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This work analyses load profiles for East African microgrids, and then investigates the integration of electric two-wheelers and portable storage into a solar PV with battery microgrid in Uganda, East Africa. By introducing e-mobility and portable storage, demand side management strategic load growth can thus be achieved and electricity access can be expanded. Battery degradation is also considered. The results showed a 98.5% reduction in PV energy curtailment and a 57% reduction in the levelized cost of energy (LCOE) from 0.808 USD/kWh to 0.350 USD/kWh when the electric two-wheeler and portable storage loads were introduced. Such reductions are important enablers of financial viability and sustainability of microgrids. It is possible to avoid emissions of up to 73.27 tons of CO2/year with the proposed e-bikes, and an average of 160 customers could be served annually as off-microgrid consumers without requiring an investment in additional distribution infrastructure. Annual revenue could be increased by 135% by incorporating the additional loads. Sensitivity analyses were conducted by varying component costs, the battery lifetime, the interest rate, and the priority weighting of the additional loads. The battery costs were found to be a major contributor to lifecycle costs (LCC) and also have a big impact on the LCOE. The interest rate significantly affects the LCC as well. [ABSTRACT FROM AUTHOR]

The market for microinverters is growing, especially in Europe. Driven by rising electricity prices and an easing in legislation since 2024, the number of mini-photovoltaic energy systems (mini-PVs) being installed is increasing substantially. Indoor and outdoor studies of microinverters have been carried out at Paderborn University since 2014. In the indoor lab, conversion efficiencies as a function of load have been measured with high accuracy and ranked according to Euro and CEC weightings; the latest rankings from 2024 are included in this paper. In the outdoor lab, energy yields have been measured using identical and calibrated crystalline silicon PV modules; until 2020, measurements were carried out using 215 Wp modules. Because of increasing PV module power ratings, 360 Wp modules were used from 2020 until 2024. In 2024, the test modules were upgraded to 410 Wp modules, taking into account the increase from 600 W to 800 W of inverter power limits, which is suitable for simplified operation permission ("plug-in") in many European countries within a homogenised legislation area for such mini-photovoltaic energy systems or "balcony power plants". This legislation for simplified operation also covers overpowered mini-plants, although the maximum AC output remains limited to 800 W. Presently, yield assessments are being carried out in the outdoor lab, which will take at least a year to be valid and comparable. Kits consisting of PV modules, inverters, and mounting systems are also being evaluated. Yield rankings sometimes differ from efficiency rankings due to the use of different MPPT algorithms with different MPP approach speeds and accuracies. To accelerate yield assessment, we developed a novel, simple formula to determine energy yield for any module and inverter configuration, including overpowered systems. This is a linear approach, determined by just two coefficients, a and b, which are given for several inverters. To reduce costs, inverters will be integrated into the module frame or the module terminal box in the future. [ABSTRACT FROM AUTHOR]

The realization of a carbon-neutral civilization, which has been set as a goal for the coming decades, goes directly hand-in-hand with the need for an energy system based on renewable energies (REs). Due to the strong weather-related, daily, and seasonal fluctuations in supply of REs, suitable energy storage devices must be included for such energy systems. For this purpose, an energy system model featuring hybrid energy storage consisting of a hydrogen unit (for long-term storage) and a lithium-ion storage device (for short-term storage) was developed. With a proper design, such a system can ensure a year-round energy supply by using electricity generated by photovoltaics (PVs). In the energy system that was investigated, hydrogen ( H 2 ) was produced by using an electrolyser (ELY) with a PV surplus during the summer months and then stored in an H 2 tank. During the winter, due to the lack of PV power, the H 2 is converted back into electricity and heat by a fuel cell (FC). While the components of such a system are expensive, a resource- and cost-efficient layout is important. For this purpose, a Matlab/Simulink model that enabled an energy balance analysis and a component lifetime forecast was developed. With this model, the results of extensive parameter studies allowed an optimized system layout to be created for specific applications. The parameter studies covered different focal points. Several ELY and FC layouts, different load characteristics, different system scales, different weather conditions, and different load levels—especially in winter with variations in heating demand—were investigated. [ABSTRACT FROM AUTHOR]

