Optimal Power Generation Research Articles

Feasibility and sensitivity assessment of various heads for micro-hydropower plant design in the Deluwang watershed, Indonesia

ABSTRACT The escalating global demand for electrical energy, including in Indonesia, underscores the need for renewable energy sources like micro-hydropower plants (MHPs). This study examines the financial feasibility and sensitivity of MHP projects in the Deluwang watershed, Situbondo Regency, Indonesia. Three cases with varying head elevations and discharge rates were analyzed, utilizing crossflow turbines. Case 1, with the highest head and discharge, emerged as the most profitable, demonstrating the highest values for Net Present Value (NPV), Benefit–Cost Ratio (BCR), and Internal Rate of Return (IRR). The study found that on-grid systems, despite higher initial costs, offer more stable revenue and faster payback periods compared to off-grid systems. Sensitivity analysis revealed the on-grid method's resilience to fluctuations in interest rates, project lifespan, and river discharge, maintaining feasibility with up to an 80% reduction in discharge over 15 years. This highlights the importance of strategic planning in MHP design, considering head and discharge rates to optimize power generation. The findings provide valuable insights for renewable energy development, contributing to Indonesia's energy needs and local socio-economic benefits. Future research should further explore the socio-economic impacts of MHP installations to enhance their development and sustainability.

A Rome district transition towards optimal and sustainable heat and power generation

In this work, a specific district of Rome energy metabolism has been studied to reduce the carbon footprint of electric and thermal energy generation. Two scenarios were investigated, one “ex-ante” with the district as it was, fully dependent on the national grid for electricity and methane-fuelled boilers for heating. And an “ex-post” scenario with the buildings retrofitted with more efficient thermal insulation, LED lights, photovoltaic panels and trigeneration systems. The energy metabolism of the district was modelled in TRNSYS in both cases. For the ex-post scenario, the digital twin implemented a control logic for energy flows with several functionalities including prioritizing the power flow, setting rules and boundaries on the operation of the co-generators, preventing batteries from overcharging/discharging. The sizing of PV panels, batteries, and cogeneration units in the ex-post scenario was optimized in terms of both energy and economic performance using a Python library with the Non-dominated Sorting Genetic algorithm (NSGA-II). In the ex-post scenario, the optimal energy system delivers significant reductions in energy costs and CO2 emissions. The energy transition results in a decrease in purchased electricity of 68.2%, CO2 emissions by 56% and generation costs by 48.9%. The Levelized Cost Of Energy (LCOE) of the district is estimated to be 196 €/MWh.

Enhancing fault-clearing algorithm for renewable-energy-based distribution systems using artificial neural networks

Abstract Integrating small and large-scale photovoltaic (PV) solar systems into electrical distribution systems has become mandatory due to increased electricity bills and the concern for limiting greenhouse gases. However, the reliable and efficient operation of PV-based distribution systems can be confronted by the intermittence and high variability of solar sources and their consequential faults. In this regard, this article suggests a moderated fault-clearing strategy based on the incremental conductance–maximum power point tracking (IC–MPPT) technique and artificial neural networks (ANNs) to enhance fault detection, localization, and restoration processes in PV-based distribution systems. The proposed strategy leverages IC–MPPT to ensure optimal power generation from the PV solar system, even in the presence of faults. By tracking the maximum power point, the algorithm maintains the performance of the system and mitigates against the impact of faults on the output power. Furthermore, an ANN is employed to improve fault detection and localization accuracy. The developed ANN-based moderated fault-clearing strategy is trained using historical data and fault scenarios, enabling it to recognize fault patterns and make informed decisions through extensive simulations and comparisons with traditional fault-clearing methods. To accomplish this study, benchmarks in PV-based distribution systems are constructed and employed using the MATLAB®/Simulink® software package. Moreover, to validate the efficacy of the developed ANN-based moderated fault-clearing strategy, a real case study of a 1-MW PV-based distribution system in an industrial field located in Giza governorate, Egypt, is tested and investigated. The obtained results demonstrate the effectiveness of the IC–MPPT and ANN-based moderated fault-clearing strategy in achieving faster fault detection, precise fault localization, and efficient restoration in PV solar-based distribution systems while preserving maximum power extraction under small and large system disturbances. Furthermore, IC–MPPT based on an ANN achieves an average power of 98.556 kW and 299.632 kWh energy availability, whereas the IC–MPPT based on a proportional–integral controller achieves 95.7996 kW and 283.4036 kWh, and the classic perturb-and-observe MPPT algorithm achieves 92.2657 kW and 276.8014 kWh.

