Optimal DG allocation and sizing in presence of storage systems considering network configuration effects in distribution systems

Abbasi, Fazel; Hosseini, Mehdi

doi:10.1049/iet-gtd.2015.0367

Cited by 83 publications

(45 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The objective function considers (i) savings in energy costs derived from storing energy at low-priced hours and selling it at peak hours and (ii) savings in network reinforcement thanks to the peak shaving. In [17] the Authors use the non-dominated sorting genetic algorithm for the solution of optimal allocation of DGs in distribution networks considering off-line network reconfiguration. The objective function minimizes resistive losses, energy not supplied (ENS), and the costs associated with DGs.…”

Section: Related Workmentioning

confidence: 99%

Optimal Planning of Distributed Energy Storage Systems in Active Distribution Networks Embedding Grid Reconfiguration

Nick

Cherkaoui

Paolone

2018

IEEE Trans. Power Syst.

151

View full text Add to dashboard Cite

Abstract-In this paper we present a procedure for the optimal siting and sizing of Energy Storage Systems (ESSs) owned, and directly controlled by network operators of Active Distribution Networks (ADNs). The peculiarity of the proposed planning procedure consists in embedding the grid reconfiguration. We use a recently proposed conditionally exact convex Optimal Power Flow (OPF) as the core of the optimization model. We appropriately model the objective function to include both technical and economic aspects, while keeping the exactness of the relaxed convex OPF. In particular, the proposed procedure accounts for the minimization of: voltage-magnitude deviations, feeders'/lines' congestion, cost of supplying loads, and investment costs related to the ESSs. In addition, the seasonal configurations of the grid are determined based on (1) network security constraints, and (2) the minimum resistive losses. The stochasticity of loads and renewable productions also are taken into account. We suitably modeled the ESSs to consider their ability to support the network by both active and reactive powers. Two test cases are used to demonstrate, and quantify, the capabilities of the proposed procedure for providing optimal and feasible solutions. Sets and indicesIndex of lines and buses other than slack bus

show abstract

Section: Related Workmentioning

confidence: 99%

Optimal Planning of Distributed Energy Storage Systems in Active Distribution Networks Embedding Grid Reconfiguration

Nick

Cherkaoui

Paolone

2018

IEEE Trans. Power Syst.

151

View full text Add to dashboard Cite

show abstract

“…The expression of the taste concentration determination value of each fruit fly can be described as (3) and (4). Then calculate the taste concentration of each fruit fly as (5).…”

Section: 2．binary Fruit Fly Optimization Algorithmmentioning

confidence: 99%

Untitled

2017

JAIP

View full text Add to dashboard Cite

Abstract:In this paper, the mathematical model of fault self-healing with the minimum net loss and node voltage deviation is proposed. Then, against the deficiencies of the fruit fly optimization algorithm, combine binary quantum particle swarm algorithm and binary fruit fly optimization algorithm to produce a binary hybrid algorithm for fault self-healing process. Finally, the experiment proved that the algorithm has faster convergence rate and stronger global optimization ability.

show abstract

“…17 In Paliwal et al, 18 the effects of optimal allocation and operation of BESS are analyzed on hybrid power system consisting of wind, hydro plants with battery storage. The effect of network reconfiguration on the sizes and location of BESS is studied in Abbasi and Hosseini and Nick et al 19,20 However, BESS is still an expensive choice for DSO as it adds extra investment and operational cost into the system. Furthermore, selection of depth of discharge (DOD) and charging/discharging cycles affect the overall life cycles of BESS.…”

Section: Introductionmentioning

confidence: 99%

Bilevel optimization framework for impact analysis of DR on optimal accommodation of PV and BESS in distribution system

Sharma

Niazi

Verma

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary The optimal integration of emerging distributed energy resources (DERs) such as energy storage systems and distributed generations (DGs) can improve the performance of distribution systems (DS) significantly. However, increased penetration of DGs may adversely affect the system performance under certain conditions in terms of increased energy losses, voltage violation, power mismatch, reverse power flow etc. The demand response (DR) is one of the operational technologies which may help overcome such issues related to increased DG penetration. In this paper, the role of DR is investigated to optimally accommodate multiple photovoltaics (PV) and battery energy storage systems (BESS) in DS. The problem is formulated as bilevel constrained optimization problem which has been solved using genetic algorithm (GA). The level 1 of optimization determines the optimal nodes and sizes of multiple BESS and PVs which are to be integrated in the system. Thereafter, dispatch of BESS in coordination with DR is optimized in the level 2 optimization. The simulation results highlight the effectiveness of DR in accommodating multiple PV and BESS in DS.

show abstract

Optimal DG allocation and sizing in presence of storage systems considering network configuration effects in distribution systems

Cited by 83 publications

References 24 publications

Optimal Planning of Distributed Energy Storage Systems in Active Distribution Networks Embedding Grid Reconfiguration

Optimal Planning of Distributed Energy Storage Systems in Active Distribution Networks Embedding Grid Reconfiguration

Untitled

Bilevel optimization framework for impact analysis of DR on optimal accommodation of PV and BESS in distribution system

Contact Info

Product

Resources

About