Power distribution network expansion scheduling using dynamic programming genetic algorithm

Carrano, Eduardo G.; Cardoso, Rodrigo T. N.; Takahashi, Ricardo H. C.; Fonseca, Carlos M.; Neto, Oriane M.

doi:10.1049/iet-gtd:20070174

Cited by 37 publications

(16 citation statements)

References 15 publications

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“…So GA (genetic algorithm) [25][26] is used to obtain the best tap positions suitable for the uncertain circumstance at each time segment. The binary code is shown in Fig.…”

Section: Pdipm and Gamentioning

confidence: 99%

Optimal Coordination of Intermittent Distributed Generation with Probabilistic Power Flow

Xing¹,

Cheng²,

Zhang³

2015

Journal of Electrical Engineering and Technology

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-This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active management techniques such as IDG curtailment, on-load tap changer (OLTC) tap adjusting, voltage regulator (VR) tap adjusting, shunt capacitors compensation and so on are fully considered. Genetic algorithm and Primal-Dual Interior Point Method (PDIPM) is used for the model solving. Point estimate method is used to simulate the uncertainties. Different scenarios are selected for the IDG accommodation capability investigation under different active management schemes. Finally a modified IEEE 123 case is used to testify the proposed accommodation model, the results show that the active management can largely increase the IDG accommodation and penetration.

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“…So GA (genetic algorithm) [25][26] is used to obtain the best tap positions suitable for the uncertain circumstance at each time segment. The binary code is shown in Fig.…”

Section: Pdipm and Gamentioning

confidence: 99%

Optimal Coordination of Intermittent Distributed Generation with Probabilistic Power Flow

Xing¹,

Cheng²,

Zhang³

2015

Journal of Electrical Engineering and Technology

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“…Thus the following process realizations will be analyzed in period 1: (3,4,8), (3,5,7), (3,5,8), (3,5,9), (3,6,7), (3,6,8), (3,6,9). Next, probability distributions for each criterion and each state y 1 ∈ Y 1 are generated.…”

Section: Numerical Examplementioning

confidence: 99%

“…Unfortunately, due to the well known "curse of dimensionality", the possibility of applying this approach in practice doesn't occur very often. Some attempts to overcome the curse of dimensionality are worth noting; they are based on artificial intelligence-for instance ant colonies [25] or genetic algorithms approaches [6].…”

Section: Introductionmentioning

confidence: 99%

Interactive procedure for a multiobjective stochastic discrete dynamic problem

Nowak

Trzaskalik

2012

J Glob Optim

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Multiple objectives and dynamics characterize many sequential decision problems. In the paper we consider returns in partially ordered criteria space as a way of generalization of single criterion dynamic programming models to multiobjective case. In our problem evaluations of alternatives with respect to criteria are represented by distribution functions. Thus, the overall comparison of two alternatives is equivalent to the comparison of two vectors of probability distributions. We assume that the decision maker tries to find a solution preferred to all other solutions (the most preferred solution). In the paper a new interactive procedure for stochastic, dynamic multiple criteria decision making problem is proposed. The procedure consists of two steps. First, the Bellman principle is used to identify the set of efficient solutions. Next interactive approach is employed to find the most preferred solution. A numerical example and a real-world application are presented to illustrate the applicability of the proposed technique.

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“…Otherwise, there will be a risk of low voltage or even voltage collapse [16]. The traditional control and management mode of power distribution network are passive [17]. Its scheduling method is outdated and automation level is low [18].…”

Section: Introductionmentioning

confidence: 99%

A Flexible Load Control Strategy for Distribution Network to Reduce the Line Losses and to Eliminate the Transmission Congestion

Wang

Hu²,

Shen³

et al. 2017

Mathematical Problems in Engineering

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There are many uncertain factors in the modern distribution network, including the access of renewable energy sources and the heavy load level. The existence of these factors has brought challenges to the stability of the power distribution network, as well as increasing the risk of exceeding transmission capacity of distribution lines. The appearance of flexible load control technology provides a new idea to solve the above problems. Air conditioners (ACs) account for a great proportion of all loads. In this paper, the model of dispatching AC loads in the regional power grid is constructed, and the direct load control (DLC) method is adopted to reduce the load of ACs. An improved tabu search technique is proposed to solve the problem of network dispatch in distribution systems in order to reduce the resistive line losses and to eliminate the transmission congestion in lines under normal operating conditions. The optimal node solution is obtained to find the best location and reduction capacity of ACs for load control. To demonstrate the validity and effectiveness of the proposed method, a test system is studied. The numerical results are also given in this article, which reveal that the proposed method is promising.

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Power distribution network expansion scheduling using dynamic programming genetic algorithm

Cited by 37 publications

References 15 publications

Optimal Coordination of Intermittent Distributed Generation with Probabilistic Power Flow

Optimal Coordination of Intermittent Distributed Generation with Probabilistic Power Flow

Interactive procedure for a multiobjective stochastic discrete dynamic problem

A Flexible Load Control Strategy for Distribution Network to Reduce the Line Losses and to Eliminate the Transmission Congestion

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