Linear approximated formulation of AC optimal power flow using binary discretisation

Akbari, Tohid; Bina, Mohammad Tavakoli

doi:10.1049/iet-gtd.2015.0388

Cited by 83 publications

(74 citation statements)

References 34 publications

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“…However, AC power flow equations are nonlinear, which increase the complexity of optimization problem. 24,25 In this paper, a linearized model of AC power flow in distribution system is used. 26,27 The linear form of AC power flow equations of distribution network are represented by Equations 9 to 14.…”

Section: Distribution Network Load Flowmentioning

confidence: 99%

“…Equation 13 is linearized by using linearization method presented in Akbari and Bina. 25 Figure 3A shows a typical radial distribution network, while Figure 3B shows a typical 33-bus, 12.6-kV distribution network with Distributed Generation (DG). 26 Local distributed generators and percentages of loads in each bus and three zones for allocating storages are also illustrated in Figure 3B.…”

Section: Distribution Network Load Flowmentioning

confidence: 99%

“…Monte Carlo simulation results vector for transformer availability after scenario reduction is described by X main ωdt . Charge and discharge rates of storage system are represented by (25) and (26). Equation 27 illustrates ESS operation status in charging/discharging or deactivating modes.…”

Section: Power Exchange With Upstream Networkmentioning

confidence: 99%

See 2 more Smart Citations

Expansion planning of energy storages in microgrid under uncertainties and demand response

BiazarGhadikolaei

Shahabi

Barforoushi

2019

Int Trans Electr Energ Syst

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Summary In this paper, a new stochastic framework is proposed to study expansion planning problem of energy storage systems in microgrids, which contain renewable resources and responsive loads. Fluctuations on wind and solar generation, microgrid islanding capability and load's variations have considered as sources of uncertainties, which are modelled by sets of scenarios. Reserve constrains are considered to cover stochastic nature of uncertainties. Optimization problem is prepared as a two‐stage stochastic programming. Due to presence of discrete and continues variables, mathematical formulations of optimization model are implemented as a mixed integer linear programming (MILP) problem, which are solved by CPLEX solver in GAMS software. A distribution network consist of 33 buses with some responsive loads is selected as microgird to examine the effectiveness of the proposed approach. Results demonstrate that installing storage devices in microgrid cause cost reduction while improving system adequacy. The proposed model can be utilized as a planning tool for microgrids operators, which want to make decisions on choosing different types of storages and allocate them in optimum buses, considering stochastic contingencies and demand response programs.

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Section: Distribution Network Load Flowmentioning

confidence: 99%

Section: Distribution Network Load Flowmentioning

confidence: 99%

See 1 more Smart Citation

Expansion planning of energy storages in microgrid under uncertainties and demand response

BiazarGhadikolaei

Shahabi

Barforoushi

2019

Int Trans Electr Energ Syst

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“…AC OPF: The AC OPF model is associated with the AC power network and is based on the natural power flow characteristics of the system [30]. As a result, the results obtained with this type of OPF are more accurate [31].…”

Section: Optimal Power Flow Problemmentioning

confidence: 99%

Analysis of the Effect of Uncertain Renewable Sources on Static Voltage Stability by Using NR-Based DSOPF Model with Adapted IEEE-30 Bus Test System

Gözde

Baydar²,

Taplamacıoğlu³

2018

Balkan Journal of Electrical and Computer Engineering

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This study examines the uncertainty effect of renewable energy resources on the static voltage stability thanks to modeling a specific area of Turkish electricity network by using classic IEEE 30-bus test system. For this purpose, the classic IEEE 30-bus test system is adapted to the Turkish electricity network by using new approach proposed in the study, which is based on the 2015 Turkey real and reactive load curves. In this way, the classic IEEE 30-bus test system is considered a part of Turkish electricity network. The analyses are performed on this model using Newton-Raphson (NR) solution by established three Optimal Power Flow (OPF) studies: dynamic-OPF study without renewable sources, dynamic-OPF study with renewable energy sources having constant power output, Dynamic-Stochastic Optimal Power Flow (DSOPF) study with uncertain renewable energy sources. To take into account the uncertainty effects, Weibull Probability Distribution Function (PDF) using Turkey wind and solar data are used for each month. At the end of the study, it is observed that the integration of uncertain renewable energy sources into the Turkey electricity power system largely decreases both the yearly total generation cost and the reactive power generation.

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“…Although the aforementioned models are not capable of solving practical-constrained models (either complex ED or OPF problems), they have brought new insights into this area of research by showing the importance of solverbased models. Even in some existing linear models for ACOPF problems, [24] and [25], due to the complexity of linearization that highly depends on the approximation techniques, the logical constraints have been neglected. Therefore, the main motivations of proposing the solver-based MINLP models that may fill the existing gap in this area of research can be summarized as (a) the popularity and efficient outcomes of solver-based models in other areas, and (b) the lack of an efficient solver-based model for LCOPF-based problems.…”

Section: Introductionmentioning

confidence: 99%

Logically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model

Pourakbari‐Kasmaei

Mantovani

2018

International Journal of Electrical Power & Energy Systems

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There is increasing evidence of the shortage of solver-based models for solving logically-constrained AC optimal power flow problem (LCOPF). Although in the literature the heuristic-based models have been widely used to handle the LCOPF problems with logical terms such as conditional statements, logical-and, logical-or, etc., their requirement of several trials and adjustments plagues finding a trustworthy solution. On the other hand, a welldefined solver-based model is of much interest in practice, due to rapidity and precision in finding an optimal solution. To remedy this shortcoming, in this paper we provide a solver-friendly procedure to recast the logical constraints to solver-based mixed-integer nonlinear programming (MINLP) terms. We specifically investigate the recasting of logical constraints into the terms of the objective function, so it facilitates the pre-solving and probing techniques of commercial solvers and consequently results in a higher computational efficiency. By applying this recast method to the problem, two sub-power-and sub-function-based MINLP models, namely SP-MINLP and SF-MINLP, respectively, are proposed. Results not only show the superiority of the proposed models in finding a better optimal solution, compared to the existing approaches in the literature, but also the effectiveness and computational tractability in solving large-scale power systems under different configurations.

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Linear approximated formulation of AC optimal power flow using binary discretisation

Cited by 83 publications

References 34 publications

Expansion planning of energy storages in microgrid under uncertainties and demand response

Expansion planning of energy storages in microgrid under uncertainties and demand response

Analysis of the Effect of Uncertain Renewable Sources on Static Voltage Stability by Using NR-Based DSOPF Model with Adapted IEEE-30 Bus Test System

Logically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model

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