An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum

Gil-González, Walter; Molina-Cabrera, Alexander; Montoya, Oscar Danilo; Grisales-Noreña, Luis Fernando

doi:10.3390/app10217681

Cited by 11 publications

(7 citation statements)

References 28 publications

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“…Based on the aforementioned problems with conventional metaheuristic approaches, we propose a hybrid DSCA-SOCP programming to solve the studied problem using a master-slave optimization strategy, where the master stage is entrusted with determining the subset of nodes where DGs will be located, and the slave stage solves the resulting optimal power flow problem to determine their optimal sizes. The main advantage of the proposed approach is that the SOCP programming ensures the global optimal solution for each nodal combination provided by the DSCA [18], which implies that if the best subset of nodes is identified by the master stage, the global optimal solution for the problem of the optimal placement and sizing of DGs in AC distribution networks will be guaranteed (this will be confirmed in the results section) [19].…”

Section: Introductionmentioning

confidence: 60%

A Hybrid Approach Based on SOCP and the Discrete Version of the SCA for Optimal Placement and Sizing DGs in AC Distribution Networks

et al. 2020

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This paper deals with the problem of the optimal placement and sizing of distributed generators (DGs) in alternating current (AC) distribution networks by proposing a hybrid master–slave optimization procedure. In the master stage, the discrete version of the sine–cosine algorithm (SCA) determines the optimal location of the DGs, i.e., the nodes where these must be located, by using an integer codification. In the slave stage, the problem of the optimal sizing of the DGs is solved through the implementation of the second-order cone programming (SOCP) equivalent model to obtain solutions for the resulting optimal power flow problem. As the main advantage, the proposed approach allows converting the original mixed-integer nonlinear programming formulation into a mixed-integer SOCP equivalent. That is, each combination of nodes provided by the master level SCA algorithm to locate distributed generators brings an optimal solution in terms of its sizing; since SOCP is a convex optimization model that ensures the global optimum finding. Numerical validations of the proposed hybrid SCA-SOCP to optimal placement and sizing of DGs in AC distribution networks show its capacity to find global optimal solutions. Some classical distribution networks (33 and 69 nodes) were tested, and some comparisons were made using reported results from literature. In addition, simulation cases with unity and variable power factor are made, including the possibility of locating photovoltaic sources considering daily load and generation curves. All the simulations were carried out in the MATLAB software using the CVX optimization tool.

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Section: Introductionmentioning

confidence: 60%

A Hybrid Approach Based on SOCP and the Discrete Version of the SCA for Optimal Placement and Sizing DGs in AC Distribution Networks

et al. 2020

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“…Remark 1. The expression (1), related to the objective function, is a quadratic function associated with the sums of the products between voltage variables; this is convex due to the properties associated with the matrix of conductance, G which is positive semidefinite [23,24]. Remark 2.…”

Section: Exact Minlp Modelmentioning

confidence: 99%

A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks

et al. 2021

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The problem of the optimal placement and dimensioning of constant power sources (i.e., distributed generators) in electrical direct current (DC) distribution networks has been addressed in this research from the point of view of convex optimization. The original mixed-integer nonlinear programming (MINLP) model has been transformed into a mixed-integer conic equivalent via second-order cone programming, which produces a MI-SOCP approximation. The main advantage of the proposed MI-SOCP model is the possibility of ensuring global optimum finding using a combination of the branch and bound method to address the integer part of the problem (i.e., the location of the power sources) and the interior-point method to solve the dimensioning problem. Numerical results in the 21- and 69-node test feeders demonstrated its efficiency and robustness compared to an exact MINLP method available in GAMS: in the case of the 69-node test feeders, the exact MINLP solvers are stuck in local optimal solutions, while the proposed MI-SOCP model enables the finding of the global optimal solution. Additional simulations with daily load curves and photovoltaic sources confirmed the effectiveness of the proposed MI-SOCP methodology in locating and sizing distributed generators in DC grids; it also had low processing times since the location of three photovoltaic sources only requires 233.16s, which is 3.7 times faster than the time required by the SOCP model in the absence of power sources.

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“…Physical limits and other considerations are included in the set of constrains. In this way, we derive a convex problem to be solved by any optimization technique [45][46][47]. The solution is a sequence of control signals in time, the first of which is applied to the power system.…”

Section: The Enhanced Time-delay Compensatormentioning

confidence: 99%

Latencies in Power Systems: A Database-Based Time-Delay Compensation for Memory Controllers

et al. 2021

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Time-delay is inherent to communications schemes in power systems, and in a closed loop strategy the presence of latencies increases inter-area oscillations and security problems in tie-lines. Recently, Wide Area Measurement Systems (WAMS) have been introduced to improve observability and overcome slow-rate communications from traditional Supervisory Control and Data Acquisition (SCADA). However, there is a need for tackling time-delays in control strategies based in WAMS. For this purpose, this paper proposes an Enhanced Time Delay Compensator (ETDC) approach which manages varying time delays introducing the perspective of network latency instead dead time; also, ETDC takes advantage of real signals and measurements transmission procedure in WAMS building a closed-loop memory control for power systems. The strength of the proposal was tested satisfactorily in a widely studied benchmark model in which inter-area oscillations were excited properly.

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An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum

Cited by 11 publications

References 28 publications

A Hybrid Approach Based on SOCP and the Discrete Version of the SCA for Optimal Placement and Sizing DGs in AC Distribution Networks

A Hybrid Approach Based on SOCP and the Discrete Version of the SCA for Optimal Placement and Sizing DGs in AC Distribution Networks

A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks

Latencies in Power Systems: A Database-Based Time-Delay Compensation for Memory Controllers

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