Optimal Power Generation Research Articles

Multi-objective optimization with advanced exergy analysis of a wind-solar‑hydrogen multi-energy supply system

Identifying the primary sources of exergy destruction is a powerful method for promoting the high-efficiency operation of multi-energy supply systems. Advanced exergy analysis identifies avoidable parts of the destruction and discovers interactions between subsystems of a multi-energy complementary coupled system to explore the potential for system improvement. In this paper, a wind-solar‑hydrogen multi-energy supply (WSH-MES) system is studied, in which wind farms, photovoltaic power plants, solar thermal power plants, and hydrogen grid systems are coupled at the grid side to share the electrical load. To optimize power generation and improve system performance, a bi-level capacity-operation co-optimization model is developed specifically for the WSH-MES system. The upper level of the model employs a multi-objective optimization approach to find the best balance between energy, exergy, and advanced exergy and economy. The model is solved using the Non-dominated Sorting Genetic Algorithm-II and linear programming. To gain insights into the system's performance, advanced exergy analysis is performed under the optimal capacity configuration. By considering avoidable exergy destruction efficiency and exergy destruction proportion, the sequence of optimization potential for the WSH-MES system is determined. Surprisingly, the findings entirely different from that of conventional exergy analysis and reveal the interrelations between the analyzed subsystems. The sequence of optimization potential for the WSH-MES system is found to be as follows: concentrated solar power, photovoltaics, proton exchange membrane fuel cells, wind power, and proton exchange membrane electrolyzers. The identified optimization potential provides valuable guidance for improving energy efficiency, reducing costs, minimizing environmental impact, and serves as a reference for the design and optimization of new systems.

Performance degradation analysis and fabrication guidance of μ-TEG from material to device

Micro thermoelectric generator (μ-TEG) attracts more and more attention due to its small size and high power density. Many two-dimensional thermoelectric materials with high performance have facilitated the development of μ-TEG. However, the performance of μ-TEG fabricated by these great thermoelectric materials is significantly degraded due to size effect, interfacial effects (include contact effect and boundary effect) and structure effect. To accurately assess the performance degradation degree from material to μ-TEG and guide the device fabrication, an experiment-verified mathematical model considering interfacial and size effects is proposed. Firstly, the phonon/electron temperature distribution in thermoelectric leg of μ-TEG is analyzed to investigate the device-level thermoelectric properties of material. Then based on the device-level thermoelectric properties, the actual power generation performance model of μ-TEG is established to conduct the influence analysis of these effects (boundary, size, contact and structure effects) on material and device. Finally, the thermoelectric leg thickness (Hte) is optimized to realize optimal power generation. The study results reveal that boundary and size effects weaken the device-level thermoelectric properties, and the reduction trend is more obvious when Hte is smaller, especially when Hte ≤ 20 μm. The decrease from the material intrinsic figure of merit ((ZT)m) to the device figure of merit ((ZT)D) is owing to the boundary effect, structure effect and contact effect, and the dominant factor of this decrease changes from structure effect (Hte＜7 μm)to contact effect (Hte ≥ 7 μm) as Hte increases, which points to a main optimization direction for (ZT)D for different Hte. As for contact effect, the electrical contact resistivity (re,c) has a more significant impact on weakening the performance of μ-TEG than thermal contact resistivity (rk,c), and their optimization goals are explored (re,c ≤ 5.1 × 10−12 Ω·m2, rk,c ≤ 9.3 × 10−8 K·m2/W). At given electrical and thermal contact resistivity, there exists an optimal Hte for achieving the optimal power generation (Popt) and a large range of Hte for achieving 95%Popt, and the optimal Hte increases with increasing electrical and thermal contact resistivity. This study can reduce the processing difficulty and save time and economic costs of μ-TEG fabrication, which can avoid the blind fabrication of μ-TEG.