Harnessing solar power: Innovations in nanofluid-cooled segmented thermoelectric generators for exergy, economic, environmental, and thermo-mechanical excellence

Addressing the imperative need for advancements in thermoelectric generation, this study pioneers an analysis of nanofluid-cooled solar segmented thermoelectric generators with non-uniform cross-sections. Insights into thermal management, structural integrity, and economic efficiency in thermoelectric systems are provided, employing a numerical model that accurately represents thermoelectric effects by accounting for temperature dependencies of semiconductor materials. Through research, exploration of diverse coolant strategies, including TiO2, Fe3O4, Al2O3, and graphene, offers key insights into their impact on cooling dynamics. Findings demonstrate that graphene nanofluid, operating at a flow velocity of 2 m/s, outperforms others, achieving optimal power generation of 221.77 mW and an exergy efficiency of 8.99 %. Additionally, at a concentrated irradiance of 595 kWm−2, graphene leads in environmental benefits, with the highest CO2 savings of 0.38 kgyr−1, and demonstrates economic advantages with a cost-effective dollar per mW value of 3.79×10−6 $mW−1. Furthermore, the study verifies the structural integrity of these systems, with graphene achieving an optimal von Mises stress of 1.35 GPa at a semiconductor height of 0.2 mm. These advancements contribute to environmentally friendly and high-performance generators for sustainable energy solutions, paving the way for future innovations in thermoelectric technology.

Determination of conditions for the optimal power generation PV system for energy community and citizen’s energy in Ukraine by criterion programming method

Determination of conditions for the optimal power generation PV system for energy community and citizen’s energy in Ukraine by criterion programming method

Enhancing AGC Efficiency and Settling Time in Multi-Area Power Systems with GrasshopperBased PID Optimization under Open Market Dynamics

This paper delves into the optimization of Automatic Generation Control (AGC) using a Grasshopper-based PID approach in multi-area power systems. It investigates the performance of this method in scenarios both with and without High-Voltage Direct Current (HVDC) links, operating under an Open Market System. Through simulations, the study evaluates the effectiveness of the Grasshopper-based PID controller in maintaining system stability and enhancing power generation within a competitive energy market. The findings provide insights into the adaptability of this technique across different network configurations, shedding light on its potential to enhance AGC efficiency and grid robustness in a dynamic energy landscape. This research contributes to advancing AGC strategies in complex energy markets, offering DISCO's and TRANSCO's a robust solution for optimized power generation, improved stability, and reduced frequency deviations in multi-area systems.

Hydrodynamic Development and Optimisation of a Retrofittable Dual-Mode Propeller Turbine

