Active and reactive dispatch with minimum control movements

Malakar, Tanmoy; Goswami, S. K.

doi:10.1016/j.ijepes.2012.07.014

Cited by 40 publications

(21 citation statements)

References 25 publications

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“…The goal of optimal reactive power dispatch [7][8][9] is to determine the optimum values of independent variables by optimizing a predefined objective function with respect to the operating bounds of the system. The ORPD problem can be mathematically expressed as a nonlinear constrained optimization problem as follows:…”

Section: The Mathematical Model Of Optimal Reactive Power Dispatchmentioning

confidence: 99%

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Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation

Oo¹

2017

IJEPE

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Abstract:Reactive power dispatch plays a main role in order to provide good facility secure and economic operation in the power system. Optimal reactive power dispatch (ORPD) is a nonlinear optimization problem and has both equality and inequality constraints. ORPD is defined as the minimization of active power loss by controlling a number of variables. Due to complex characteristics of ORPD, heuristic optimization has become an efficient solver. In this paper, particle swarm optimization (PSO) algorithm and MATPOWER toolbox are applied to solve the ORPD problem for distribution system with distributed generating (DG) plant. The proposed method minimizes the active power loss in a practical power system as well as determines the optimal placement of a new installed DG. The practical 41-bus, 6-machine power distribution network of Myingyan area is used to evaluate the performance. The result shows that the adjustment of control variables of distribution power network with a new DG gives a better approach than adjustment only the control variables without DG.

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Section: The Mathematical Model Of Optimal Reactive Power Dispatchmentioning

confidence: 99%

“…The fitness function of ORPD problem presented in this paper is to minimize the total power loss. For each individual, the equality constraints given by (7) and (8) are satisfied by using MATPOWER toolbox.…”

Section: Step By Step Procedures Of Pso Algorithm Combined With Matpomentioning

confidence: 99%

Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation

Oo¹

2017

IJEPE

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“…Due to the daily operation constraints of discrete control devices, frequent and excessive switching operations should be avoided. In [1][2][3][4][5][6], the daily schedule of discrete control devices is optimized based on dynamic programming approach while accounting for constraints of maximum allowable daily switching operation number (MADSON). The minimum total energy loss of daily 24-snapshot is defined as the objective function to evaluate the control performance [5].…”

Section: Introductionmentioning

confidence: 99%

“…The minimum total energy loss of daily 24-snapshot is defined as the objective function to evaluate the control performance [5]. In [6], the total power system operation cost involving fuel cost of generators and switching cost of discrete control devices are considered. However, dynamic programming approach is a very complex nonlinear optimization due to the spatial-temporal coupling.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, this problem is converted into several single Deterministic ORPD (DORPD) problems that can be solved by traditional optimization methods. Another approach considering costs of adjusting discrete control devices is proposed to avoid excessive operations [6,10]. However, in these articles, load uncertainty is not taken into account.…”

Section: Introductionmentioning

confidence: 99%

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A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation

Chen

Yan

Lee³

et al. 2017

Journal of Electrical Engineering and Technology

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-The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

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Managing a hybrid energy smart grid with a renewable energy source

Chakir

Ouadi

Giri

2019

Asian Journal of Control

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The aim of this work is to develop tools for optimal power flow management control in a micro grid (MG). The latter consists of a wind turbine, energy storage system, two gas turbines (GTs), and the main grid. Unlike the traditional approach, which is limited to the distribution of active power, this paper models an electrical system to coordinate and optimize the flow of both active and reactive power using discrete controls. The proposed optimal power distribution strategy has two objectives. First, it aims at forecasting over a time horizon of 24 hours the optimal distribution of the active and reactive power required for each power source connected to the MG. The proposed management incorporates the forecasts of consumption, weather, and tariffs. Second, it aims at reducing the CO 2 emissions rate by optimizing both the operating point of the two GTs and the usage of the storage unit. The proposed optimization problem for the energy management system is solved using the Bellman algorithm through dynamic programming. Its effectiveness is illustrated with various simulations carried out in the Matlab environment. The supremacy of the proposed management algorithm is highlighted by comparing its performance with conventional (restricted) management. KEYWORDSBellman algorithm, distributed generation, dynamic programming, energy management system, hybrid system, optimal power flow DGs generally integrate certain renewable energy production systems. However, regarding the intermittent nature of these non-polluting sources, the introduction of an energy storage system is compulsory. Indeed, this will smooth the power produced and thus avoid grid stability problems. Moreover, this storage system is generally supported by other auxiliary sources to cope with the sharp fluctuations in electricity demand on one hand and renewable production on the other. In this context, the micro grid (MG) considered in this paper consists of:--

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Active and reactive dispatch with minimum control movements

Cited by 40 publications

References 25 publications

Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation

Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation

A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation

Managing a hybrid energy smart grid with a renewable energy source

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