rabiee. A Two-Stage Mathematical Programming Approach for the Solution of Combined Heat and Power Economic Dispatch. IEEE Systems Journal 2019, 14, 2873 -2881.
AMA StyleMohammad Moradi-Dalvand, Morteza Nazari-Heris, Behnam Mohammadi-Ivatloo, Sadjad Galavani, Abbas Rabiee. A Two-Stage Mathematical Programming Approach for the Solution of Combined Heat and Power Economic Dispatch. IEEE Systems Journal. 2019; 14 (2):2873-2881.
Chicago/Turabian StyleMohammad Moradi-Dalvand; Morteza Nazari-Heris; Behnam Mohammadi-Ivatloo; Sadjad Galavani; Abbas Rabiee. 2019. "A Two-Stage Mathematical Programming Approach for the Solution of Combined Heat and Power Economic Dispatch." IEEE Systems Journal 14, no. 2: 2873-2881.
This chapter proposes a model to demonstrate the impact of renewable energy sources, demand response (DR), and distribution feeder reconfiguration (DFR) on the optimal share of energy in distribution systems (DSs). The price-based DR program is adopted via load shifting mechanism. The proposed model determines optimal locations of RESs and DR in DSs to minimize the energy procurement cost as well as the cost of energy not supplied. Hence, a multiobjective optimization problem is formulated through a mixed-integer second-order cone programming (MISOCP) model, with a guaranteed global optimal solution. This model is solved via the ε-constraint method and Pareto optimal solutions obtained. The DFR is also considered to optimize the network topology. The proposed model is implemented on a standard 70-bus radial test system and solved by the General Algebraic Modeling System (GAMS) optimization software. According to simulation results, the proposed model is beneficial both from the reliability and economic perspectives.
Ehsan Hooshmand; Abbas Rabiee. Distribution Feeder Reconfiguration Considering Price-Based Demand Response Program. Demand Response Application in Smart Grids 2019, 95 -117.
AMA StyleEhsan Hooshmand, Abbas Rabiee. Distribution Feeder Reconfiguration Considering Price-Based Demand Response Program. Demand Response Application in Smart Grids. 2019; ():95-117.
Chicago/Turabian StyleEhsan Hooshmand; Abbas Rabiee. 2019. "Distribution Feeder Reconfiguration Considering Price-Based Demand Response Program." Demand Response Application in Smart Grids , no. : 95-117.
The distribution network operator is usually responsible for improvement of efficiency and reliability of the network. This paper proposes a framework to demonstrate the impact of renewable energy sources (RESs), energy storage systems (ESSs), demand response (DR) and reconfiguration on the optimal sharing of energy. The proposed model determines the optimal locations of RESs, ESSs and DR in the distribution network to minimize simultaneously the cost of energy procurement and energy not supplied. A multi-objective optimization problem is formulated with a mixed-integer second-order cone programming model and ε-constraint method is used to generate Pareto optimal solutions. The network reconfiguration is also considered to optimize the power flow by changing the network topology. The proposed model is implemented on the IEEE standard 33-bus radial test system, and solved by General Algebraic Modeling System (GAMS) optimization software. According to the simulation results, the proposed framework is beneficial both from the reliability and economic perspectives.
Ehsan Hooshmand; Abbas Rabiee. Energy management in distribution systems, considering the impact of reconfiguration, RESs, ESSs and DR: A trade-off between cost and reliability. Renewable Energy 2019, 139, 346 -358.
AMA StyleEhsan Hooshmand, Abbas Rabiee. Energy management in distribution systems, considering the impact of reconfiguration, RESs, ESSs and DR: A trade-off between cost and reliability. Renewable Energy. 2019; 139 ():346-358.
Chicago/Turabian StyleEhsan Hooshmand; Abbas Rabiee. 2019. "Energy management in distribution systems, considering the impact of reconfiguration, RESs, ESSs and DR: A trade-off between cost and reliability." Renewable Energy 139, no. : 346-358.