Dual-mode propellers, as propulsion and turbine devices, have found widespread application in renewable energy systems for marine vehicles, particularly in sailing boats and yachts. However, the existing dual-mode propellers in these contexts are typically chosen in an off-the-shelf manner, indicating a lack of hydrodynamic optimisation to enhance both the propulsion and energy generation efficiency in the same rotor. To address this limitation and furnish scientific validation of the design of a dual-mode propeller turbine rotor optimised to achieve a balanced performance in both propulsion and energy generation, rigorous experimentation was conducted using specialised software, Rotorysics 2019, and a case study vessel, the Princess Royale. Utilising prior experimental data for this propeller turbine, code validation was undertaken to ensure accurate prediction of the effects of the pitch, blade count and expanded area ratio on the performance in both modes. With the intention of achieving optimal power generation and propulsion efficiencies in conjunction with a single rotor, the findings reveal that the optimised fixed-pitch propeller exhibits dual functionality. They serve as both propulsion and tidal/current turbines with balanced efficiency. They are particularly suitable for low-speed vessels such as yachts anchored in currents or for sailboats utilising a propeller as a towed turbine. Through thorough testing and analysis, the concept of a dual-mode propeller turbine was feasible. Analysing them separately, in terms of the propulsion, the best geometry found through numerous tests of different expanded area ratios, blade number, pitch and speed was the 3-blade, 0.6 pitch ratio, which achieved a propulsive efficiency of 54.33% (0.5433204) and a power coefficient of 0.291843. Conversely, if the focus was on power generation while maintaining excellent propulsive efficiency, the optimal geometry would be the 5-blade, 0.6 pitch ratio, which offers a power coefficient of 0.348402 and a propulsive efficiency of 48.55% (0.48547). However, when using both power generation and propulsion as the criteria, the 5-blade, 0.6 pitch ratio, with an EAR of 0.387142, is superior, with balanced optimisation, offering a propulsive efficiency of 52.53% (0.52527) and a power coefficient of 0.319718. As expected, this encompasses a higher blade number for increased power generation efficiency and a higher pitch ratio for increased propulsive efficiency.

Enhancing wind power with permanent magnet synchronous generator control strategies

AbstractDue to the substantial rise in wind power generation, the direct-drive permanent magnet synchronous generator has emerged as a leading technology for efficient variable speed operation, meeting grid demands effectively. This paper presents a comparative analysis of control strategies for permanent magnet synchronous generator based wind turbine using real variable wind speed data from a 2 MW of Tetouan wind farm in Morocco. The proposed approach is based on evaluating two primary control strategies: the adaptive fuzzy-proportional-integral controller and the conventional proportional-integral controller aimed at enhancing the wind turbine's output power. The simulation performed on MATLAB-Simulink indicates that pitch control mechanisms play a crucial role in optimizing power generation, also demonstrating its ability to achieve satisfactory performance.

An integrated planning framework for optimal power generation portfolio including frequency and reserve requirements

AbstractElectricity system decarbonisation poses several challenges to network stability and supply security, given renewables' intermittency and possible reduction of system inertia. This manuscript presents a novel integrated system framework to determine optimal generation investments for addressing decarbonisation challenges and achieving cost‐effective electricity systems while ensuring frequency stability and reserve requirements are met at the operational level in a net‐zero system. The novel planning framework is a mixed‐integer bilinear programming problem accurately modelling clustered variables for the on/off status of generation units and seconds‐timescale frequency requirements at an operational and planning level. The benefits of the decision framework and effects of dispatch decisions in a year are illustrated using the Great Britain case study. The results provide optimal trade‐offs and cost‐effective investment portfolios for including detailed modelling of unit‐commitment and frequency stability constraints versus not including them in the planning model. Making investment decisions for a net‐zero electricity system without these constraints can lead to very high system costs due to significant demand curtailment. Although the model's computation burden was increased by these constraints, complexity was managed by formulating them tightly and compactly. Non‐convex quadratic nadir constraints were efficiently solvable to global optimality by applying McCormick relaxations and branching techniques in an advanced solver.

Influence of compression ratio on the performance characteristics of a spark ignition engine

In this study, the influence of the compression ratio on the performance characteristics of a gasoline engine was investigated in detail using COMSOL simulations. Four compression ratios — 8, 9, 10 and 11 — were investigated at different engine speeds between 1000 and 1800. The analysis focused on power output, braking performance and fuel consumption in order to decipher the complicated relationships between compression ratios and engine dynamics. The results showed a significant increase in power output with increasing compression ratio, highlighting the delicate balance required for optimal power generation. Braking power increased with higher compression ratios, indicating a potential improvement in braking performance. In addition, the study showed a correlation between increased fuel consumption and higher compression ratios, highlighting the need for strategic fuel-saving measures. These results contribute to the understanding of gasoline engine behavior and provide insights into the trade-offs that need to be made when adjusting the compression ratio. Recommendations include experimental validation, exploration of dynamic compression control, research into integrated braking systems, investigation of sustainable fuel strategies and a focus on multi-metric optimization. The observed increase in power output at higher compression ratios highlights an important aspect of engine optimization. Engineers and researchers need to carefully consider compression ratio adjustments to ensure optimal power generation while maintaining efficiency. This insight can guide the development of engines that strike an ideal balance between power and fuel efficiency.

