Optimal design of mixed AC–DC distribution systems for commercial buildings: A Nonconvex Generalized Benders Decomposition approach

Frank, Stephen; Rebennack, Steffen

doi:10.1016/j.ejor.2014.10.008

Cited by 45 publications

(22 citation statements)

References 29 publications

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“…The main function of the VSC is to realize the bi-directional flow of active power on the AC side and the DC side, and at the same time to regulate the reactive power. The control mode of the converter mainly includes master-slave control and droop control [15][16][17]. This paper mainly studies the distribution network DG planning method when the converter adopts master-slave control mode.…”

Section: Ac/dc Distribution Network Modelmentioning

confidence: 99%

An AC/DC Distribution Network DG Planning Problem: A Genetic-Ant Colony Hybrid Algorithm Approach

2019

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The planning problem of distributed generators (DG) accessing the AC/DC distribution network is a hot research topic at present. In this paper, a location and volume model of DG is established that considers DG operation and maintenance costs, DG investment costs, system network loss costs, fuel costs, pollution compensation costs, and environmental protection subsidies. Furthermore, voltage and power constraints are also considered in the model. To solve the proposed model, a hybrid algorithm called the GA-ACO algorithm is presented that combines the ant colony algorithm (ACO) and the genetic algorithm (GA). On one hand GA has good robustness, good adaptability, and quick global searching ability but it also has some disadvantages such as premature convergence and low convergence speed. On the other hand, ACO has the ability of parallel processing and global searching but its convergence speed is very low at the beginning. The IEEE-33 node distribution network is taken as a basic network to verify the rationale of the proposed model and the effectiveness of the proposed hybrid algorithm. Simulation results show that the proposed model is very in line with reality, the hybrid algorithm is very effective in solving the model and it has advantages in both convergence speed and convergence results compared to ACO and GA.

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Section: Ac/dc Distribution Network Modelmentioning

confidence: 99%

An AC/DC Distribution Network DG Planning Problem: A Genetic-Ant Colony Hybrid Algorithm Approach

2019

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“…Solving optimisation problems in simultaneous expansion planning and large-scale systems as an MINLP is complex, time-consuming, and an NP-hard problem [22]. Frank and Rebennack [23] have developed a non-convex MINLP problem for mixed AC-DC electricity distribution systems. In that paper, a global optimisation algorithm has been presented that is based on non-convex generalised Benders decomposition.…”

Section: Introductionmentioning

confidence: 99%

MILP model for integrated expansion planning of multi‐carrier active energy systems

Ghasemi¹,

Aghaei²,

Gharehpetian

et al. 2019

IET Generation, Transmission & Distribution

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“…Functions f 0,ω and fω represent probability times costs associated with x 0 and vω for every scenario ω. Problem (P0) can also arise from integrated system design and operation problems which consider system operation over multiple time periods (but without uncertainties), such as for energy polygeneration plants [29] and electrical power distribution networks [30]). In this case, x 0 represents system design decisions and xω represents system operational decisions for time period (or scenario) ω, and f 0,ω and fω represent frequency of occurrence of time period ω times investment cost and operational cost, respectively.…”

Section: Introductionmentioning

confidence: 99%

A joint decomposition method for global optimization of multiscenario nonconvex mixed-integer nonlinear programs

Ogbe

2019

J Glob Optim

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This paper proposes a joint decomposition method that combines Lagrangian decomposition and generalized Benders decomposition, to efficiently solve multiscenario nonconvex mixed-integer nonlinear programming (MINLP) problems to global optimality, without the need for explicit branch and bound search. In this approach, we view the variables coupling the scenario dependent variables and those causing nonconvexity as complicating variables. We systematically solve the Lagrangian decomposition subproblems and the generalized Benders decomposition subproblems in a unified framework. The method requires the solution of a difficult relaxed master problem, but the problem is only solved when necessary. Enhancements to the method are made to reduce the number of the relaxed master problems to be solved and ease the solution of each relaxed master problem. We consider two scenario-based, two-stage stochastic nonconvex MINLP problems that arise from integrated design and operation of process networks in the case study, and we show that the proposed method can solve the two problems significantly faster than stateof-the-art global optimization solvers.

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Optimal design of mixed AC–DC distribution systems for commercial buildings: A Nonconvex Generalized Benders Decomposition approach

Cited by 45 publications

References 29 publications

An AC/DC Distribution Network DG Planning Problem: A Genetic-Ant Colony Hybrid Algorithm Approach

An AC/DC Distribution Network DG Planning Problem: A Genetic-Ant Colony Hybrid Algorithm Approach

MILP model for integrated expansion planning of multi‐carrier active energy systems

A joint decomposition method for global optimization of multiscenario nonconvex mixed-integer nonlinear programs

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