Moving towards RER has become imperative to achieve sustainable development goals (SDG). Renewable energy resources (RER) are characterized by uncertainty whereas, most of them are unpredictable and variable according to climatic conditions. This paper focuses on RER-based electrical power plants as a base to achieve two different goals, SDG7 (obtaining reasonably priced clean energy) and SDG13 (reducing climate change). These goals in turn would support other environmental, social, and economic SDG. This study is constructed based on two pillars which are technological developments and life cycle assessment (LCA) for wind, solar, biomass, and geothermal power plants. To support the study and achieve the main point, many essential topics are presented in brief such as fossil fuels’ environmental impact, economic sustainability linkage to RER, the current contribution of RER in energy consumption worldwide and barriers and environmental effects of RER under consideration. As a result, solar and wind energy lead the RER electricity market with major contributions of 27.7% and 26.92%, respectively, biomass and geothermal are still of negligible contributions at 4.68% and 0.5%, respectively, offshore HAWT dominated other WT techniques, silicon-based PV cells dominated other solar PV technologies with 27% efficiency, combustion thermochemical energy conversion process dominated other biomass energy systems techniques, due to many concerns geothermal energy system is not preferable. Many emerging technologies need to receive more public attention, intensive research, financial support, and governmental facilities including effective policies and data availability.

Isolated microgrid (IMG) power systems face the significant challenge of achieving fast power sharing and stable performance. This paper presents an innovative solution to this challenge through the introduction of a new droop control technique. The conventional droop controller technique used in inverter-based IMG systems is unable to provide satisfactory performance easily, as selecting a high droop controller gain to achieve fast power sharing can reduce the system’s stability. This paper addresses this dilemma by proposing a modified droop control for inverter-based IMGs that effectively dampens low-frequency oscillations, even at higher droop gain values that would typically lead to instability. The design is described step-by-step, and the proposed controller’s effectiveness is validated through time domain simulation analysis. The results demonstrate the significant improvement in stability and fast power sharing achieved with the proposed controller. This innovative technique presents a promising solution for achieving fast power sharing and stable performance in IMG power systems.

The objective of this paper is to propose a new technique for maximum power point tracking (MPPT) in photovoltaic (PV) systems that utilizes fewer sensors, thereby reducing the hardware cost. The technique aims to achieve efficient MPPT under various environmental conditions by employing a modified SEPIC converter and a model predictive control (MPC)-based MPPT algorithm. To achieve the objective, the proposed technique utilizes only one voltage sensor and one current sensor, significantly reducing the hardware requirements compared to traditional MPPT techniques. The modified SEPIC converter is employed to regulate the voltage and current levels in the PV system. The MPC-based MPPT algorithm is implemented to dynamically adjust the operation of the converter and track the maximum power point. The algorithm incorporates a model predictive control approach, which utilizes a predictive model of the PV system to anticipate and optimize the power output. The algorithm predicts the behavior of the PV system based on the available sensor measurements, allowing for accurate MPPT. The algorithm operates in real-time, providing instantaneous adjustments to maximize power extraction. The study demonstrates that the proposed technique effectively tracks the maximum power point of the PV system using only one voltage sensor and one current sensor, thus reducing the overall hardware cost. The MPC-based MPPT algorithm, in combination with the modified SEPIC converter, achieves efficient power extraction under various operating conditions. The simulation and experimental results indicate that the proposed technique outperforms traditional MPPT techniques in terms of cost-effectiveness and power extraction efficiency.

In this paper, an enhanced version of whale optimization algorithm (EWOA) is presented to be applied in adaptive control techniques as a parameter tuner. One weakness point in this control scheme is the low efficiency of its objective function. Balloon effect (BE) is a modification introduced to increase the efficiency of the objective function of the optimization method and the ability of the controller to deal with system problems increase consequently. Controlling of the temperature of electric furnaces is considered as one of the important issues in several industrial applications. Conventional controllers such as PID controller cannot deal efficiently with the problem of parameters variations and step disturbance. This paper proposes an adaptive controller, in which the gain of the temperature controller is tuned online using EWOA supported by balloon effect. System responses obtained by the proposed adaptive control scheme using EWOA + BE have been compared with an electric furnace temperature control (EFTC) scheme response using both the PID controller-based modified flower pollination algorithm (MoFPA) and PID-accelerated PIDA-based MoFPA. From the results, it can be observed that the proposed controller tuned by the EWOA + BE method improves the time performance compared with the other techniques (PID and PIDA-based MoFPA) in case of EFTC application.

The paper suggests a 9-level inverter with quadruple boosting which it considers very useful for small-scale PV systems. The suggested circuit uses capacitors that are a self-balanced voltage without using an additional circuit or complicated control algorithms to balance the voltage of the capacitors. The circuit produces 9 levels with quadruple boost gain at the output terminals by using minimum components as compared with other recent topologies. The circuit analysis and modeling for each output level are described. The switching control strategy uses a simplistic logic control circuit relying on Pulse Width Modulation (PWM) is implemented to ensure balance voltage of capacitors. By the help of MATLAB/SIMULINK, the effectiveness and robustness of architecture are validated. Furthermore, a prototype for this topology is set up and tested in the laboratory using a DSPACE-1104 verifying the theoretical analysis. The experimental setup and hardware implementation are described. The theoretical and experimental results are investigated under various conditions illustrating excellent agreement between the theoretical and experimental endorses the targeted circuit.

Single widespread employment of renewable energy sources (RESs) contributes to the shortage in the inertia of the microgrid (MG). After this, frequency stability may regress as a result of power imbalance or minor load fluctuations. This paper proposes an explicit adaptive modified virtual inertia control (VIC) based on an online Archimedes optimization algorithm (AOA) identifier for MG containing thermal, wind, and solar photovoltaic power plants. The Rung Kutta approach is used to construct the proposed online identifier, which acts as a model of the MG. AOA predicts the coefficients of the online identifier based on the input and output of MG to mimic the frequency deviation of the MG online. AOA estimates online the inertia and damping coefficients of the VIC system with an energy storage device based on online AOA identifier coefficients. The frequency deviation of the MG based on the proposed explicit adaptive modified VIC is compared with the conventional VIC based on fixed parameters and the VIC system based on optimal parameters using AOA offline under mutation in loads, weather-dependent input, and MG parameters using MATLAB/Simulink software. Furthermore, the proposed explicit adaptive modified VIC based on an online AOA identifier is evaluated with the adaptive VIC system based on fuzzy logic control, which adjusts only the inertial gain online. The simulation results demonstrate the capabilities of the proposed explicit adaptive modified VIC to improve the frequency stability and enhance low-inertia islanded MGs with RESs.