Considering increasing distributed energy resources and responsive loads in smart grid paradigm, this study proposes a new approach for robust hourly energy scheduling of distribution systems at the presence of severe uncertain renewable energy sources (RES). Wind and photovoltaic power generations are considered as the RESs. The aim is to minimise the total energy procurement cost, while considering the participation of RESs, by their optimal allocation in the network. The inherent uncertainty of RESs is handled via information gap decision theory. One of the features of the proposed model is to consider the impact of demand response and energy storage system as the effective tools to reduce unintended costs due to uncertainty of RESs. Also, the proposed model handles the uncertainty of multiple RESs in a way that maximum tolerable uncertainty of RESs is achieved for a given worsening of total energy procurement cost. The proposed model is formulated as a mixed integer nonlinear optimisation problem and is implemented in general algebraic modelling system environment. The model is applied on the IEEE standard 33-bus radial test system, and the obtained results substantiate that the utilisation of ESS and DR can reduce the impact of RESs' uncertainty on the energy cost.
Ehsan Hooshmand; Abbas Rabiee. Robust model for optimal allocation of renewable energy sources, energy storage systems and demand response in distribution systems via information gap decision theory. IET Generation, Transmission & Distribution 2019, 13, 511 -520.
AMA StyleEhsan Hooshmand, Abbas Rabiee. Robust model for optimal allocation of renewable energy sources, energy storage systems and demand response in distribution systems via information gap decision theory. IET Generation, Transmission & Distribution. 2019; 13 (4):511-520.
Chicago/Turabian StyleEhsan Hooshmand; Abbas Rabiee. 2019. "Robust model for optimal allocation of renewable energy sources, energy storage systems and demand response in distribution systems via information gap decision theory." IET Generation, Transmission & Distribution 13, no. 4: 511-520.
There are many technical challenges for integration of renewable energy sources (RESs) in the context of microgrids. Among these challenges, spinning reserve energy management should be accurately considered in the microgrid scheduling system for a better system operation. This study presents a methodology to model and analyse a novel scheme to integrate RESs, particularly photovoltaic (PV) systems, in diesel generation-based isolated microgrids. The proposed approach considers the uncertainties of PV power generation and demand, simultaneously, by solving a bi-level multi-objective optimisation problem using information gap decision theory (IGDT). The proposed energy management system is formulated considering spinning reserve constraints and the uncertainties associated with PV power generation and load, by solving a unit commitment problem. This method, a non-probabilistic approach, does not require the probability density function of uncertain parameters and provides a robust framework to better understand the potential savings due to the PV integration. In order to test and perform the analysis, realistic data from a 20 MW hybrid PV project is used as a case study. Furthermore, the proposed method is compared with probabilistic techniques, such as Monte Carlo simulations and scenario-based stochastic programming technique. The presented studies demonstrate applicability of the proposed model for real microgrids.
Mohamad‐Amin Nasr; Ehsan Nasr‐Azadani; Abbas Rabiee; Seyed Hossein Hosseinian. Risk‐averse energy management system for isolated microgrids considering generation and demand uncertainties based on information gap decision theory. IET Renewable Power Generation 2019, 13, 940 -951.
AMA StyleMohamad‐Amin Nasr, Ehsan Nasr‐Azadani, Abbas Rabiee, Seyed Hossein Hosseinian. Risk‐averse energy management system for isolated microgrids considering generation and demand uncertainties based on information gap decision theory. IET Renewable Power Generation. 2019; 13 (6):940-951.
Chicago/Turabian StyleMohamad‐Amin Nasr; Ehsan Nasr‐Azadani; Abbas Rabiee; Seyed Hossein Hosseinian. 2019. "Risk‐averse energy management system for isolated microgrids considering generation and demand uncertainties based on information gap decision theory." IET Renewable Power Generation 13, no. 6: 940-951.
Seyed Masoud Mohseni-Bonab; Innocent Kamwa; Ali Moeini; Abbas Rabiee. Voltage Security Constrained Stochastic Programming Model for Day-Ahead BESS Schedule in Co-Optimization of T&D Systems. IEEE Transactions on Sustainable Energy 2019, 11, 391 -404.
AMA StyleSeyed Masoud Mohseni-Bonab, Innocent Kamwa, Ali Moeini, Abbas Rabiee. Voltage Security Constrained Stochastic Programming Model for Day-Ahead BESS Schedule in Co-Optimization of T&D Systems. IEEE Transactions on Sustainable Energy. 2019; 11 (1):391-404.
