Hybrid genetic multi objective/fuzzy algorithm for optimal sizing and allocation of renewable DG systems

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.

“…With regard to the voltage stability index expressed in the literature (Appendix A), the voltage stability index of each bus is obtained as below (from ):

{VS}_{m} = {|V_{n}|}^{4} - 4 ((), P_{normalm - 1} r_{m} Q_{normalm - 1} x_{m}) {|V_{n}|}^{2} - 4 {({normalQ}_{m - 1} {normalr}_{normalm} - {normalP}_{m - 1} {normalx}_{normalm})}^{2}, normalm = 1, 2, \dots, normalN .

…”

Section: Objective Function and Its Constraintsmentioning

confidence: 99%

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

“…Abdel‐mawgoud et al, presented a hybrid approach based on moth‐flame optimization algorithm and loss sensitivity factor to allocate renewable energy‐based DG in RDS. A multiobjective GA algorithm, has been proposed for the optimal allocation of PV and wind renewable energy sources and its effect on voltage stability and critical loading margins are analyzed. Kayal and Chanda have presented a multiobjective particle swarm optimization algorithm to site solar and wind DGs for loss minimization and voltage stability improvement.…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of renewable DGs in a radial distribution system based on new voltage stability index

Parihar

Malik

2020

Summary Optimal siting and sizing of renewable DGs can provide a clean and sustainable solution for the smart distribution system. In this article, solar photovoltaic (SPV) and wind turbine generating (WTG) are considered as distribution generation (DG) resources. A methodology to determine the optimal location based on a new voltage stability index (VSI) followed by optimal power rating of renewable DGs based on PSO algorithm in the radial distribution system is proposed. The effectiveness of the method is tested and validated on IEEE 34‐bus and 69‐bus systems for different load levels. The optimal allocation of SPV‐DG and WTG‐DG is also carried out in the presence of load growth and composite load model. The method accounts for the change in long‐term load profile in the planning stage to improve power system performance. The significant reduction in power losses with improved voltage profile and remarkable annual energy loss saving is noticed for the renewable DGs. Further, the results obtained are compared with the other nature‐inspired algorithms to highlight the superiority of the proposed method. The analysis demonstrates that the penetration of renewable DGs allows the system to have load growth for few more years without violating the system constraints. The statistical analysis is also carried out.

“…Nowadays, there is a considerable growth in the integration of the distributed generation (DG) units with their new technologies and many types of flexible alternating current transmission systems (FACTS) into the distribution systems around the world . The advantages of utilizing DGs involve technical, environmental, and economic benefits such as impacts on line congestion, voltage profile, system stability, protection, power loss, power quality, environmental emissions, and investment costs . In deregulated distribution systems, the operators have to provide customers with suitable quality and security under the existing system configuration, available power capacity, and uncertainties such as the variable power outputs of the renewable resources and the load variations .…”

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

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.