Design and Implementation of Solar Powered Mobile Phone Fast Charging Station for Campus

Abstract: The proliferation of mobile phone usage has become ubiquitous on college campuses, leading to a heightened demand for accessible and sustainable charging facilities. This research project aims to address this need by designing and implementing a solar-powered mobile phone charging station tailored to the unique requirements of a campus environment. By harnessing solar energy as a clean and renewable power source, the proposed solution aims to provide an environmentally friendly charging option for students, staff, and visitors. The project encompasses the design, development, and testing of a solar-powered charging station that integrates various components such as solar panels, charge controllers, batteries for energy storage, power management circuitry, and a user interface. The design process will involve careful consideration of factors such as power generation capacity, energy storage capabilities, user interface design, and system scalability to ensure an optimal and efficient solution. Efficient energy management is crucial for the successful operation of the charging station. To this end, the project will focus on implementing advanced techniques such as maximum power point tracking (MPPT) and battery management algorithms to optimize power generation, storage, and utilization. This approach will help maximize the efficiency and reliability of the charging station while ensuring a consistent supply of power to meet the charging needs of users. Additionally, the project will develop a user-friendly interface that enables seamless operation and monitoring of the charging station. The interface will provide real-time information on power availability, charging status, and system diagnostics, ensuring a user-friendly and intuitive experience for users. User feedback and input will be incorporated into the design process to enhance usability and accessibility. The implementation and testing phase of the project will involve deploying the designed charging station on the campus premises. Performance evaluations will be conducted to assess factors such as charging efficiency, reliability, and system scalability. Data on solar energy generation, energy consumption, and user feedback will be collected and analysed to evaluate the effectiveness of the solar-powered charging solution in a campus environment. The anticipated outcomes of this research project include the design and implementation of a solar-powered mobile phone charging station specifically tailored to campus usage. Furthermore, the project will deliver an advanced energy management system that optimizes power generation, storage, and utilization. The development of a user-friendly interface will ensure easy operation and monitoring of the charging station, enhancing the overall user experience. The research findings will provide valuable insights into the system's performance, efficiency, reliability, and scalability. Additionally, an economic and environmental assessment will highlight the benefits of adopting solar-powered charging solutions on campus, including reduced carbon emissions and energy costs. In conclusion, the design and implementation of a solar-powered mobile phone charging station for campus usage will provide an innovative and sustainable solution to meet the increasing demand for charging facilities. By harnessing the power of the sun, this research project aims to offer a convenient, environmentally friendly, and cost-effective charging option for mobile devices on campus. The outcomes of this research will contribute to the promotion of sustainable energy practices, reduce the carbon footprint of campuses, and enhance the overall campus experience for students, staff, and visitors.

A novelty approach to solve an economic dispatch problem for a renewable integrated micro-grid using optimization techniques

Introduction. The renewable integrated microgrid has considered several distributed energy sources namely photovoltaic power plant, thermal generators, wind power plant and combined heat and power source. Economic dispatch problem is a complex operation due to large dimension of power systems. The objective function becomes non linear due to the inclusion of many constraints. Hourly demand of a commercial area is taken into consideration for performing economic dispatch and five combinations are considered to find the best optimal solution to meet the demand. The novelty of the proposed work consists of a Sparrow Search Algorithm is used to solve economic load dispatch problem to get the better convergence and accuracy in power generation with minimum cost. Purpose. Economic dispatch is performed for the renewable integrated microgrid, in order to determine the optimal output of all the distributed energy sources present in the microgrid to meet the load demand at minimum possible cost. Methods. Sparrow Search Algorithm is compared with other algorithms like Particle Swarm Optimization, Genetic Algorithm and has been proved to be more efficient than Particle Swarm Optimization, Genetic Algorithm and Conventional Lagrange method. Results. The five combinations are generation without solar power supply system and Combined Heat and Power source, generation without solar and wind power supply systems, generation including all the distributed energy sources, generation without wind power supply system and Combined Heat and Power source, generation without thermal generators. Practical value. The proposed optimization algorithm has been very supportive to determine the optimal power generation with minimal fuel to meet the large demand in commercial area.

Optimal behavioral performance and power generation potential from palm oil mill industry: Case study using downdraft gasification with power generation

ABSTRACT Considering Malaysia's position as a leading producer of palm oil, it wastes appears to be a promising renewable energy source. Thus, present work compares optimal behavioural performance and power generation potential from the palm oil mill wastes, including empty fruit bunch (EFB) and palm kernel shell (PKS). Aspen Plus software is used to perform a sensitivity study, investigating the influence of temperature and equivalence ratio (ER) on syngas output, syngas composition, and power generation. Temperature increase (600◦C to 1000◦C) leads to increase in H2 and CO and decrease in CO2 and CH4 composition. At optimal operating condition, temperature for EFB and PKS is at 740◦C and 865◦C while ER is at 0.25 for both feedstocks. The low heating value (LHV), cold gas efficiency (CGE) and total syngas output happens to be around 4.84 MJ/Nm3, 48.89% and 259.18 kg/hr for (EFB and 4.01 MJ/Nm3, 51.27 % and 312.97 kg/h for PKS. EFB shows higher capability to produce more quality syngas and generate more power compared to PKS. From economic perspective, EFB brings more revenue (115 million/year) than PKS (111 million/year) for 10 MW plant capacity by considering electricity as the main product.

