Optimal power flow of a distribution system based on increasingly tight cutting planes added to a second order cone relaxation

Abdelouadoud, Seddik Yassine; Girard, Robin; Neirac, François-Pascal; Guiot, Thierry

doi:10.1016/j.ijepes.2014.12.084

Cited by 60 publications

(62 citation statements)

References 23 publications

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“…(26) and setting fixed the set J st as seen in eq. (27). The final resulting ideal sizing is found in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…An example of this could be high PV production and low loads during the summer season. In order to overcome the challenge of inaccurate convex relaxations [27] presents an AC OPF algorithm that integrates linear cuts implemented in an iterative manner to ensure an exact and feasible relaxation of the power flow equations. In a followup work, this algorithm has then been developed into a multi-temporal one in order to more objectively evaluate the benefits of grid connected storage and other temporally dependent variables in [28].…”

Section: Introductionmentioning

confidence: 99%

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Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

2018

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. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm. Applied Energy, Elsevier, 2018Elsevier, , 219, pp.385-393. <10.1016Elsevier, /j.apenergy.2017 .008>. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm Etta Grover-Silva 1,2 , Robin Girard 1 , George Kariniotakis 1 AbstractThe high variability and uncertainty introduced into modern electrical distribution systems due to decentralized renewable energy generators requires new solutions for grid management and power quality assurance. One of these possible solutions includes grid integrated energy storage. The appropriate size and placement of decentralized storage is highly dependent on purpose of the battery system and expected operational strategy. However, battery operational strategies are difficult to simulate simultaneously during a sizing and placement planning calculation. The motivation of this paper is to propose an algorithm that is capable of integrating sizing, placement and operational strategies of batteries into an Optimal Power Flow (OPF) distribution grid planning tool. The choice of the OPF approach permits to account for grid constraints which is more adapted for grid-connected storage devices compared to other approaches in the state of the art that are based only on an email balance analysis. This paper presents an alternating current (AC) multi-temporal OPF algorithm that uses a convex relaxation of the power flow equations to guarantee exact and optimal solutions with high algorithmic performance. The algorithm is unique and innovative due to the fact that it combines the simultaneous optimization of placement and sizing of storage devices taking into account load curves, photovoltaic (PV) production profiles, and distribution grid power quality constraints. The choice to invest in battery capacity is highly sensitive to the price of battery systems. The investment in battery systems solely for reducing losses an operational costs was proven not to be cost effective, however when battery systems are allowed to buy and sell electricity based on variable market prices they become cost effective. The assumptions used for this study shows that current battery system prices are too high to be cost effective even when allowing battery system market participation.Keywords: Optimal power flow, storage, smart grids, renewable energy, distribution grid planning Nomenclature Parameters η st Charging and discharging efficiency of the battery system P pv,j,t Ideal PV production for node j at time step t S pv,j,t PV maximum apparent power flow at node j V j Voltage maximum at node n V j Voltage minimum at node n c inv stInvestment costs of the battery system for the nominal capacity in e/MWh-day Operations and maintenance costs of using the battery system for the power use in e/MWh-day c e,tPrice of electricity at time step t I max Total capital cost limit of project P ld,j,t Active power load at n...

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“…(26) and setting fixed the set J st as seen in eq. (27). The final resulting ideal sizing is found in Fig.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

2018

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“…In 2015, Abdelouadoud et al [14] presented a second-order cone (SOC) relaxation algorithm to solve OPF based on a branch flow model of a radial and balanced distribution system. In 2016, Baran and Fernandes [15] presented a three-phase OPF, which includes the mutual impedances in order to minimize the losses of system.…”

Section: Uncategorised Mathematical Techniquesmentioning

confidence: 99%

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Khan

Singh

2017

Journal of Engineering

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The exhaustive knowledge of optimal power flow (OPF) methods is critical for proper system operation and planning, since OPF methods are utilized for finding the optimal state of any system under system constraint conditions, such as loss minimization, reactive power limits, thermal limits of transmission lines, and reactive power optimization. Incorporating renewable energy sources optimized the power flow of system under different constraints. This work presents a comprehensive study of optimal power flows methods with conventional and renewable energy constraints. Additionally, this work presents a progress of optimal power flow solution from its beginning to its present form. Authors classify the optimal power flow methods under different constraints condition of conventional and renewable energy sources. The current and future applications of optimal power flow programs in smart system planning, operations, sensitivity calculation, and control are presented. This study will help the engineers and researchers to optimize power flow with conventional and renewable energy sources.

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“…Moreover, we develop an efficient gradient descentbased method to update the predictive model parameter. This method is more efficient than the most popular optimization algorithm used in structured output prediction methods, cutting plane algorithm [6,8,7,1], because it avoids the time-consuming quadratic programming problem of cutting plane algorithm.…”

Section: Our Contributionsmentioning

confidence: 99%

“…We summarize the developed iterative learning algorithm in Algorithm (1). From this algorithm, we can see that the iterations are repeated T times.…”

Section: Iterative Algorithmmentioning

confidence: 99%

Manifold regularization in structured output space for semi-supervised structured output prediction

Jiang

Jia

Sheng

et al. 2015

Neural Comput & Applic

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Structured output prediction aims to learn a predictor to predict a structured output from a input data vector. The structured outputs include vector, tree, sequence, etc. We usually assume that we have a training set of input-output pairs to train the predictor. However, in many real-world applications, it is difficult to obtain the output for a input, thus for many training input data points, the structured outputs are missing. In this paper, we discuss how to learn from a training set composed of some input-output pairs, and some input data points without outputs. This problem is called semisupervised structured output prediction. We propose a novel method for this problem by constructing a nearest neighbor graph from the input space to present the manifold structure, and using it to regularize the structured output space directly. We define a slack structured output for each training data point, and proposed to predict it by learning a structured output predictor. The learning of both slack structured outputs and the predictor are unified within one single minimization problem. In this problem, we propose to minimize the structured loss between the slack structured outputs of neighboring data points, and the prediction error measured by the structured loss. The problem is optimized by an iterative algorithm. Experiment results over three benchmark data sets show its advantage.

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Optimal power flow of a distribution system based on increasingly tight cutting planes added to a second order cone relaxation

Cited by 60 publications

References 23 publications

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Manifold regularization in structured output space for semi-supervised structured output prediction

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