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

Abstract

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).

An extended ϵ‐constraint method for a multiobjective finite‐horizon Markov decision process

“…These weights are nonnegative parameters that indicate the weight distributed to the objective functions. These are chosen based on the priority of each objective function and the preference of the decision maker (Naidji and Boudour, 2020; Sun, 2020). By considering a K ‐vector $$\lambda \ = ( {{\lambda _1},{\lambda _2}, \ldots ,{\lambda _K}} )\ $$, all the K objective functions are weighted and added together to form a single objective MDP model.…”

Anovel power management strategies inPV‐wind‐based grid connected hybrid renewable energy system using proportional distribution algorithm

“…Other adjustments of active and reactive power, such as power limitations, balancing adjustment, automatic frequency control, reactive power control, and automatic voltage control can be required by the manager of the electrical grid 30‐32 which is not studied in this paper.…”

Optimal Reactive Power Dispatch With Time-Varying Demand and Renewable Energy Uncertainty Using Rao-3 Algorithm

“…In [38], an enhanced firefly algorithm has been introduced for multi-objective optimal active/reactive power dispatch with uncertainties consideration. Also, in [39] a quantum-behaved particle swarm optimization differential mutation (QPSODM) algorithm is used to solve the multiobjective ORPD with renewable energy uncertainty. From an environmental, economic, and technical point of view, the switch from fossil-fueled-based generation to renewable energy sources is a must.…”