Three powerful nature-inspired algorithms to optimize power flow in Algeria's Adrar power system

Makhloufi, Saida; Mekhaldi, A.; Teguar, M.

doi:10.1016/j.energy.2016.10.064

Cited by 23 publications

(6 citation statements)

References 26 publications

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“…To evaluate applicability of the GTO on the practical power system, Adrar’s power network (APN) 28-bus (Makhloufi et al, 2016) has been considered as test system. Adrar’s power network (APN) is situated in the southwest of Algeria, is isolated grid from the Algerian power grid.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Optimal power flow solution based on gorilla troops optimization technique considering uncertainty of renewable energy sources: A case study of Adrar’s isolated power network

2023

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This paper proposes an efficient Gorilla troops-inspired algorithm to cope optimal power flow (OPF) problem considering uncertainty of renewable energy sources (RES). The problem is formulated as large-scale constrained optimization problem with non-linear characteristics. Its degree of complexity increases with incorporation of intermittent energy sources, making it harder to be solved using conventional optimization techniques. However, could be efficiently resolved by nature-inspired optimization algorithms and solvers. The objective function is the overall cost of system, including reserve cost for over-estimation and penalty cost for under-estimation of two types of PV-solar and wind energy. To demonstrate the consistency and robustness of the developed algorithm a case study on the modified IEEE 30-bus system and and Adrar’s power network (isolated grid) is carried out. Simulation results show the capability of GTO to find high quality optimal feasible solutions and ranked first among the compared algorithms, and so, over different function landscapes.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Optimal power flow solution based on gorilla troops optimization technique considering uncertainty of renewable energy sources: A case study of Adrar’s isolated power network

2023

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“…A total peak load of 291.2 MW was realized in the year of 2015. APS consists in seven gas turbine power plants with a total generation capacity of 495.6 MW . A wind farm and a PV plant with capacity of 10.2 and 20 MW, respectively, are installed there.…”

Section: Case Study Simulation Results and Discussionmentioning

confidence: 99%

Stochastic multi‐objective optimal reactive power dispatch considering load and renewable energy sources uncertainties: a case study of the Adrar isolated power system

Naidji

Boudour

2020

Int Trans Electr Energ Syst

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Optimal reactive power dispatch (ORPD) is a particular case of the optimal power flow (OPF) which consists in determining the state of an electric power system by optimizing a specific objective function and satisfying a set of some operating constraints. In this paper, the purpose is to solve deterministic and stochastic multi‐objective ORPD (MO‐ORPD) problem under load and renewable energy sources (RES) uncertainties. The uncertainty is modelled using stochastic scenario‐based approach (SSBA). The objectives to be minimized are active power loss and cumulative voltage deviation from their corresponding nominal values. The MO‐ORPD is solved using sum weighed method, and fuzzy satisfying method is used to select the best compromise solution among Pareto front of non‐dominated solutions. In this paper, quantum‐behaved particle swarm optimization differential mutation (QPSODM) algorithm is proposed to solve the ORPD problem. The proposed methodology has been examined and confirmed on the IEEE 14‐bus and the practical Adrar's isolated power system. The performance of the proposed methodology is compared with recent algorithms. Simulation results show that the proposed methodology can solve the MO‐ORPD including RES effectively and can give best and logic results. Furthermore, a sensitivity analysis is carried out to show the performance of the proposed algorithm comparing to own developed algorithms particle swarm optimization (PSO) and quantum PSO (QPSO).

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“…In the literatures, different methods have been presented for modelling WP and load demand uncertainties. In [3], predetermined probability distribution functions (PDFs) have been used for modelling WP uncertainty. Excess and deficit realised WP with respect to forecast WP have been penalised by the associated cost coefficients considering the probability of each case.…”

Section: Introductionmentioning

confidence: 99%

Non‐deterministic optimal power flow considering the uncertainties of wind power and load demand by multi‐objective information gap decision theory and directed search domain method

Rahmani

Amjady

2018

IET Renewable Power Generation

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Optimal power flow (OPF) as an important operation function of wind power-integrated power systems encounters the uncertainties of load demand and wind power. To cope with these uncertainty sources, various OPF models including deterministic OPF, probabilistic OPF, scenario-based OPF, stochastic OPF, robust OPF and recently information gap decision theory (IGDT)-based OPF have been presented in the literature. A multi-objective IGDT-based AC OPF model is presented which can simultaneously optimise various uncertainty horizons pertaining to load demands and wind powers considering the specified robustness level. Another main contribution of this study is presenting an effective directed search domain (DSD)based multi-objective solution method to solve the proposed multi-objective IGDT-based AC OPF problem. The proposed OPF model and solution approach are tested on the IEEE 118-bus test system and the obtained results are compared with the results of other OPF models and solution methods. These comparisons illustrate the effectiveness of the proposed multi-objective IGDT-based AC OPF model as well as the proposed DSD-based multi-objective solution method.

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Three powerful nature-inspired algorithms to optimize power flow in Algeria's Adrar power system

Cited by 23 publications

References 26 publications

Optimal power flow solution based on gorilla troops optimization technique considering uncertainty of renewable energy sources: A case study of Adrar’s isolated power network

Optimal power flow solution based on gorilla troops optimization technique considering uncertainty of renewable energy sources: A case study of Adrar’s isolated power network

Stochastic multi‐objective optimal reactive power dispatch considering load and renewable energy sources uncertainties: a case study of the Adrar isolated power system

Non‐deterministic optimal power flow considering the uncertainties of wind power and load demand by multi‐objective information gap decision theory and directed search domain method

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