Bending strength evaluation and power generation performance optimization of a curved photovoltaic-thermoelectric hybrid device

Curved photovoltaic-thermoelectric (PV-TE) hybrid devices have great potential applications in the fields of aerospace, navigation and daily life. During the application, the curvature radius of the PV-TE hybrid device needs to be altered to fit different curved surfaces. Naturally, the bending strength of the curved hybrid device is a very important issue. This paper evaluates the bending strength and optimizes the output power and energy conversion efficiency of the curved hybrid device. The stress solutions are obtained by means of the variational principle. The recovery of transverse shear stress is achieved by using the Cauchy’s polar equilibrium equation. It is found that the thermal stress is much smaller than the bending stresses induced by the bending deformation of the hybrid device. The circumferential stress is the key factor that results in the failure of the hybrid device. The optimization of the curvature radius of the hybrid device is conducted and the safety region is identified to protect the hybrid device from strength failure. The ratio of thickness to cross-sectional area of the thermoelectric leg is optimized to obtain the optimum power generation performance of the hybrid device. This paper offers some favorable suggestions for structural design of the curved hybrid device.

Supply‐demand optimizer for economic emission dispatch incorporating price penalty factor and variable load demand levels

AbstractThe Economic and Emission Dispatch (EED) method is widely used to optimize generator output in a power system. The goal is to reduce fuel costs and emissions, including carbon dioxide, sulphur dioxide, and nitrogen oxides, while maintaining power balance and adhering to limit constraints. EED aims to minimize emissions and operating costs while meeting power demands. To solve the multi‐objective EED problem, the supply‐demand optimization (SDO) algorithm is proposed, which employs a price penalty factor approach to convert it into a single‐objective function. The SDO algorithm uses a swarm‐based optimization strategy inspired by supply‐demand mechanisms in economics. The algorithm's performance is evaluated on seven benchmark functions before being used to simulate the EED problem on power systems with varying numbers of units and load demands. Established algorithms like the Grey Wolf Optimizer (GWO), Moth‐Flame Optimization (MFO), Transient Search Optimization (TSO), and Whale Optimization Algorithm (WOA) are compared to the SDO algorithm. The simulations are conducted on power systems with different numbers of units and load demands to optimize power generation output. The numerical analyses demonstrate that the SDO technique is more efficient and produces higher quality solutions than other recent optimization methods.

Optimal Power Generation and Voyage Scheduling in Shipboard Power Systems Considering Load Characteristics-Based Operating Reserve Management

Optimal Power Generation and Voyage Scheduling in Shipboard Power Systems Considering Load Characteristics-Based Operating Reserve Management

A Reinforcement Learning approach to the Optimal Torque MPPT problem in wind turbines

In this work, a torque controller for a variable rotational speed wind turbine has been modelled using Reinforcement Learning and considering the Optimal Torque - Maximum Power Point Tracking problem as one of optimization. The reward optimization function is designed as a non-linear function depending mainly on the rotor power variation. Based on this, an optimal action (electromagnetic torque variation) regulates the turbine rotational speed. A simulated 1.5 MW three bladed wind turbine operation is managed by the torque controller. It keeps the turbine working at optimal operational conditions after a successful training process, which is carried out using the Proximal Policy Optimization algorithm. For the controller training, the turbine confronts constant and then randomly staggered wind speed behaviour. Time series of rotor angular speed, torque and power are presented. Our results show that the modelled controller is able to reach and maintain the wind turbine operation at its optimal power generation conditions. This methodology avoids using some empirical parameter characteristic of the Optimal Torque - Maximum Power Point Tracking algorithm widely used in wind turbine control systems.

