Deployment of Distributed Generation with D-FACTS in Distribution System: A Comprehensive Analytical Review

Gupta, Atma Ram; Kumar, Ashwani

doi:10.1080/03772063.2019.1644206

Cited by 30 publications

(10 citation statements)

References 146 publications

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“…For each bus that has a load, there are two equations shown by Equations ( 22) and (23). For each bus with controlled voltage, there is an equation that is specified by Equation (22). By extending Equations ( 22) and ( 23) in the form of the Taylor series near the initial estimate and by ignoring sentences with higher degrees, the following set of linear equations is obtained: .…”

Section: Problem-solving Methodsmentioning

confidence: 99%

Improving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices

Dashtdar

Bajaj

Hosseinimoghadam

et al. 2021

Int Trans Electr Energ Syst

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Distribution networks have problems such as an increase in active losses, overload on distribution substations, voltage drop, decrease in network reliability, increase in load unbalance and unbalance in line current due to variable characteristics in terms of load consumption. In this article, to reduce losses, improve the voltage profile and increase the reliability of the system, the UPQC (Unified Power Quality Controller) optimal placement and reconfiguration method have been used in the distribution network. The two objective functions of losses and the mean voltage deviation are defined by considering the reliability indices. Since the reconfiguration of distribution networks is a large-scale nonlinear hybrid optimization problem with several constraints, the genetic algorithm combines genes including key numbers and UPQC location, UPQC series power size, UPQC shunt power size used to solve the problem. The proposed method is implemented in three steps on IEEE 33-bus and 69-bus standard networks by considering the load model List of Symbols and Abbreviations: agr, agriculture load; com, commercial load; C i , number of loads connected to the ith bus; D, load coefficient; F1, F2, objective functions; fraci,k, the amount of load lost in the ith bus; gen, general load; I EAF_a , main current component of a phase; Ii, current of feeders; Ii, input current to bus i; ind, industrial load; i p , reference current phase component for active power; i q , reference current phase component for reactive power; I ref_a , current reference of the a phase; I s , source current; n, number of buses; P 0i , Q 0i , active and reactive power at a per-unit voltage of bus i; Pi, Q i , active and reactive power passing through branch i; P ref , reference active power; P rk , probability of losing the ith bus; P total,loss , total active network losses; Q a , reactive power of a phase; Q L , reactive power demand; res, residential load; ri, resistance of branch i; S, tnumber of UPQCs installed in the network; V DC_ref , treference DC voltage; V i , voltage of Bus i; V trans_a , effective value of the voltage of the a phase; V s , source voltage; Y ij , admittance matrix; Z s , source impedance; Δδ i , changes in voltage angle of bus, changes in voltage magnitude of bus i; ΔP i , changes in active power of bus i; ΔQ i , changes in reactive power of bus i; γ, τ, active and reactive charge change coefficient; ACS, ant colony search; ACIFi, average fixed number of each customer (1/a) per year; AENS, average energy not supplied per customer; AI

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Section: Problem-solving Methodsmentioning

confidence: 99%

Improving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices

Dashtdar

Bajaj

Hosseinimoghadam

et al. 2021

Int Trans Electr Energ Syst

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“…Before DGs are added to the network, the grid needs to meet the total network demand (load plus losses). With PV-DGs, the amount of power brought in from the grid can be cut down, and so can GHG emissions, which can be measured by, 𝐺𝐻𝐺 𝑒𝑚 = (𝐶𝑂 2 + 𝑁𝑂 𝑥 + 𝑆𝑂 2 ) × 𝑃 𝑠𝑠 (10) where 𝐺𝐻𝐺 𝑒𝑚 is the total GHG emission by the grid-associated conventional power sources, 𝐶𝑂 2 , 𝑁𝑂 𝑥 and 𝑆𝑂 2 are the most accounted emissions [37]; 𝑃 𝑠𝑠 is the total active power demand (includes load and losses) on the substation/grid.…”

