Hierarchical Distributed Mixed-Integer Optimization for Reactive Power Dispatch

Murray, Alexander; Engelmann, Alexander; Hagenmeyer, Veit; Faulwasser, Timm

doi:10.1016/j.ifacol.2018.11.730

Cited by 16 publications

(9 citation statements)

References 24 publications

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“…For example, optimal reactive power dispatch is a variant of opf, where the active power injections p are assumed to be given (e.g. by an energy market) and only the remaining variables which mainly are the reactive power injections, transformer settings, shunt settings or facts set-points are used for minimizing the losses in the grid [77].…”

Section: Further Opf Variantsmentioning

confidence: 99%

Optimal power flow: an introduction to predictive, distributed and stochastic control challenges

Faulwasser

Engelmann

Mühlpfordt

et al. 2018

At - Automatisierungstechnik

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The Energiewende is a paradigm change that can be witnessed at latest since the political decision to step out of nuclear energy. Moreover, despite common roots in Electrical Engineering, the control community and the power systems community face a lack of common vocabulary. In this context, this paper aims at providing a systems-and-control specific introduction to optimal power flow problems which are pivotal in the operation of energy systems. Based on a concise problem statement, we introduce a common description of optimal power flow variants including multi-stage-problems and predictive control, stochastic uncertainties, and issues of distributed optimization. Moreover, we sketch open questions that might be of interest for the systems and control community.

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Section: Further Opf Variantsmentioning

confidence: 99%

Optimal power flow: an introduction to predictive, distributed and stochastic control challenges

Faulwasser

Engelmann

Mühlpfordt

et al. 2018

At - Automatisierungstechnik

Self Cite

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“…For reaching the targets of the ORPD problem, various optimization methodologies have been recommended such as deterministic algorithms and metaheuristic algorithms [4]. All of these algorithms comprise original deterministic algorithms, modified deterministic algorithms, original metaheuristic algorithms, modified metaheuristic algorithms, and crossbreed heuristic algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Thus, the number of new solutions produced in each iteration N spi and the number of new solutions produced in each run N spr are criteria for comparing the search speed of different applied methods. We have set different values (2,3,4,5) to N pack and the values of N coyote have been 9, 6, 4, and 3, accordingly. Although the different setting results in different population size, N pop = 18, 18, 16, 15, N spi = 20 is the same for all settings excluding the case of N pack = 3 and N coyote = 6 with N spi = 21.…”

Section: Testing Performance Of Coa and Icoa On Different Adjustment ...mentioning

confidence: 99%

Optimal Reactive Power Generation for Transmission Power Systems Considering Discrete Values of Capacitors and Tap Changers

Kien¹,

Hien²,

Nguyen³

2021

Applied Sciences

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In this paper, an improved coyote optimization algorithm (ICOA) is developed for determining control parameters of transmission power networks to deal with an optimal reactive power dispatch (ORPD) problem. The performance of ICOA method is superior to its conventional coyote optimization algorithm (COA) thanks to modifications of two new solution generations of COA. COA uses a center solution to generate an update step size in the first solution generation and produced one new solution by using random factors to diversify the search space in the second solution generation. By tackling the drawbacks of COA, ICOA can reduce control parameters and computation steps, shorten execution time, and provide better results. ICOA is compared to its conventional COA for three standard IEEE systems of 30-, 57-, and 118-buses with continuous and discrete control variables. Moreover, three other algorithms such as water cycle algorithm (WCA), salp swarm algorithm (SSA), and sunflower optimization algorithm (SFOA) have been also implemented for further investigation of the real performance of the proposed method. All the applied methods are metaheuristic algorithms based on population and randomization. The result comparison from the test systems has indicated that ICOA can provide higher solution quality than other methods with reasonable execution time. Therefore, ICOA is a reliable tool for finding optimal solutions of the ORPD problem.

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“…Recently, different optimization methods have been studied to solve the ORPD problem; various optimization methodologies are recommended, such as deterministic and metaheuristic algorithms [8]. These algorithms include original, modified deterministic, original, modified metaheuristic, and crossbreed heuristic algorithms [9].…”

Section: Introductionmentioning

confidence: 99%

Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm

et al. 2022

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In this study, an optimization algorithm called chaotic turbulent flow of water-based optimization (CTFWO) algorithm is proposed to find the optimal solution for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a complicated, mixed-integer nonlinear optimization problem, comprising control variables which are discrete and continuous. The CTFWO algorithm is used to minimize voltage deviation (VD) and real power loss (P_loss) for IEEE 30-bus and IEEE 57-bus power systems. These goals can be achieved by obtaining the optimized voltage values of the generator, the transformer tap changing positions, and the reactive compensation. In order to evaluate the ability of the proposed algorithm to obtain ORPD problem solutions, the results of the proposed CTFWO algorithm are compared with different algorithms, including artificial ecosystem-based optimization (AEO), the equilibrium optimizer (EO), the gradient-based optimizer (GBO), and the original turbulent flow of water-based optimization (TFWO) algorithm. These are also compared with the results of the evaluated performance of various methods that are used in many recent papers. The experimental results show that the proposed CTFWO algorithm has superior performance, and is competitive with many state-of-the-art algorithms outlined in some of the recent studies in terms of solution accuracy, convergence rate, and stability.

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Hierarchical Distributed Mixed-Integer Optimization for Reactive Power Dispatch

Cited by 16 publications

References 24 publications

Optimal power flow: an introduction to predictive, distributed and stochastic control challenges

Optimal power flow: an introduction to predictive, distributed and stochastic control challenges

Optimal Reactive Power Generation for Transmission Power Systems Considering Discrete Values of Capacitors and Tap Changers

Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm

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