Lattice Boltzmann simulation for wake interactions of aligned wind turbines using actuator line model with turbine control

A wind turbine wake causes a decrease in wind speed and an increase in turbulence intensity. The wind turbine wake interaction is essential for predicting the power output of a wind farm consisting of many wind turbines. This research proposes a CFD method able to reproduce wake interactions and power outputs of multiple wind turbines with high speed and accuracy. Large eddy simulations with the lattice Boltzmann method are used for fluid calculations, specifically for large-scale CFD simulations. The wind turbines are represented using an actuator line model. Optimal power generation efficiency is achieved by controlling the rotor speed and blade pitch angle. Large-scale simulations of eight aligned wind turbines are conducted using 1.75 billion grid points and 40 GPUs. We compare two cases with and without control to investigate the effect of turbine control on wake and power output. Both the instantaneous and mean streamwise velocities confirm that the turbine control reduces the wake velocity deficit of the downwind wind turbine. High-speed inflow of wind to the downstream turbines augments their power output. With implementation of turbine control, the power outputs of the downstream turbines agree well with the observation data obtained in an earlier study. The results demonstrate the importance of controlling the rotational speed and pitch angle for actuator line simulations.

Thermal stratification characteristics and cooling water shortage risks for pumped storage reservoir–green data centers under extreme climates

Utilizing the thermal stratification of reservoirs to obtain cold water for cooling green data centers (GDCs) is a new mode of energy conservation and emission reduction. However, global warming is expected to alter this phenomenon in deep reservoirs and thus may affect the digitalization process. While the frequency and intensity of extreme climate (EC) events are increasing under a changing climate, the impacts of these highly destructive events on thermal stratification and the related cascading effects on GDC cold-water supplies are still unclear. A two-lateral-dimensional thermohydrodynamic model was established to determine the characteristics of reservoir thermal stratification changes and its potential water environment impacts based on the heat extreme experienced by the Jinshuitan Reservoir, a large, pumped storage power station (PSPS) with a GDC in southeastern China. Fourteen different PSPS inlet/outlet schemes under 2 climate scenarios were designed, and two new indexes, namely, the risk index of cold-water shortage and the index of thermal stratification, were proposed to explore the impact of extreme climates on GDC water extraction. The results showed that compared to the present climate conditions, the reservoir experienced stronger thermal stratification with a 20.6 % average increase in thermal stability, a longer thermal stratification duration with a transitional trend from seasonal to permanent stratification, and a thinner cold-water layer with a 15-m average decrease. Changes in the thermal stratification of reservoirs under EC conditions will benefit some species, such as diatoms (except for early July and the period from mid-August to early October), green algae and cyanobacteria and the migration of warm-water fish, but adversely impact dissolved oxygen, diatoms and cold-water fish. Furthermore, the risk of cold-water shortages under EC conditions was consistently greater than that under average climate (AC) conditions (traditional assessment) when the elevation of pumped storage intake/outlet was less than 145 m. According to the traditional assessment method, the intake/outlet elevation of pumped storage reservoirs resulted in a 60.27 % increase in the risk of cold-water shortages during climate extremes. Furthermore, the demand for green cold-water withdrawal and optimal pumped storage power generation benefits were met when the PSPS intake/outlet elevation was 145 m. Beyond solving this specific case, this study elucidates the importance of linking the thermal stratification and data center of cold-water withdrawal to ECs. These findings provide new insights for increasing climate change resilience.

A Comparative Smart Computation Algorithm for Economic And Emission Dispatch Optimization of Tanjung Jati Power Plant

This research delves into optimization strategies for enhancing power generation efficiency and reducing costs in PLTU Tanjung Jati. The study explores three computational algorithms for optimization: Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), focusing on optimizing power generation costs while considering penalty costs and emissions. Through extensive simulations and evaluations, the results indicate that the GWO algorithm achieves the most optimal outcomes in terms of cost optimization, demonstrating fast convergence and lesser simulation time compared to the other algorithms. The research provides valuable insights into selecting optimal algorithms for complex optimization problems like Combined Economic Emission Dispatch (CEED) in power generation systems, ultimately contributing to more efficient and cost-effective power generation.

