PSO and Improved BSFS Based Sequential Comprehensive Placement and Real-Time Multi-Objective Control of Delta-Connected Switched Capacitors in Unbalanced Radial MV Distribution Networks

Su, Xiangjing; Masoum, Mohammad A. S.; Wolfs, Peter

doi:10.1109/tpwrs.2015.2398361

Cited by 43 publications

(23 citation statements)

References 25 publications

(68 reference statements)

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“…• Benefits: Easy to code, efficient computation time and better convergence than GA. [61,65], [67]]; CRU (C) [76,88]; NTR (D) [92,93].…”

Section: Meta-heuristics (Mh) Methodsmentioning

confidence: 99%

“…Planning components associated to each PT in reviewed work are designated with symbols A, B, C, and D, respectively, also shown in an overarching diagram as in Figure 1. The color coding allocated to each PT in the arrangement order includes green (A) for DGP ; orange (B) for VPQ [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70]; blue (C) for CRU [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88][89] and purple (D) for NTR [90][91][92][93][94][95][96][97][98][99][100]. It is important to note that date o...…”

Section: Composite Review Of Mop Techniques With Taxonomymentioning

confidence: 99%

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Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN) needs to consider choices, primarily distributed generation (DG), network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP) in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs) based on mult-objective optimizations (MOOs) in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT) have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at the multi-objective-based frameworks, are also presented in this paper.Keywords: active distribution network (ADN); distributed generation (DG); distributed energy resources (DERs); distribution network planning (DP); multi-objective optimization (MOO); multi-criteria decision analysis (MCDA); distributed generation placement (DGP); volt-ampere reactive power (VAR) compensation and power quality (VPQ); component reinforcement and up gradation (CRU); network (distribution) topology change and reconfiguration (NTR); planning techniques (PT); multiple objective planning (MOP); multi-objective planning techniques (MOPTs); future distribution networks (FDNs)

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“…• Benefits: Easy to code, efficient computation time and better convergence than GA. [61,65], [67]]; CRU (C) [76,88]; NTR (D) [92,93].…”

Section: Meta-heuristics (Mh) Methodsmentioning

confidence: 99%

Section: Composite Review Of Mop Techniques With Taxonomymentioning

confidence: 99%

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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“…The probability function, , in (12), is calculated as a random number (between 0 and 1) each time based on the historical probing performance. It is utilized to alternate the two operators in (12). The details are given in the next sub-section.…”

Section: Mutation Based On the Elite Individualsmentioning

confidence: 99%

“…According to [9]- [12], the optimization techniques to solve MOPF can be categorized into two groups: (i) mathematical programming methods and (ii) heuristic algorithms.…”

Section: Introductionmentioning

confidence: 99%

A Judicious Decision-Making Approach for Power Dispatch in Smart Grid Using a Multiobjective Evolutionary Algorithm Based on Decomposition

Xiao

Sutanto

Muttaqi

et al. 2020

IEEE Trans. on Ind. Applicat.

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Multiobjective evolutionary algorithm based on decomposition (MOEA/D) is an efficient mathematical strategy for solving multiobjective optimization problems. However, the MOEA/D algorithm has not yet been widely used on the multiobjective optimal power flow (MOPF) problems, which consider several conflicting objectives with varying tradeoff levels. This article proposes a novel differential evolution (DE) strategy based on the MOEA/D framework to quickly determine a set of optimal solutions of MOPFs, in the objective space formed from the different objectives, such as the most optimal economic dispatch, the least environmental emission objectives, and the minimum transmission losses, while considering the power system constraints. A judicious decision can be made by the user from the set of optimal solutions of the MOPF associated with the weight vectors representing the tradeoff levels of the different objectives. For improved performance, two aggregate objective functions, a load flow operator and a selfadaptive DE strategy work cooperatively: 1) to improve the weak convergence of the MOEA/D and to achieve a better decision speed; 2) to obtain more accurate optimal solutions even under non-convex conditions; 3) to ensure that the power system constraints are taken into account; 4) to integrate the above features into a fast and efficient algorithm. The proposed algorithm has been validated using the IEEE 30-bus system and a revised 33-bus radial system added to one node of the 30-bus system. The simulation results show that the proposed algorithm can provide a good accuracy and can converge to a set of optimal solutions of the MOPFs. Disciplines Disciplines Engineering | Science and Technology StudiesAbstract-Multi-objective evolutionary algorithm based on decomposition (MOEA/D) is an efficient mathematical strategy for solving multi-objective optimization problems. However, the MOEA/D algorithm has not yet been widely used on the multiobjective optimal power flow (MOPF) problems, which considers several conflicting objectives with varying trade-off levels. This paper proposes a novel differential evolution (DE) strategy based on the MOEA/D framework to quickly determine a set of optimal solutions of MOPFs, in the objective space formed from the different objectives, such as the most optimal economic dispatch, the least environmental emission objectives, and the minimum transmission losses, while considering the power system constraints. A judicious decision can be made by the user from the set of optimal solutions of the MOPF associated with the weight vectors representing the trade-off levels of the different objectives. For improved performance, two aggregate objective functions, a load flow operator and a self-adaptive DE strategy work cooperatively: 1) to improve the weak convergence of the MOEA/D and to achieve a better decision speed; 2) to obtain more accurate optimal solutions even under non-convex conditions; 3) to ensure that the power system constraints are taken into account; 4) to integrate the ab...

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“…In this section, the basic knowledge of PSO is briefly introduced . For PSO, a particle swarm with M particles is randomly generated in an N‐dimensional space.…”

Section: Combined Optimization For Frequency Regulationmentioning

confidence: 99%

Coordinated optimization of vehicle-to-grid control and load frequency control by considering statistical properties of active power imbalance

Yang

Dong

et al. 2018

Int Trans Electr Energ Syst

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Summary The significantly increased penetration level of electric vehicles (EVs) that causes a great challenge for the vehicle‐to‐grid (V2G) system and power system influences the performance of the systems. To achieve some good performance of the V2G and power system, this paper proposes a co‐optimizing method based on the operation of V2G control and load frequency control (LFC). Compared with the existed results, the proposed method that deals with dead bands and statistical properties of power imbalance in power system establishes a model of two‐area V2G system containing the nonlinear features in the beginning. Based on the proposed model, the composition of power imbalance is analyzed, while the Latin hypercube sampling (LHS) is employed to obtain active power imbalance scenarios caused by the probability distribution of load disturbance and renewable energy source in each area. Because the active power imbalance scenarios are considered and the cost function is constructed by the integration of integral time multiply absolute error (ITAE), the droop coefficients of V2G control and proportional‐integral (PI) controllers of LFC that are co‐optimized simultaneously maintain the demand of holding state of charge (SOC) from EV owners and frequency regulation of V2G system. Finally, simulation results show the validity and advantage of the proposed method.

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PSO and Improved BSFS Based Sequential Comprehensive Placement and Real-Time Multi-Objective Control of Delta-Connected Switched Capacitors in Unbalanced Radial MV Distribution Networks

Cited by 43 publications

References 25 publications

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

A Judicious Decision-Making Approach for Power Dispatch in Smart Grid Using a Multiobjective Evolutionary Algorithm Based on Decomposition

Coordinated optimization of vehicle-to-grid control and load frequency control by considering statistical properties of active power imbalance

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