Distributed Algorithm for Nonsmooth Resource Allocation Problems With Nonlinear Constraints and Its Application to Smart Grids

In this article, we study nondifferentiable resource allocation problems (RAPs). In our problem, the decisions of agents are subject to coupling inequality constraints, local inequality constraints, and local convex set constraints. In contrast to existing RAPs, the cost functions are nonsmooth and the inequality constraints are nonsmooth and nonlinear in our problem. Based on differential inclusions and projection methods, we exploit a fully distributed subgradient-based resource allocation algorithm to optimally allocate the network resources. With the help of the set-valued LaSalle invariance principle, we prove the global convergence of the algorithm to the optimal resource allocation of our problem. Finally, our method is applied to the economic dispatch problems of smart grids. With our method, the generations of generating units converge to the optimal power generation.

Performance Evaluation Of Permanent Magnet Synchronous Generator (PMSG) On Tidal Power Generation Optimization

In a tidal current energy generation system, optimization of power generation can be done through turbine design, system design, and control of mechanical transmission from the turbine to the generator, as well as from the aspect of electronic generator output control. This research aims to analyze the performance of the PMSG generator from a prototype of the tidal current energy power plant. Turbine rotation is simulated using an ac motor equipped with an ac drive that supports separate speed and torque control. The hydraulic transmission system consists of a pump and a hydraulic motor that transfers the rotation of the turbine to the generator, where the power output is observed with variations in turbine speed and torque. The results indicate that the transmission system has worked well in transmitting the turbine’s mechanical power and increasing the rotational speed. The decrease in speed with increasing load and low average efficiency (less than 20%) occurs, mainly due to the characteristics of the generator being tested. The generator has a large rated torque requirement of 32 Nm, which is much higher than the main drive capacity of the turbine simulator. The design of a tidal energy conversion system, in which the tidal current speed fluctuates, requires careful selection of the generator, not only from the aspect of power capacity and rated rotational speed, but also from the initial torque value and required rated torque.

Potassium alleviating power overshoot and promoting carbon capture of bufferless algae microbial fuel cells

Power overshoot makes microbial fuel cell (MFC) unable to work normally under high current densities, limiting its application in carbon capture. Herein, effects of cations in medium on overshoot are compared using bufferless MFCs filled by saline or algae suspension containing Na+ or K+. Furthermore, the relationship between cation type and CO2 sequestration abilities of algae MFCs are analyzed under continuous flow mode. As a result, K+ helps to inhibit oxygen leakage while promote proton transport through Nafion separator. Transmembrane diffusion coefficient of oxygen in Na+ saline medium is 1.41 × 10−4 cm·s−1, which decreases to 0.91 × 10−4 cm·s−1 in K+ group. K+ as well as cathodic biofilms or algae cells attribute to overshoot alleviation. No matter saline or algal medium, MFCs containing K+ exhibit better electrochemical properties and achieve more than 40% and 20% increases in maximum power and current densities. Carbon capture capacities of algae MFCs are promoted over 40% in the presence of K+. Under the inlet CO2 concentration of 1% v/v, 5% v/v and 10% v/v, CO2 removal efficiencies of single-chamber algae MFCs containing K+ are 27.46 ± 1.07%, 35.51 ± 1.24% and 39.15 ± 1.35%. This work provides a new strategy for the optimization of MFC power generation and carbon capture by simply adjusting the cations in the solution matrix.

Study on fast prediction method of hydrodynamic load of floating horizontal axis tidal current turbine with pitching motion under free surface

The floating horizontal-axis tidal current turbine (HATCT) moves with the floating carrier while rotating, resulting in a change in its relative inflow velocity at any time. If the rotating speed of the HATCT is fixed, the HATCT cannot work at the optimum tip speed ratio, resulting in the failure to achieve the optimum power generation efficiency. Therefore, this paper proposes a control strategy for the rotating speed of the HATCT, and obtains the hydrodynamic loads of the HATCT with variable speed rotation and pitching motion under free surface conditions based on the CFD method. Compared with the hydrodynamic load of the HATCT under the same situation but with fixed speed control, the variable speed control can effectively improve the power coefficient of the HATCT, but the load fluctuation in terms of the inflow direction load, power, and pitch moment coefficients are more significant than those with fixed speed control. On this basis, according to the variation law of the damping coefficient with pitch period, pitch amplitude, and tip speed ratio, the hydrodynamic load prediction method of the HATCT with pitching motion is established. The validity of this prediction method is verified by comparing the results with those of CFD calculation.

