Multi‐objective approach to maximise loadability of distribution networks by simultaneous reconfiguration and allocation of distributed energy resources

Quadri, Imran Ahmad; Bhowmick, Suman; Joshi, Dheeraj

doi:10.1049/iet-gtd.2018.5618

Cited by 34 publications

(27 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Comparison of C1_NL for DGs Operating at 0.90 LPF The evaluation comparison of case 1 (C1_NL) for each alternative in terms of TPE, CPE, and OPE are shown in Table 30. The achieved results are compared with multi-objective hybrid GA and TOPSIS approach in [42] and the multi-objective centric hybrid sensitivity-based approach in [53]. It is observed that the proposed alternative A7 in IDMP during C1_NL is best from the viewpoint of TPE and OPE, whereas A4 outperforms on the basis of CPE.…”

Section: Evaluated Resultsmentioning

confidence: 99%

A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth

et al. 2020

View full text Add to dashboard Cite

The modern distribution networks under the smart grid paradigm have been considered both interconnected and reliable. In grid modernization concepts, the optimal asset optimization across a certain planning horizon is of core importance. Modern planning problems are more inclined towards a feasible solution amongst conflicting criteria. In this paper, an integrated decision-making planning (IDMP) approach is proposed. The proposed methodology includes voltage stability assessment indices linked with loss minimization condition-based approach, and is integrated with different multi-criteria decision-making methodologies (MCDM), followed by unanimous decision making (UDM). The proposed IDMP approach aims at optimal assets sitting and sizing in a meshed distribution network to find a trade-off solution with various asset types across normal and load growth horizons. An initial evaluation is carried out with assets such as distributed generation (DG), photovoltaic (PV)-based renewable DG, and distributed static compensator (D-STATCOM) units. The solutions for various cases of asset optimization and respective alternatives focusing on technical only, economic only, and techno-economic objectives across the planning horizon have been evaluated. Later, various prominent MCDM methodologies are applied to find a trade-off solution across different cases and scenarios of assets optimization. Finally, UDM is applied to find trade-off solutions amongst various MCDM methodologies across normal and load growth levels. The proposed approach is carried out across a 33-bus meshed configured distribution network. Findings from the proposed IDMP approach are compared with available works reported in the literature. The numerical results achieved have validated the effectiveness of the proposed planning approach in terms of better performance and an effective trade-off solution across various asset types.

show abstract

Section: Evaluated Resultsmentioning

confidence: 99%

A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In this paper the maximum voltage limit is considered around 1.0 P.U ± 1% in accordance with substation as a reference, as shown in Equation 31 The lagging PF of DG needs to be within limits and a variation of ± 3% is allowed in DGs operating at lagging PF, one of which corresponds to utility favored 0.9 PF and other is equal to that of TDS load such as 0.85 PF in 33-bus (and 0.82 PF for 69-bus). PF DG,i value ranges from PF DG,i,min → PF − 3% to PF DG,i,max → PF + 3% [48]:…”

Section: Voltage Constraintmentioning

confidence: 99%

“…The DG capacity integrated at bus 'm' in both active and reactive power terms (P DG and Q DG ) must not exceed the maximum value of power counterparts from substation (P SS and Q SS ) as illustrated in Equations (33) and (34) [48]:…”

Section: Active and Reactive Power Limit Of Dgmentioning

confidence: 99%

“…The technical performance indicators (TPI) or technical parameters (TP) with the concerned mathematical relationships, units and aimed objectives are listed in Table 1. The relevant details regarding all mentioned TPIs (or TP) can be found with background details in our previous publications [29,35,[46][47][48]. The terms TPI and TP have been used interchangeably throughout the paper, indicating performance evaluation of various cases and respective scenarios in the proposed approach.…”