Chicago/Turabian StyleSeyed Masoud Mohseni-Bonab; Innocent Kamwa; Ali Moeini; Abbas Rabiee. 2019. "Voltage Security Constrained Stochastic Programming Model for Day-Ahead BESS Schedule in Co-Optimization of T&D Systems." IEEE Transactions on Sustainable Energy 11, no. 1: 391-404.
Recently, penetration of intermittent power sources has been increased in power systems due to an international drive for clean and sustainable energies; but these alternative sources could encounter power systems with some problems, which need planning and prevention. This paper proposes a two-stage scenario-based planning model for large-scale wind farms development, based on a project management approach. Considering a 10-year project of large wind farms development, the annual installation capacities of wind turbines are first optimally planned in order to minimize the Levelized Cost of Energy (LCOE) of wind farms. Second, as wind power penetration is consistently increasing in the grid, some stability concerns will come up such as voltage instability. To remedy this condition, the optimum dispatch of grid’s conventional power sources and control variables is determined in such a way that not only in any state of operation (taking into account wind and load uncertainties) but also in post-contingency conditions, the prescribed security margin is ensured at the lowest possible cost. This study has been conducted on an actual power system of Iran’s southeast grid, as well as IEEE 118-bus standard test system. Also, modified crow search algorithm (MCSA) is utilized to solve the developed optimization model. The numerical studies substantiate the effectiveness of the proposed method for long-term planning of wind farms.
Amirreza Gholizadeh; Abbas Rabiee; Roohollah Fadaeinedjad. A scenario-based voltage stability constrained planning model for integration of large-scale wind farms. International Journal of Electrical Power & Energy Systems 2018, 105, 564 -580.
AMA StyleAmirreza Gholizadeh, Abbas Rabiee, Roohollah Fadaeinedjad. A scenario-based voltage stability constrained planning model for integration of large-scale wind farms. International Journal of Electrical Power & Energy Systems. 2018; 105 ():564-580.
Chicago/Turabian StyleAmirreza Gholizadeh; Abbas Rabiee; Roohollah Fadaeinedjad. 2018. "A scenario-based voltage stability constrained planning model for integration of large-scale wind farms." International Journal of Electrical Power & Energy Systems 105, no. : 564-580.
Optimal distribution system reconfiguration (DSR) and distribution generation (DG) allocation are viable solutions for improvement of technical and economic aspects of distribution systems. This paper proposes a stochastic multi-objective DSR (SMO-DSR) model, aims to maximize the DG owner’s profit and minimizes the distribution company’s (DisCo's) costs. The uncertainties of wind power generation, electricity price, and demand are handled via scenario based approach. The proposed SMO-DSR model is solved via ε-constraint method and the best compromise solution is selected by fuzzy satisfying criterion. The model is a mixed integer non-linear programing (MINLP) problem which is implemented on IEEE 33-bus distribution system in General Algebraic Modeling System (GAMS) environment. To show the effectiveness of the proposed SMO-DSR approach, it is studied in different cases. A sensitivity analysis is also performed to show the effect of contract price of wind energy on the objectives of DisCo and DG owner. The obtained results substantiate the interaction between the DSR and DG allocation problems. Also, it is shown that the contract price of wind energy considerably influences both DG owner and DisCo schedules. Besides, when a compromise is made between the DG owner's profit and DisCo's cost, the power losses of the network is reduced.
Ehsan Kianmehr; Saman Nikkhah; Abbas Rabiee. Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives. Renewable Energy 2018, 132, 471 -485.
AMA StyleEhsan Kianmehr, Saman Nikkhah, Abbas Rabiee. Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives. Renewable Energy. 2018; 132 ():471-485.
Chicago/Turabian StyleEhsan Kianmehr; Saman Nikkhah; Abbas Rabiee. 2018. "Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives." Renewable Energy 132, no. : 471-485.
