Electricity Generation System Research Articles

Modeling and simulation of a full ISRU-based system for energy storage and electricity generation on the Moon

Modeling and simulation of a full ISRU-based system for energy storage and electricity generation on the Moon

Optimum carbon tax rate for emission targets of electricity generation system by life cycle techno-economic-environmental optimization model

Reduction of greenhouse gas emissions from the electricity sector is of special interest for decarbonization of energy systems. Optimum carbon tax as a powerful policy tool is here studied by integrated techno-economic-environmental life cycle analysis in a unit commitment problem. The present model is formulated as a bi-level optimization problem to reach the optimum carbon tax rates for different emission targets. The total life cycle CO2 emissions are estimated to be 20333.90 tons/hr in a real case study of Iran's electricity sector for the peak demand hour. The carbon tax rate for a 2% and a 3% emissions reduction is equal to 15.87 and 24.65 $/ton, respectively. In the business-as-usual scenario, higher carbon taxes will be required each year to meet the same emission target. However, developing the electricity sector with cleaner technologies and strategic plans may decrease the carbon tax rate. The extent of this reduction depends on the type of development program implemented in the green revolution scenario. Therefore, policy makers play a direct role in ensuring the sustainable development of the electricity sector. The present model provides a robust framework to analyze the real carbon tax rates for the whole life cycle of electricity generation dispatch.

Management of Hybrid Hydropower and Floating Solar Systems at Num Ngum 1 in Lao PDR

The integration of a hybrid hydro-floating solar power (HPP-FPV) system is covered in this study with the goal of improving energy management and producing more electricity. The production capacity of the hybrid system is almost twice as high as that of the original HPP system, demonstrating its potential for higher energy generation. Because it forecasts weather and modifies electricity generation accordingly. The analysis highlights how crucial it is to make sure that the hybrid system's electricity generation doesn’t go beyond the current power grid's maximum transmission capacity. This is essential to preserving the consistency and caliber of the power that is provided. The research's overall goal of increasing the output of renewable energy through creative system integration and practical management techniques is captured in the abstract.

Investigating the correlation between flow dynamics and flow-induced voltage generation

The conversion of water current to voltage generation through graphene has gained interest in both basic physics and applications such as sensors and electricity generation systems. However, many aspects of the mechanism remain unclear. Recently, quantum-based momentum transfer theories have been reported, but these often do not account for flow conditions. In this study, we investigated the correlation between the flow conditions of a liquid medium and the electrical conduction of graphene through experiments and numerical calculations. Our results suggest that the necessary condition is that the flow must be neither irregular nor purely laminar; instead, graphene responds to the transition process of the fluid. This finding supports the extension of current theories and presents valuable insights for both basic science and industrial applications.

Time Series Forecasting of Thermal Systems Dispatch in Legal Amazon Using Machine Learning

This paper analyzes time series forecasting methods applied to thermal systems in Brazil, specifically focusing on diesel consumption as a key determinant. Recognizing the critical role of thermal systems in ensuring energy stability, especially during low rain seasons, this study employs bagged, boosted, and stacked ensemble learning methods for time series forecasting focusing on exploring consumption patterns and trends. By leveraging historical data, the research aims to predict future diesel consumption within Brazil’s thermal energy sector. Based on the bagged ensemble learning approach a mean absolute percentage error of 0.089% and a coefficient of determination of 0.9752 were achieved (average considering 50 experiments), showing it to be a promising model for the short-time forecasting of thermal dispatch for the electric power generation system. The bagged model results were better than for boosted and stacked ensemble learning methods, long short-term memory networks, and adaptive neuro-fuzzy inference systems. Since the thermal dispatch in Brazil is closely related to energy prices, the predictions presented here are an interesting way of planning and decision-making for energy power systems.

Design and simulation of a photovoltaic plant for maximum use of the solar resource in the Toluviejo municipality of Colombia

Currently, there are various technologies for constructing photovoltaic plants including monofacial and bifacial photovoltaic panels, centralized and string-type inverters, and fixed mounting structures with light followers, to build electrical energy generation systems. This work reviewed the advantages and disadvantages between these technologies, and the implementation of a photovoltaic plant in Toluviejo, Colombia was proposed. To justify and confirm the design, simulations were carried out with the PVsyst software, resulting in the bifacial panels, centralized inverters, and structures with light followers, the most effective solution, and with the highest production for the proposed photovoltaic power generation plant.