Section: Greenhouse Gas Emissionmentioning

confidence: 99%

“…Some researchers also focused on reactive power (VAr) compensation devices in EDSs, such as capacitor banks (CBs), short and series reactors, and custom power devices, such as automatic voltage regulators (AVR), tap-changing transformers, distribution static compensator (DSTATCOM), unified power quality controller (UPQC), and static synchronous series compensator (SSSC), etc. [10]. Most EDSs are radial and have a low voltage profile, so dynamic VAr compensation is needed to keep operations running smoothly.…”

Section: Introductionmentioning

confidence: 99%

Northern Goshawk Optimization for Optimal Allocation of Multiple Types of Active and Reactive Power Distribution Generation in Radial Distribution Systems for Techno-Environmental Benefits

2023

IJIES

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Radial distribution systems (RDSs) can work better from a technical, economic, and environmental point of view if they have the right mix of renewable energy-based distribution generation (DG) and reactive power sources like and distribution-static compensator (DSTATCOM). In this paper, the Northern Goshawk Optimization (NGO), a new meta-heuristic that mimics the hunting behaviour of the northern goshawk, is introduced as a way to figure out where and how big different types of active and reactive power DGs in RDSs should be. For the suggested multi-objective function, NGO is used to find the best places and sizes for photovoltaic systems (PVs), wind turbine systems (WTs), and DSTATCOMs. The main goals of the suggested method are to reduce distribution losses, improve the voltage profile, increase the voltage stability margin, and reduce greenhouse gas (GHG) emissions. Five different case studies are simulated to figure out how well the suggested method works with computers. Simulations use IEEE 33-bus feeder. When compared to the literature and other heuristic algorithms, the results show that NGO works. The computational efficiency of NGO is compared for four cases: (i) only PV ((ii) only WT (iii) only DSTATCOM and (vi) simultaneous PV, WT and DSTATCOM allocation. The results also show that the proposed NGO much efficient than other algorithms and also improves all techno-environmental factors and RDS performance in a big way.

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Qiuye Sun . in the distribution grid [2]. D-FACTS include numerous controllers such as Distribution Static Var Compensator (D-SVC), unified power quality conditioner (UPQC), and Distributed static compensator (DSTATCOM) [3].…”

Section: Introduction a Literature Surveymentioning

confidence: 99%

Stochastic Optimal Planning of Distribution System Considering Integrated Photovoltaic-Based DG and DSTATCOM Under Uncertainties of Loads and Solar Irradiance

et al. 2021

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Optimal planning of integration the Photovoltage Distributed Generation (PV-DG) and DSTATCOM is a crucial task due to the stochastic variations of PV output power and the load demand which are related to solar irradiance variations and the activities of the customers, respectively. In this article, the optimal planning problem of the PV-DG and DSTATCOM system is solved. The proposed model considers the uncertainties of the solar irradiance and the load demand for a multi-objective function, including the cost reduction, the voltage profile, and stability index improvement. Modified Ant Lion Optimizer (MALO) is proposed to enhance the basic ALO searching ability using two strategies. The first strategy is based on Levy Flight Distribution (LFD) to strengthen the exploration of the algorithm and avoid the premature of the basic ALO. In contrast, the second strategy is based on updating the solutions in a spiral orientation to improve the exploitation of the algorithm. The IEEE 69-bus and 118-bus radial distribution systems are used to demonstrate the effectiveness of the proposed method, and the yielded simulations are compared with the basic ALO and other well-known optimization techniques for power loss minimization under deterministic conditions. The simulation results demonstrate that the techno-economic benefits can be increased considerably by optimal inclusion of two PV-DGs and DSTATCOMs compared with a single system.

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Deployment of Distributed Generation with D-FACTS in Distribution System: A Comprehensive Analytical Review

Cited by 30 publications

References 146 publications

Improving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices

Improving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices

Northern Goshawk Optimization for Optimal Allocation of Multiple Types of Active and Reactive Power Distribution Generation in Radial Distribution Systems for Techno-Environmental Benefits

Stochastic Optimal Planning of Distribution System Considering Integrated Photovoltaic-Based DG and DSTATCOM Under Uncertainties of Loads and Solar Irradiance

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