Electrokinetic energy conversion in nanochannels with surface charge-dependent slip

Electrokinetic energy conversion in nanochannels has attracted increasing attention in recent years. However, few scholars have studied the impact of the intrinsic distinction between surface charge-dependent and independent slip on power generation performance. In this work, we consider three kinds of boundary conditions, including no slip, independent slip and surface charge-dependent slip, to investigate the ion concentration distribution, velocity and energy conversion performance in nanochannels combined with the electric double layer theory. The results show that the boundary slip can improve the output performance significantly. Besides, due to the restriction of surface charge on boundary slip, the power generation performance under independent slip and dependent slip exhibits a significant deviation. Thus, the independent slip model is not suitable for predicting ion transport and fluidic flow in practical applications. Moreover, the ion concentration and channel height also play an optimizing role in the performance of electrokinetic energy conversion. We find the boundary slip is a benefit to promote the ion flux due to the velocity mechanism but has little effect on ion concentration distribution. The findings of this study can help for better understanding the ion transfer behavior in nanochannels, which provides useful information for the design and optimization of nanochannel power generation.

Energy-Economic-Environmental Analysis of On-Grid Solar System for Electricity and Hydrogen Production at Homemade Scale: Effect of Different Shades

As an energy source, solar cells can be central to peak load control in different power companies. Hydrogen production can be cost-effective if the generated electricity is unusable. Shades reduce solar cell current and fundamentally alter panel function, making it necessary to restore panels to optimum power generation. Owing to the issues outlined in this paper, the energy-economic-environmental effect of a shade detection algorithm was examined for different shade scenarios, and domestic-scale solar hydrogen production was evaluated. As the effect of the partial shade detection algorithm on the amount of solar hydrogen production has not been investigated quantitatively so far, this issue was discussed in this study. The algorithm and laboratory equipment developed by the authors were used to detect the partial shadow. Thanks to the respected reviewer, the following sentence was added to the abstract. The analyses in HOMER V2.81 software used 20-year average data for a residential building in the city of Tehran obtained from the NASA website. The results recommended that the designed algorithm increases hydrogen production in different scenarios between 5.8% and 32.9%. The results also revealed that the designed algorithm significantly lessen the pollutants between 100 kg/year and 240 kg/year.

Human-in-the-loop optimization of knee-joint biomechanical energy harvester to maximize power generation with minimal user effort

Knee-joint harvesters of biomechanical energy promise to supply usable electric energy and reduce metabolic cost of walking for field workers, but few have succeeded. Optimizing the power generation pattern for each user based on the power generation of the harvester and metabolic cost of the user was assumed to be able to solve the problem. We have developed human-in-the-loop optimization for identifying the power generation pattern that can maximize power generation with minimal metabolic cost during walking. The experimental results showed that walking with the harvesters using the optimized power generation pattern reduced net metabolic cost by 2.36 ± 2.52% compared to walking without the harvester and by 5.81 ± 2.76% compared to walking with the harvesters using the static pattern. The harvester using the optimized power generation pattern can generate 2.75 ± 0.33 W electric power, which was similar to the power generation of the harvester using the static power generation pattern and was 11 times more than the power generation of the harvester that can reduce metabolic cost.

A Semantic Segmentation Method Based on Image Entropy Weighted Spatio-Temporal Fusion for Blade Attachment Recognition of Marine Current Turbines

Marine current turbines (MCTs) may exhibit reduced energy production and structural instability due to attachments, such as biofouling and plankton. Semantic segmentation (SS) is utilized to recognize these attachments, enabling on-demand maintenance towards optimizing power generation efficiency and minimizing maintenance costs. However, the degree of motion blur might vary according to the MCT rotational speed. The SS methods are not robust against such variations, and the recognition accuracy could be significantly reduced. In order to alleviate this problem, the SS method is proposed based on image entropy weighted spatio-temporal fusion (IEWSTF). The method has two features: (1) A spatio-temporal fusion (STF) mechanism is proposed to learn spatio-temporal (ST) features in adjacent frames while conducting feature fusion, thus reducing the impact of motion blur on feature extraction. (2) An image entropy weighting (IEW) mechanism is proposed to adjust the fusion weights adaptively for better fusion effects. The experimental results demonstrate that the proposed method achieves superior recognition performance with MCT datasets with various rotational speeds and is more robust to rotational speed variations than other methods.