The issues such as the price of oil and global warming are economic and environmental concerns that increase wind power penetration as a renewable energy source in today’s power systems worldwide. Unfortunately, variability and intermittency of wind energy could cause serious operational concerns, such as voltage stability problem. Therefore, it is important to minimize the negative aspects of wind power penetration on the voltage stability of power system. Consequently, the aim of this chapter is to provide a comprehensive long-term planning model for expansion of joint energy storage systems (ESSs) and large-scale wind farms (WFs) in order to increase wind power penetration and grid voltage stability. The proposed voltage stability constrained planning model comprises the following steps: (1) modeling of the impact of voltage stability constraints on the optimal capacity of WFs; (2) maximizing the profit obtained via wind energy procurement for WFs owners; (3) using ESS to facilitate long-term wind power integration and to alleviate the intermittency of WFs power generation; (4) investigation of the impact of ESS and WFs on the voltage stability. It is worth to note that ultimate goals are to increase the wind power penetration and to maintain a desired level of voltage stability. The results obtained from implementation of proposed method on the IEEE New England 39-bus standard test system demonstrate the effectiveness of the joint ESS and WFs planning model.
Saman Nikkhah; Abbas Rabiee. A Joint Energy Storage Systems and Wind Farms Long-Term Planning Model Considering Voltage Stability. Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs 2018, 337 -363.
AMA StyleSaman Nikkhah, Abbas Rabiee. A Joint Energy Storage Systems and Wind Farms Long-Term Planning Model Considering Voltage Stability. Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs. 2018; ():337-363.
Chicago/Turabian StyleSaman Nikkhah; Abbas Rabiee. 2018. "A Joint Energy Storage Systems and Wind Farms Long-Term Planning Model Considering Voltage Stability." Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs , no. : 337-363.
With the growth of emerging new technologies in distribution networks, such as wind power, photovoltaic or DGs, the need for simultaneously investigation of these networks alongside transmission networks is highly important. In this paper, an efficient framework is proposed to understand seamlessly transmission and distribution (T&D) interactions while including detailed models for distributed energy resources. Wind power, photovoltaic and load are investigated according to their 24h profile. Besides, wind power uncertainty is considered via scenario based method. Finally, Battery Energy Storage Systems (BESSs`) are used to track probabilistic renewable generation and minimize the total system power losses. The modified IEEE 9-bus test system is selected as a transmission network and 3 simple 8-bus radial feeders are selected as the distribution side networks. The problem modeled as a mixed integer nonlinear programming (MINLP) optimization problem and handled via GAMS programming language. The results show that with high penetration of renewable sources at distribution level, rescheduling main generators increases system energy efficiency. Moreover, BESS mitigates the impact of renewable sources volatility on both transmission and distribution levels while reducing power losses during peak hours.
Seyed Masoud Mohseni-Bonab; Innocent Kamwa; Abbas Rabiee; Ali Moeini. Stochastic Day-ahead Optimal BESSs' Allocation in T&D Systems: Co-Optimization Based Approach with Uncertainties. 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D) 2018, 1 -9.
AMA StyleSeyed Masoud Mohseni-Bonab, Innocent Kamwa, Abbas Rabiee, Ali Moeini. Stochastic Day-ahead Optimal BESSs' Allocation in T&D Systems: Co-Optimization Based Approach with Uncertainties. 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D). 2018; ():1-9.
Chicago/Turabian StyleSeyed Masoud Mohseni-Bonab; Innocent Kamwa; Abbas Rabiee; Ali Moeini. 2018. "Stochastic Day-ahead Optimal BESSs' Allocation in T&D Systems: Co-Optimization Based Approach with Uncertainties." 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D) , no. : 1-9.
This study proposes an optimal voltage control scheme to deal with long-term voltage stability of power systems. The control of voltage is accomplished by model predictive control (MPC) scheme. The control objective function considers the control efforts and the difference between the predicted and reference voltages. Also, this study considers the detailed non-linear dynamic model of the system including doubly-fed induction generator wind turbines, over excitation limiter and under-load tap changer, which are important elements, should be considered in voltage stability evaluation of power systems. The proposed approach composed of the following two major stages at each time instance: first, the power system non-linear dynamic equations are linearized and optimal control laws are obtained by MPC technique; in the second stage, the system dynamic behavior is investigated via time-domain simulations by applying the attained optimal control signals at the first step. The proposed MPC-based voltage control scheme is implemented on a well-known test system, under variable wind speed and fault conditions. Also, this method's performance is compared with state feedback control technique. The obtained numerical results validate the capability of the proposed control scheme to preserve voltage stability at the presence of stochastic wind speed variations and severe disturbances.
Hossein Yassami; Abbas Rabiee; Abolfazl Jalilvand; Farhad Bayat. Model predictive control scheme for coordinated voltage control of power systems at the presence of volatile wind power generation. IET Generation, Transmission & Distribution 2018, 12, 1922 -1928.