Multi-objective performance analysis of different SCO2 Brayton cycles on hypersonic vehicles

To provide the continuous and stable power supply of hypersonic vehicles, this study investigates four candidate cycles on the basis of three critical parameters. Specifically, the effects of cycle pressure ratio (PR), recompression split ratio (x), and cycle intermediate pressure ratio (RPR) on the regenerative, recompression, precompression, and partial cooling supercritical carbon dioxide (SCO2) Brayton cycles (BCs) are emphasized. The analysis is carried on by using an established thermodynamic simulation platform. Using PR as the working condition parameter, the influence laws of x and RPR on each cycle at common working conditions are given. The Non-dominated Solution Genetic Algorithm-II (NSGA-II) performs multi-objective optimization for different cycle types. The performance of these cycles is then compared under optimal conditions. The results show that the regenerative SCO2 BC could maintain relatively high output power while keep the structure simple, compared with other three cycles. The optimum power generation in the study range and the common operating conditions of regenerative SCO2 BC is 203.49 kW and 154.03 kW, respectively. Therefore, the regenerative SCO2 BC preferably satisfies the requirements of the hypersonic vehicles.

I-V response test of 60–150 W mono-crystalline solar panel

This work investigates the discrepancies in electrical parameters of mono-crystalline solar panels between Ago-Iwoye weather conditions and the manufacturer’s specified ideal conditions. Manufacturer’s specifications are typically based on 1,000 W/m2 global solar irradiance, AM 1.5, and 25°C operating temperature, while actual weather conditions at installation sites can vary significantly. Mono-crystalline (single-crystal) silicon solar panels of capacities 60, 80, 100, and 150 W were evaluated through current-voltage (I-V) response tests at an installation site in Ago-Iwoye, Nigeria, with solar irradiance exposure from 11 a.m. to 3 p.m. The analysis of I-V and P-V curves revealed a significant reduction in maximum power output by 28.6%, 25.9%, 28.9%, and 19.36%, respectively, compared to the manufacturer’s stated values. This deviation underscores the importance of considering local weather conditions during solar PV projects, and we recommend adding an additional 20%–30% of the total solar panel capacity during installations to account for variations in solar irradiance and operating temperatures, ensuring optimal performance and effective solar power generation in Ago-Iwoye and similar areas.

Optimizing multi-resource-based energy supply chains in developing economies: A periodic review model for affordable and sustainable solutions

Electricity shortages are prevalent in developing countries, further exacerbated by the advocacy of zero-carbon policies to mitigate global climate change. This transition away from fossil fuels poses significant challenges in establishing cost-effective and sustainable energy supply networks. To tackle these challenges, this research assesses the influence of operational efficiencies, advancements in transmission technology, and strategic facility placements on the design of energy supply chains. We prioritize factors such as investment requirements, transmission yield, energy mix, carbon emissions, and social costs. We construct a robust optimization model with stochastic parameters that examines extreme scenarios. Applying this framework to a real-world case in Pakistan spanning a 30-year planning horizon, we present a novel approach that simultaneously diversifies raw material reserves while determining optimal power generation capacity and transmission technologies. Our analysis shows that integrating renewable energy resources and changing transmission methods within the current energy mix can yield an affordable and sustainable energy supply chain, reducing reliance on coal. Consequently, the study case demonstrates substantial reductions in carbon emissions and social costs by 85.68 % and 17.81 %, respectively, in the second and third 10-year planning intervals.