This paper presents a model of an energy system for a private household extended by a lifetime prognosis. The energy system was designed for fully covering the year-round energy demand of a private household on the basis of electricity generated by a photovoltaic (PV) system, using a hybrid energy storage system consisting of a hydrogen unit and a lithium-ion battery. Hydrogen is produced with a Proton Exchange Membrane (PEM) electrolyser by PV surplus during the summer months and then stored in a hydrogen tank. Mainly during winter, in terms of lack of PV energy, the hydrogen is converted back into electricity and heat by a fuel cell. The model was created in Matlab/Simulink and is based on real input data. Heat demand was also taken into account and is covered by a heat pump. The simulation period is a full year to account for the seasonality of energy production and demand. Due to high initial costs, the longevity of such an energy system is of vital interest. Therefore, this model was extended by a lifetime prediction in order to optimize the dimensioning with the aim of lifetime extension of a hydrogen-based energy system. Lifetime influencing factors were identified on the basis of a literature review and were integrated in the model. An extensive parameter study was performed to evaluate different dimensionings regarding the energy balance and the lifetime of the three components, electrolyser, fuel cell and lithium-ion battery. The results demonstrate the benefits of a holistic modelling approach and enable a design optimization regarding the use of resources, lifetime and self-sufficiency of the system. [ABSTRACT FROM AUTHOR]

Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users' consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model's efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system's peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers. [ABSTRACT FROM AUTHOR]

In this work, a model of an energy system based on photovoltaics as the main energy source and a hybrid energy storage consisting of a short-term lithium-ion battery and hydrogen as the long-term storage facility is presented. The electrical and the heat energy circuits and resulting flows have been modelled. Therefore, the waste heat produced by the electrolyser and the fuel cell have been considered and a heat pump was considered to cover the residual heat demand. The model is designed for the analysis of a whole year energy flow by using a time series of loads, weather and heat profile as input. This paper provides the main set of equations to derive the component properties and describes the implementation into MATLAB/Simulink. The novel model was created for an energy flow simulation over one year. The results of the simulation have been verified by comparing them with well-established simulation results from HOMER Energy. It turns out that the novel model is well suited for the analysis of the dynamic system behaviour. Moreover, different characteristics to achieve an energy balance, an ideal dimensioning for the particular use case and further research possibilities of hydrogen use in the residential sector are covered by the novel model. [ABSTRACT FROM AUTHOR]

Fast-growing energy demand of the world makes the researchers focus on finding new energy sources or optimizing already-developed approaches. For an efficient use of solar and wind energy in an energy system, correct design and sizing of a power system is of high importance and improving or optimizing the process of data obtaining for this purpose leads to higher performance and lower cost per unit of energy. It is essential to have the most precise possible estimation of solar and wind energy potential and other local weather parameters in order to fully feed the demand and avoid extra costs. There are various methods for obtaining local data, such as local measurements, official organizational data, satellite obtained, and reanalysis data. In this paper, the Modern-Era Retrospective analysis for Research and Applications dataset version 2 (MERRA-2) dataset provided by NASA is introduced and its performance is evaluated by comparison to various locally measured datasets offered by meteorological institutions such as Meteonorm and Deutscher Wetterdienst (DWD, or Germany's National Meteorological Service) around the world. After comparison, correlation coefficients from 0.95 to 0.99 are observed for monthly global horizontal irradiance values. In the case of air temperature, correlation coefficients of 0.99 and for wind speed from 0.81 to 0.99 are observed. High correlation with ground measurements and relatively low errors are confirmed, especially for irradiance and temperature values, that makes MERRA-2 a valuable dataset, considering its world coverage and availability. [ABSTRACT FROM AUTHOR]