AMA StyleHossein Yassami, Abbas Rabiee, Abolfazl Jalilvand, Farhad Bayat. Model predictive control scheme for coordinated voltage control of power systems at the presence of volatile wind power generation. IET Generation, Transmission & Distribution. 2018; 12 (8):1922-1928.
Chicago/Turabian StyleHossein Yassami; Abbas Rabiee; Abolfazl Jalilvand; Farhad Bayat. 2018. "Model predictive control scheme for coordinated voltage control of power systems at the presence of volatile wind power generation." IET Generation, Transmission & Distribution 12, no. 8: 1922-1928.
This paper proposes a novel approach for long-term planning of wind energy considering its inherent uncertainty. The uncertainty of wind energy is handled via information gap decision theory (IGDT) method. Additionally, due to the importance of security considerations, loading margin is employed as an index of voltage stability to guarantee the security of power system. The operational constraints (such as power flow equations) in initial operation point considered along with those at the voltage collapse point, simultaneously. Accordingly, the IGDT-based voltage stability constrained wind energy-planning model is proposed that can be used for ensuring the safe operation of power networks. The main feature of this model is to handle the uncertainty of wind energy in the long-term wind energy planning via IGDT technique, by considering voltage stability constraints. In order to evaluate the capability of the IGDT technique for uncertainty handling of wind energy, the obtained results are compared with Monte Carlo simulations. To demonstrate the effectiveness of proposed model, it is applied to the New-England 39-bus test system. The obtained results validated the applicability of the proposed model for optimal wind energy planning. The proposed methodology could help wind farm investors to make optimal large-scale wind energy investment decisions.
Abbas Rabiee; Saman Nikkhah; Alireza Soroudi. Information gap decision theory to deal with long-term wind energy planning considering voltage stability. Energy 2018, 147, 451 -463.
AMA StyleAbbas Rabiee, Saman Nikkhah, Alireza Soroudi. Information gap decision theory to deal with long-term wind energy planning considering voltage stability. Energy. 2018; 147 ():451-463.
Chicago/Turabian StyleAbbas Rabiee; Saman Nikkhah; Alireza Soroudi. 2018. "Information gap decision theory to deal with long-term wind energy planning considering voltage stability." Energy 147, no. : 451-463.
This paper proposes a new framework for corrective voltage control (CVC) of power systems. It ensures a desired loading margin (LM) after encountering severe contingencies while minimizing the corresponding control costs. The framework is divided into primary corrective voltage control (PCVC) and secondary CVC (SCVC) stages for restoration of voltage stability and ensuring a desired LM. These stages are based on the sequence and quickness of the control actions required in post-contingency state of the system. The PCVC sub problem deals with the condition faced by a power system subject to voltage instability as the result of severe contingencies. Such control is merely devised to restore system stability. Next, in the SCVC sub problem that follows PCVC, the system operating point is modified such that a desired LM is ensured, and hence voltage security of the system is achieved. The active and reactive power redispatch of generation units and involuntary load curtailment (ILC) are employed along with the voluntary demand-side participations as control facilities in PCVC and SCVC sub problems, by deploying a proper voltage dependent static model for loads. The proposed framework is examined on the IEEE 118-bus system. The numerical results substantiate the effectiveness of the proposed approach.
Abbas Rabiee; Seyed Masoud Mohseni-Bonab; Mostafa Parniani; Innocent Kamwa. Optimal Cost of Voltage Security Control Using Voltage Dependent Load Models in Presence of Demand Response. IEEE Transactions on Smart Grid 2018, 10, 2383 -2395.
AMA StyleAbbas Rabiee, Seyed Masoud Mohseni-Bonab, Mostafa Parniani, Innocent Kamwa. Optimal Cost of Voltage Security Control Using Voltage Dependent Load Models in Presence of Demand Response. IEEE Transactions on Smart Grid. 2018; 10 (3):2383-2395.
Chicago/Turabian StyleAbbas Rabiee; Seyed Masoud Mohseni-Bonab; Mostafa Parniani; Innocent Kamwa. 2018. "Optimal Cost of Voltage Security Control Using Voltage Dependent Load Models in Presence of Demand Response." IEEE Transactions on Smart Grid 10, no. 3: 2383-2395.