This paper proposes a multi-objective Slime Mould Algorithm (MOSMA), variant of the recently-developed (SMA) for handling optimization problems in industries. Recently, problems, several meta-heuristic and evolutionary techniques have been suggested community. These methods tend to suffer from low-quality solutions when evaluating (MOO) than addressing objective functions identifying Pareto optimal solutions' accurate estimation increasing distribution throughout all objectives. The SMA...

The primary concerns in the practical photovoltaic (PV) system are power reduction due to change operating conditions, such as temperature or irradiance, high computation burden modern maximum point tracking (MPPT) mechanisms, and maximize PV array output during rapid weather conditions. conventional perturb observation (P&O) technique is preferred most of systems. Nevertheless, it undergoes false (MPP) solar insolation wrong decision duty cycle. To avoid computational drift effect, this...

In this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed for solving Real-World constrained Multi-objective Problems (RWMOPs). Such problems can be found in different fields, including mechanical engineering, chemical process and synthesis, power electronics systems. MOAOA inspired by the distribution behavior of main arithmetic operators mathematics. The multi-objective version formulated developed from recently introduced single-objective (AOA) through an...

Abstract Given the multi-model and nonlinear characteristics of photovoltaic (PV) models, parameter extraction presents a challenging problem. This challenge is exacerbated by propensity conventional algorithms to get trapped in local optima due complex nature Accurate estimation, nonetheless, crucial its significant impact on PV system’s performance, influencing both current energy production. While traditional methods have provided reasonable results for model variables, they often require...

Abstract This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve optimization capabilities of conventional optimizer in order address problem data clustering. The process that groups similar items within dataset into non-overlapping groups. Grey hunting behaviour served as model for however, it frequently lacks exploration and exploitation are essential efficient work mainly focuses on enhancing using weight factor concepts increase variety...

Abstract The advancement of Photovoltaic (PV) systems hinges on the precise optimization their parameters. Among numerous techniques, effectiveness each often rests inherent This research introduces a new methodology, Reinforcement Learning-based Golden Jackal Optimizer (RL-GJO). approach uniquely combines reinforcement learning with to enhance its efficiency and adaptability in handling various problems. Furthermore, incorporates an advanced non-linear hunting strategy optimize algorithm’s...

This paper delves into the increasingly complex domain of Optimal Power Flow (OPF) within modern power systems, enhanced by integration unpredictable renewable energy sources. The research originally integrates stochastic photovoltaic and wind sources, along with a suite Flexible AC Transmission System (FACTS) components – including thyristor-controlled series compensators, static VAR phase shifters. primary objective is to solve OPF problem reducing generation costs while accommodating...

The analysis and the assessment of interconnected photovoltaic (PV) modules under different shading conditions various patterns are presented in this paper. partial (PSCs) due to factors reduce power output PV arrays, its characteristics have multiple peaks mismatching losses between panels. principal objective paper is model, analyze, simulate evaluate performance array topologies such as series-parallel (SP), honey-comb (HC), total-cross-tied (TCT), ladder (LD) bridge-linked (BL) produce...

This paper proposes a new Multi-Objective Plasma Generation Optimization (MOPGO) algorithm, and its non-dominated sorting mechanism is investigated for numerous challenging real-world structural optimization design problems. The (PGO) algorithm recently reported physics-based inspired by the generation process of plasma in which electron movement energy level are based on excitation modes, de-excitation, ionization processes. As search progresses, better balance between exploration...

When discussing the commercial applications of photovoltaic (PV) systems, one most critical problems is to estimate efficiency a PV system because current (I) – voltage (V) and power (P) characteristics are highly non-linear. It should be noted that manufacturer's datasheets do not have complete information on electrical equivalent parameters systems necessary for simulating an effective module. Compared conventional approaches, computational optimization global research strategies more...

ABSTRACT This paper proposes a new Multi-Objective Equilibrium Optimizer (MOEO) to handle complex optimization problems, including real-world engineering design problems. The (EO) is recently reported physics-based metaheuristic algorithm, and it has been inspired by the models used predict equilibrium state dynamic state. A similar procedure utilized in MOEO combining different target search space. crowding distance mechanism employed algorithm balance exploitation exploration phases as...

The performance of a PhotoVoltaic (PV) system could be inferred from the features its current–voltage relationships, but PV model parameters are uncertain. Because multimodal, multivariable, and nonlinear properties, requires that extracted with high accuracy efficiency. Therefore, this paper proposes an enhanced version Gradient-Based Optimizer (GBO) to estimate uncertain various models. Criss-Cross (CC) algorithm Nelder–Mead simplex (NMs) strategy hybridized GBO improve performance. CC...

The hybrid model of the power network infrastructure is an essential part sophisticated technology electrical network. For traditional Optimal Power Flow (OPF) problem, thermal generators are typically employed to generate electricity. In this case, amount fuel required produce constrained, and emissions from frequently neglected. Renewable Energy Sources (RESs) have received increasing attention due various potential characteristics such as cleanliness, diversity, renewability. As outcome,...