Section: Performance Indices For Technical Evaluation (Tpi or Tp)mentioning

confidence: 99%

“…Annual Cost of D-STATCOM (ACD) [37,43] The relevant details of the cost of active power loss (PLC), savings (PLS) and annual investment cost (AIC) can be found in our previous publications [29,35]. The cost of active (CPDG) and reactive power (CQDG) from DG can be found in [29,35,46,48] and an annual cost of D-STATCOM (DSt) can be found in [37,43]. The terms CPIs or CPs have been used interchangeably throughout the paper like their technical counterparts and indicate the performance evaluation of the proposed approach based on cost-related aimed objectives.…”

Section: Performance Indices For Technical Evaluation (Tpi or Tp)mentioning

confidence: 99%

See 2 more Smart Citations

A New Improved Voltage Stability Assessment Index-centered Integrated Planning Approach for Multiple Asset Placement in Mesh Distribution Systems

Kazmi

Shin

2019

Energies

View full text Add to dashboard Cite

This paper offers a new improved voltage stability assessment index (VSAI_B)-centered planning approach, aiming at the attainment of technical and cost related objectives with simultaneous multiple asset deployment in a mesh distribution systems (MDS). The assets such as multiple distributed generation (DG) and distributed static compensator (D-STATCOM) units have been utilized; aiming at voltage stabilization, loss minimization, and associated objectives. The proposed planning approach incorporates expressions of VSAI_B aiming at initial simultaneous assets placement followed by loss minimization conditions (LMC) for appropriate asset sizing, which is further utilized for performance evaluations. The VSAI_B-LMC-based integrated planning approach is applied to configured MDS models such as a 33-bus test distribution system (TDS) for detailed analysis. The performance evaluations with the presented approach have been conducted for different cases along with respective scenarios considering various technical and cost-economic performance metrics. First, three cases referring to multiple DGs sitting and sizing for various power factors have been presented, followed later by two cases of multiple DGs and D-STATCOMs with respective evaluation scenarios. Finally, benchmark analysis is conducted on a 69-bus TDS for validity demonstration of the proposed approach. The comparison of achieved results in comparison with the available literature points out toward the validity and improved performance of the proposed approach.

show abstract

Ɛ‐constraint multiobjective approach for optimal network reconfiguration and optimal allocation of DGs in radial distribution systems using the butterfly optimizer

Thunuguntla

Injeti

2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

In recent days, the optimal allocation of distributed generators (DGs) problem in the distribution system caught several reader's attention to improve the system efficiency, to meet the future load growth. In this article, a multiobjective approach is proposed to determine the optimal locations for DGs, optimal DGs sizes, optimal power factors of DGs in the presence of optimal network reconfiguration to maximize the maximum loadability (λmax), minimize the active power loss and maximize the loading margin factor (λv) of the system. Butterfly Optimization (BO) algorithm is implemented to optimize the desired objectives. The Ɛ‐constraint method is used for multiobjective optimization, spanning tree technique is used for checking the radiality of the system and modified repetitive power flow using radial load flow algorithm is developed for finding theλmax, λv.The proposed approach is tested on 33 bus and 69 bus radial distribution test systems. Four scenarios are considered to achieve the desired objectives and each scenario consists of two cases: optimal allocation of DGs in the initial configured network, optimal allocation of DGs in the optimal reconfigured network. Results suggest that optimal allocation of DGs in scenario 4 gives a better improvement in maximum system loadability, loading margin factor, and active power loss reduction of the system. Obtained results compared with the suitable methods and algorithms that are available in the literature.

show abstract

Multi‐objective approach to maximise loadability of distribution networks by simultaneous reconfiguration and allocation of distributed energy resources

Cited by 34 publications

References 33 publications

A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth

A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth

A New Improved Voltage Stability Assessment Index-centered Integrated Planning Approach for Multiple Asset Placement in Mesh Distribution Systems

Ɛ‐constraint multiobjective approach for optimal network reconfiguration and optimal allocation of DGs in radial distribution systems using the butterfly optimizer

Contact Info

Product

Resources

About