Photovoltaic microgrids provide free renewable energy solutions for Rwandans. Although solar technology keeps on its advancement, hydropower remains the principal power source in Rwanda. Other renewable power sources include wind and geothermal energies that are not yet fully exploited. Nonrenewable sources in Rwanda including methane, peat, thermal, and fuels are also used for providing energy solutions for the citizens. Rwanda Energy Group (REG) sets the energy strategic plan since 2015 for achieving the minimum of 512 MW of energy production in 2024/2025 to meet the total energy demand. The plan predicted 52% for grid-connected and 48% for off-grid (standalone) connections. The literature survey and data analysis collected on site were used to evaluate and determine the best cheaper microgrid model from the three comparison case studies for the household in Rwanda. The study focused on the economic power generation model mainly based on solar resources to minimize the electricity cost and provide income for the excess energy produced. Moreover, the study resulted in a low-cost (four times cheaper), reliable, and affordable grid-connected PV and battery microgrid model for a residential home with a minimum daily load of 5.467 kWh. The simulation results based on economic comparison analysis found the levelized cost of energy (LCOE) and net present cost (NPC) for each power-generated model by using Hybrid Optimization Model for Electric Renewable (Homer) pro software. The results show that the LCOE for electricity production by each of the Grid connected-PV-Battery system, Diesel GenSet-PV-Batteries, and PV-Batteries systems was 0.0645 US$/1 kWh, 1.38 US$/1 kWh and 1.82 US$/1 kWh, respectively, compared with 0.2621 US$/1 kWh, the current residential electricity price (2020) for Rwanda.

In order to solve the problems caused by the susceptibility to changing weather conditions and the complex load conditions of photovoltaic (PV) systems, and the fact a single target inverter control strategy cannot effectively mitigate large voltage fluctuations at point of common coupling (PCC), an integrated reactive power control strategy for PV inverters is proposed. According to the weather and load conditions, this strategy is divided into four control modes: normal operation control mode, reverse power control mode, cloudy control mode and night control mode. The four control modes switch between each other under the specific switching rules to ensure an appropriate quantity of reactive power injection or consumption in the PV inverter. The effects of the four control modes in isolated operation were significant. The deviation rate of PCC voltage from its standard value was mitigated at about 2% under the integrated control strategy. Therefore, the proposed control strategy has a high application value in improving power quality and maximizing utilization of PV inverters.

This study improves the accuracy of junction temperature prediction, as the insulated gate bipolar transistor (IGBT) reliability is important for the safe operation of its working system due to junction temperature is limited in its actual performance and reliability. A model based on an improved sailfish optimization algorithm to optimize support vector machine (ISFO-SVM) is proposed to solve the problem that the junction temperature prediction accuracy is not high enough. The proposed algorithm is improved by adaptive nonlinear iterative factor, Le'vy flight and differential mutation strategy to optimize the support vector machine (SVM) internal parameters to predict junction temperature. The results indicate that ISFO-SVM performs better under the same evaluation indexes. The root mean squared error average value decreased by 67.189%, and the mean absolute percentage error average value decreased by 63.189%, compared with the sailfish optimization algorithm to optimize the SVM. The prediction error of ISFO-SVM is smaller and the error value is in the [−5 °C, 5 °C] range accounting for 98.270% of the total test samples. ISFO-SVM has a higher fitting degree than the actual junction temperature and the R2 has reached 99.660%. The model predicts the junction temperature of IGBT modules and provides scientific guidance for system reliability evaluation to maintain safe and stable operation effectively.

With the increasingly prominent defects of traditional fossil energy, large-scale renewable energy access to power grids has become a trend. In this study, a microgrid operation optimization method, including power-to-gas equipment and a hybrid energy storage system, is proposed. Firstly, this study constructs a microgrid system structure including P2G equipment and a hybrid energy storage system of electricity and hydrogen. Secondly, aiming at minimizing the system operation cost and carbon emission penalty cost, a low-carbon economic operation optimization model of the proposed microgrid is established. Then, this study proposes a microgrid optimization method based on an improved gazelle optimization algorithm to symmetrically improve economic and environmental performance. Finally, the practicability and superiority of the above model and optimization method are verified using a real microgrid case. The results show that considering the participation of P2G equipment and a hybrid energy storage system in the optimal operation, the carbon emission of the microgrid is reduced to 33.56% of the microgrid considering only a single electric energy storage system, and the comprehensive operation cost is reduced by 6.54%. This study is conducive to promoting the development of clean energy and symmetrically enhancing the economic and environmental performance of the microgrid.

This study constructs a novel virtual synchronous generator system based on a transfer function, and optimizes the parameters of the model by using the improved whale algorithm to improve the frequency control ability of virtual synchronous generator. Virtual synchronous generator technology helps to solve the problem that the integration of large-scale renewable energy generation into the power system leads to the deterioration of system frequency stability. It can maintain the symmetry of grid-connected scale and system stability. The virtual synchronous generator technology makes the inverter to have the inertia and damping characteristics of a synchronous generator. The inverter has the inertia characteristics and damps to reduce the frequency instability of high penetration renewable energy power system. The improved whale algorithm is efficient to find the best combination of control parameters and the effectiveness of the algorithm is verified by microgrid and power system. The results show that the proposed frequency coordination control scheme suppresses the frequency deviation of power system and keep the system frequency in a reasonable range.