Improving Power Quality in a Grid-Connected Hybrid Power System through the Implementation of a Fuzzy Logic Controller

The examination of modeling and designing grid-connected hybrid power systems with efficient control strategies is the focus of this study. Integration of wind and photovoltaic systems into the ac-bus bar system is a common practice in enhancing operational performance. Utilization of Matlab Simulink software is employed for the design of this hybrid system, incorporating efficient MPPT control algorithms to optimize power generation from solar and wind sources under varying climatic conditions. Analysis of the maximum power point tracking mechanism and control methods of the hybrid power system is conducted, particularly in response to changes in weather conditions such as wind speed and solar radiation. Maintaining grid voltages and Unity Power Factor (UPF) while feeding currents into the grid is essential for the hybrid system. The employment of Proportional Integral (PI) control instead of Fuzzy Logic Controller (FLC) in the voltage-oriented control approach is explored to enhance power quality.

Optimization of sustainable distributed power generation in distribution networks: a comprehensive analysis of location, capacity, and environmental impact

With the increasing integration of distributed generation (DG) into distribution networks, the impact of its output and configuration on the environment and overall benefits has become more pronounced. To enhance environmental benefits while minimizing costs, an optimization model for DG location and capacity considering environmental benefits (LCEB) is proposed. Initially, a mathematical model for DG location and capacity is established, with optimization objectives including voltage deviation, network loss, and environmental benefit. Subsequently, modified particle swarm optimization (MPSO) with a single-dimension search probability mutation is employed to solve this model, obtaining an optimized DG output and layout scheme. Finally, the feasibility and effectiveness of the proposed model are demonstrated through simulation and analysis by using the IEEE33 node system as an example. The results highlight the model’s capability to improve environmental and economic benefits, enhance voltage levels, and reduce network losses within the distribution network.

Study of hydrodynamic characteristics in oscillating wave surge converter

In the realm of renewable energy, researchers worldwide have been paying close attention to developing the Oscillating Wave Surge Converter (OWSC) device. This device has the potential to harness the power of ocean waves and convert it into a reliable source of clean energy. Hydrodynamic characteristics are essential parameters in developing OWSC devices. Therefore, this research conducted a hydrodynamic study on the OWSC device with variations in ocean wave periods, including T= 1.5, 1.7, 1.9, 2.1, and 2.3. The Boundary Element Method (BEM) describes the interaction between sea waves and floating body structures. This method assumes incompressible, inviscid, and irrotational flow. A numerical approach is used as a calculation method followed by verification and validation to support the level of actualization. The research results showed that the incident wave caused the OWSC device to experience a deviation from its equilibrium position in the form of an oscillating flap inclination angle as a form of hydrodynamic characteristics. The sea wave period correlatedwith the rate of change in flap position over time, including the maximum deviation in the flap angle. As a power plant, the performance of the OWSC device can work at reasonably short-wave period intervals based on the device's ability to produce mechanical power. The highest average mechanical power was achieved in the T= 1.5 period of 34.49 Watts with an efficiency of up to 52.43%. The OWSC device requires a high intensity of wave energy in a short duration to generate optimal mechanical power. It is important to note that optimal mechanical power generation is crucial for the OWSC device to function effectively. Therefore, the device should be placed in a location where the wave energy intensity is consistently high.

Research on the power generation performance and optimization of thermoelectric generators for recycling remaining cold energy

Compared with extensive research on the power generation of thermoelectric generators (TEGs) under medium-high temperatures, research on power generation for cold energy utilization is still limited. To study the performance and feasibility of low-temperature power generation, this paper combines simulation and experiments for research. Firstly, a simulation model based on actual material parameters is established. Then, a thermoelectric low-temperature power generation experimental platform is established to conduct experimental research on TEG in different temperature zones and temperature differences and compared with simulation results. Finally, optimization research is conducted by changing thermoelectric materials and structures. The research results indicate that the maximum errors between the dates of simulation and experiment in terms of output voltage, conversion efficiency, and exergy efficiency are 11.3 %, 10.57 %, and 10.57 %, respectively. Compared with Bi2Te3, the output voltage, conversion efficiency, and exergy efficiency of CsBi4Te6 are improved by 21.95 %, 34.64 %, and 34.64 %, respectively. The maximum output power and conversion efficiency are linearly related to the output current. The performance is optimal when the thermoelectric unit height is 1.0 mm and the side length is 1.6 mm. This proves the feasibility of TEG application at low temperatures and lays the foundation for low-temperature power generation.