The spatial distribution of China's solar energy resources and the optimum tilt angle and power generation potential of PV systems

This study aims at filling the gaps and completing the missing global solar radiation and diffuse solar radiation data considering the limited radiation data of 85 meteorological observation stations and the routine meteorological data of 2001 meteorological observation stations. Employing the Inverse Distance Weighing model, the annual and seasonal spatial distributions of global solar radiation and diffuse solar radiation are obtained. A calculation method of the optimum tilt angle of photovoltaic systems for optimal utilization is established using the Collares-Pereira and Rabl hourly solar radiation model and the solar radiation on sloped surfaces model. The spatial distribution of the optimum tilt angle is obtained using the proposed method. The simplified calculation method of the optimum tilt angle based on latitude and altitude is established by introducing two factors of latitude and altitude. In addition, the annual and seasonal photovoltaic power of China is calculated, and the spatial distribution of China's solar resource utilization potential is obtained using the calculated optimum tilt angle, solar radiation data on sloped surfaces, and the photovoltaic power model. The results show that the annual global solar radiation in China is in the range of 3097–7311 MJm−2, and the annual diffuse solar radiation value ranges from 495 to 3036 MJm−2. Moreover, the optimum tilt angle value in different regions of China is found to range between 14.5°and 49.1°, and the theoretical optimum tilt angle value generally aligns with the law of angle increasing with latitude. The annual photovoltaic power generation is between 117 kWhm−2 and 483 kWhm−2. Compared with the solar energy utilization potential of a PV placed on the horizontal surface, the annual average power generation of a PV panel placed at the optimum tilt angle can increase by up to 144.76 kWhm−2, with an average increase of 10.41%.

Industrial experiment and numerical analysis of the effect of pulsing water flow in thermoelectric generators

Thermoelectric conversion technology can effectively recover industrial waste heat and improve industrial energy utilization efficiency. Most of the industrial waste heat is released irregularly, making it difficult for the thermoelectric generator (TEG) to achieve optimal power generation performance. In order to improve the power generation performance of the TEG in the industrial environment, it is a simple and efficient method to control the internal temperature gradient of the TEG by pulsing water flow. In this study, the numerical calculation method is used to analyze the effect of cooling water conditions on the performance of the TEG in an industrial environment. The numerical calculation process is divided into two parts: steady calculation and transient calculation. Steady calculations are used to analyze the effect of cooling water's initial temperature and flow rate. The cooling water reduces the temperature of the hot end of the thermoelectric module (TEM), which prevents the TEM from reaching the maximum temperature gradient. The flow condition of cooling water is changed to pulse flow, which is used to adjust the temperature gradient of the TEM. The transient calculation is used to analyze the effect of different pulse conditions in TEG's performance. According to the numerical calculation results, industrial experiments are designed, and the experimental results verify the accuracy of the numerical calculation results. The results show that when the cooling water temperature is 20 °C and the flow rate is 3 ms−1, the power generation performance of the TEG reaches the best state. The maximum output power is 281.2 W. Pulsing water flow improves TEG power generation performance. The output power of the TEG is increased by 8.43% when the pulse condition is 0.3 s, and the output power is 304.64 W.

The Performance of Magnetostrictive Material for Wind-Induced Vibration Power Generator

This research investigated the effect of span length variation and capless prismatic structure on the performance of the micropower generator from flow-induced vibration. The vibration response type covers galloping and vortex-induced vibration regimes. The mini harvester energy induced by the harmonic oscillation of prismatic structure was implemented based on the magnetostrictive principle to gain electricity using a galfenol alloy (Fe-Ga). The power generation variations are influenced by the amplitude, frequency, structure displacement, span length, and shape of the bluff body. The optimum power generation is 2.87 mW, and the maximum power generation is 10.63 mW at the resonance velocity Vr of 6.45. Reducing the frequency characteristics of circular cylinders by applying a cap end tip affect power generation characteristics and galloping behaviour for the prism with a span length of 200 mm but not for other span lengths. The effect of span length variation on free vibration and power generation performance for all prism models is similar in that both features are decreased by increasing span length. However, it enhances onset valued power generation. Power generation is considered for the independent electricity supply for specific sensor or wireless devices of an IoT system.