Optimal active and reactive nodal power requirements towards loss minimization under reverse power flow constraint defining DG type

Bouhouras, Aggelos S.; Sgouras, Kallisthenis I.; Gkaidatzis, Paschalis A.; Labridis, Dimitris P.

doi:10.1016/j.ijepes.2015.12.014

Cited by 48 publications

(24 citation statements)

References 32 publications

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“…[110] discussed various system apparatus for hybrid energy system to improve a universal model and found an optimal combination of energy components for supplying rural community. In 2016, Bouhouras et al [111] presented the optimization concerning the placement and sizing of DG units in distribution networks (DNs) for loss minimization. In 2015, Azizipanah-Abarghooee et al [112] presented a probabilistic OPF problem for the system consisting of the thermal units (TUs), wind power plants (WPPs), photovoltaic cell (PV), and combined heat and power (CHP).…”

Section: Distributed Generation (Dg) In 2011 Amanifar Andmentioning

confidence: 99%

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Khan

Singh

2017

Journal of Engineering

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The exhaustive knowledge of optimal power flow (OPF) methods is critical for proper system operation and planning, since OPF methods are utilized for finding the optimal state of any system under system constraint conditions, such as loss minimization, reactive power limits, thermal limits of transmission lines, and reactive power optimization. Incorporating renewable energy sources optimized the power flow of system under different constraints. This work presents a comprehensive study of optimal power flows methods with conventional and renewable energy constraints. Additionally, this work presents a progress of optimal power flow solution from its beginning to its present form. Authors classify the optimal power flow methods under different constraints condition of conventional and renewable energy sources. The current and future applications of optimal power flow programs in smart system planning, operations, sensitivity calculation, and control are presented. This study will help the engineers and researchers to optimize power flow with conventional and renewable energy sources.

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Section: Distributed Generation (Dg) In 2011 Amanifar Andmentioning

confidence: 99%

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Khan

Singh

2017

Journal of Engineering

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“…A mixed‐integer linear programming (MILP) approach is proposed in Wang et al to optimize the DG hosting capacity of the grid while considering the system constraints and the operation of on‐load tap changers (OLTCs) and static VAR compensators (SVCs). A local particle swarm optimization (PSO) variant algorithm is developed in Bouhouras et al to yield loss minimization with the constraint of reverse power flow to slack bus. According to what mentioned above, the following can be expressed: Some of the technical constraints such as the short circuit capacity of the substation switch and the rating transformer should be inserted in the objective function; Different dispersion and arrangement with the same DG penetration level have different impacts on the network and require various settings; Many articles have optimized the DG penetration level only on the rated voltage limits; There is not a distinct and complete model for the hourly variations of the system load types; A probabilistic complete model for the hourly load variations and uncertainties of RESs must be defined to evaluate the allowable generation capacity in the distribution system; Changes of power factor and reactive power of DG have a significant role in the system stability; as a result, they should be entered in the planning objective; And the behavior of compensators and OLTCs must be considered. …”

Section: Introductionmentioning

confidence: 99%

A combined probabilistic modeling of renewable generation and system load types to determine allowable DG penetration level in distribution networks

Naghdi

Shafiyi

Haghifam

2018

Int Trans Electr Energ Syst

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Summary Determining the penetration level of the distributed generation (DG) is an effective tool to site and size DGs in distribution networks. A multiobjective function of optimizing the DG penetration level, subject to constraints including short circuit capacity, voltage limits, transformer capacity, reverse power flow, and congestion of lines, is introduced to minimize the real and reactive losses and to ensure the voltage stability considering the variations of loads, different locations and power factors of DGs, and statistical nature of DG powers especially renewable energy resources. This optimization is performed based on a combined probabilistic modeling of the chronological behavior of wind speed, solar irradiance, and load with different types. The dynamical behavior of the compensators and on‐load tap changers is modeled by optimization subfunctions. An improved bee algorithm is used through conducting searches in the neighboring areas based on a new nonlinear function for a higher fitness and coherency speed.

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“…The methods presented in the above papers [14][15][16][17][18][19][20][21][22][23][24][25] have considerable weaknesses due to simplifications, and the applied models do not cover all constraints or their nonlinear behavior in the objective function. Location, number, and capacity of energy resources, especially renewable resources with variable output (like solar and wind energy), have serious implications that influence the optimization algorithms of DG penetration and placement and tend to spread the interconnection points of DG units.…”

Section: Introductionmentioning

confidence: 99%

Quadratic optimization method for a dual index combination of the penetration level and the dispersion factor of the distributed generation

Naghdi

Shafiyi

Haghifam

2018

Int Trans Electr Energ Syst

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Summary Increasing integration of local generators is a challenge in the planning, design, and operation of the distribution system. The distributed energy resources, especially renewable ones, have caused dispersion of generation units along the feeder. This paper presents a dual index combination of the penetration level and the dispersion factor of distributed generation. Maximum penetration level of distributed generation was determined by a multiobjective function of the proposed dual index. This function has subroutines based on voltage stability, active and reactive power flows, voltage profile limits, and power loss that are restricted by technical constraints associated system with shunt compensator. A limited memory quasi‐Newton trust‐region algorithm was developed to optimize the objective function by using the first‐ and second‐order sensitivities of the nonlinear objective function and a trust region based on the constraints. Two networks were used for testing, and obtained results revealed accuracy and validity of the proposed method.

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Optimal active and reactive nodal power requirements towards loss minimization under reverse power flow constraint defining DG type

Cited by 48 publications

References 32 publications

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

A combined probabilistic modeling of renewable generation and system load types to determine allowable DG penetration level in distribution networks

Quadratic optimization method for a dual index combination of the penetration level and the dispersion factor of the distributed generation

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