Comprehensive framework for capacitor placement in distribution networks from the perspective of distribution system management in a restructured environment

Karimi, Hossein; Dashti, Reza

doi:10.1016/j.ijepes.2016.02.025

Cited by 20 publications

(14 citation statements)

References 28 publications

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“…Reduction of loss not only improves network efficiency but also decreases environmental pollutants by decrease in extra generation. Different solutions have been introduced for loss reduction in distribution network such as network reconfiguration [21], [22], installation of capacitor banks [23], integration of distributed generation and or storages [24], and network reinforcement [25], [26]. Often distribution companies redesign their network in order to decrease the network losses over the planning horizon.…”

Section: Indicesmentioning

confidence: 99%

An A-Posteriori Multi-Objective Optimization Method for MILP-Based Distribution Expansion Planning

2020

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Distribution expansion planning (DEP) is a mixed integer nonlinear programming (MINLP) problem and contains various options to be considered where the nonlinearity makes it difficult to solve. Over the years, different heuristic and classical optimization methods have been introduced to solve this problem. In a few classical optimization methods, this problem has been linearized. In this contribution, an-constraint based multi-objective method was proposed for mixed integer linear programming (MILP) based DEP model considering network loss. Operational network loss was linearized and incorporated in the model, then the operational loss cost was obtained by modeling the production cost. In order to model the production cost, the well-known supply price curve was considered, where the price of energy for each loading condition was obtained based on a linear model. Using the-constraint method, the Pareto optimal front was formed, which provides the decision maker with a range of solutions showing relationship among conflicting objectives. Then, a Fuzzy satisfying method was utilized to obtain the best compromised solution. Simulations were performed on an 18-node primary distribution network. Results showed the effectiveness of the proposed method for the MILP-based multi-objective DEP models. INDEX TERMS Mixed-integer linear programming, distribution expansion planning, power market, operational network loss, multi-objective optimization,-constraint optimization, a-posteriori. Feeder sections of i-th type B ij Alternative sizes of j-th branch of i-th type LC

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Section: Indicesmentioning

confidence: 99%

An A-Posteriori Multi-Objective Optimization Method for MILP-Based Distribution Expansion Planning

2020

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“…From a financial point of view, the minimum of total annual cost can also be the objective function, including the total investment and operational costs [4,5,6]. [7] based on the real-time changing load, annual growth rate of load and the active-reactive price varying over time establishes a novel objective function of comprehensive costs more according with actual conditions. The constraints of this problem contain power balance constraints, VAR compensation limits, generator output limits and voltage limits etc.…”

Section: Var Configuration Optimizationmentioning

confidence: 99%

“…The constraints of this problem contain power balance constraints, VAR compensation limits, generator output limits and voltage limits etc. Based on Lagrange multiplier method, the bus voltage limits often are added to the objective function as cross-border penalty function, so as to enhance the overall optimal flexibility and avoid the infeasible solutions [5,7].…”

Section: Var Configuration Optimizationmentioning

confidence: 99%

A Review of Reactive Power Optimization in Distribution Network

Liu¹,

Liu²

2017

dtetr

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Abstract. The reactive power (VAR) optimization in distribution network is one of important measures for loss reduction, voltage profile improvement and power factor correction. This paper classifies the VAR optimization into VAR configuration optimization and VAR operation optimization based on different implementation phases. Meantime, the VAR optimal operation is sorted by static VAR optimization and dynamic VAR optimization. Afterward the article summarizes the research situation of VAR optimization. Eventually the paper presents the future work of VAR optimization according to the research status.

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“…A combination of genetic algorithm and fuzzy multi-objective approach was proposed in [4] aiming at optimal CBs placement to improve the substation power factor, reduce the energy losses, and decrease the burden on the substation. In [5], a comprehensive objective function was proposed for CBs placement to maximize the net saving from the perspective DISCO manager using particle swarm optimization (PSO). Another approach using PSO was proposed in [6] to find the optimal location and number of CBs while wind-based DG units were taken into account aiming at reducing the power losses and enhancing the voltage profile.…”

Section: Introductionmentioning

confidence: 99%

“…This table shows the works that take advantage of each technology (marked with X) to maximize the efficiency of EDSs. It is worth noting that, in [1][2][3][4][5][14][15][16], and [20][21][22][23][24], the environmental issues were disregard, while [13] and [17] are the works that the environmental issues were taken into account.…”

Section: Introductionmentioning

confidence: 99%

Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems

et al. 2017

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This paper presents an integrated planning framework to optimally determine the location and allocation of renewable-based distributed generation (DG) units, energy storage systems (ESSs), and capacitor banks (CBs). This planning aim at improving the performance of electrical distribution systems (EDSs). In the proposed model, the cost of energy delivered by the substation and the investment costs are minimized. The environmental aspects are taken into account to obtain an efficient environmentally committed plan. The uncertainties due to PV generation and demand profile are considered via external uncertainty indexes in a deterministic environment. The proposed model is a mixed-integer nonlinear programming (MINLP) problem, which is recast to a mixed-integer linear programming (MILP) problem using appropriate linearization techniques. This approximated MILP model is implemented in the mathematical language AMPL, while the commercial solver CPLEX is used to obtain the global optimal solutions. The proposed model is validated by testing on a medium voltage distribution system with 135 nodes under different conditions and topologies.

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Comprehensive framework for capacitor placement in distribution networks from the perspective of distribution system management in a restructured environment

Cited by 20 publications

References 28 publications

An A-Posteriori Multi-Objective Optimization Method for MILP-Based Distribution Expansion Planning

An A-Posteriori Multi-Objective Optimization Method for MILP-Based Distribution Expansion Planning

A Review of Reactive Power Optimization in Distribution Network

Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems

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