Modeling and Simulation of an Integrated Synchronous Generator Connected to an Infinite Bus through a Transmission Line in Bond Graph

Most electrical energy generation systems are based on synchronous generators; as a result, their analysis always provides interesting findings, especially if an approach different to those traditionally studied is used. Therefore, an approach involving the modeling and simulation of a synchronous generator connected to an infinite bus through a transmission line in a bond graph is proposed. The behavior of the synchronous generator is analyzed in four case studies of the transmission line: (1) a symmetrical transmission line, where the resistance and inductance of the three phases (a,b,c) are equal, which determine resistances and inductances in coordinates (d,q,0) as individual decoupled elements; (2) a symmetrical transmission line for the resistances and for non-symmetrical inductances in coordinates (a,b,c) that result in resistances that are individual decoupled elements and in a field of inductances in coordinates (d,q,0); (3) a non-symmetrical transmission line for resistances and for symmetrical inductances in coordinates (a,b,c) that produce a field of resistances and inductances as individual elements decoupled in coordinates (d,q,0); and (4) a non-symmetrical transmission line for resistances and inductances in coordinates (a,b,c) that determine resistances and inductance fields in coordinates (d,q,0). A junction structure based on a bond graph model that allows for obtaining the mathematical model of this electrical system is proposed. Due to the characteristics of a bond graph, model reduction can be carried out directly and easily. Therefore, reduced bond graph models for the four transmission line case studies are proposed, where the transmission line is seen as if it were inside the synchronous generator. In order to demonstrate that the models obtained are correct, simulation results using the 20-Sim software are shown. The simulation results determine that for a symmetrical transmission line, currents in the generator in the d and q axes are −25.87 A and 0.1168 A, while in the case of a non-symmetrical transmission line, these currents are −26.14 A and 0.0211 A, showing that for these current magnitudes, the generator is little affected due to the parameters of the generator and the line. However, for a high degree of non-symmetry of the resistances in phases a, b and c, it causes the generator to reach an unstable condition, which is shown in the last simulation of the paper.

Analog One-Cycle Control Strategy for Stable Battery Charging in Photovoltaic Systems

The growing adoption of photovoltaic systems for direct electricity generation from solar radiation has underscored the importance of efficient energy storage solutions. Batteries are the predominant method for storing energy from photovoltaic systems, especially for applications such as electric vehicle (EV) charging. However, these systems face significant challenges, particularly regarding battery longevity, as fluctuations in solar irradiation can lead to harmful voltage spikes. This paper introduces an Analog One-Cycle Control (OCC) strategy designed to mitigate these issues by stabilizing the battery voltage against varying input voltages. The proposed control scheme aims to enhance battery life by preventing damage caused by voltage overshoots. Experimental results demonstrate the effectiveness of the OCC strategy in maintaining steady-state conditions and optimizing power management.

High gain super lift Luo converter for hybrid energy management systems

Recently, there has been a resurgence of interest in the development of alternative energy supplies due to rising fossil fuel prices and issues about the effects of greenhouse gas emissions on the environment. Today's demand is the design of a hybrid electric power generation system that uses solar and wind energy for remote places. This paper presents the design of an optimized hybrid renewable energy system consisting of a photo voltaic wind turbine (savinous type) with a battery and a super lift LUO converter. A solar PV module with an intelligent inverter facilitates the tracking of the maximum power point and the implementation of a battery charge controller for greater battery lifespan as well as reliable performance. Higher power output and clean energy are available from the hybrid power generation system, which combines innovative techniques with solar and wind power.

Design Of PV Plant to Improve a Voltage Profile Of 11 KV Grid in The South West of Libya

The use of photovoltaic (PV) system for electricity generation is growing up in the last decades. Thesouthern part of Libya suffers from voltage fluctuation and intermittence of electricity during thesummer time. The aim of this paper is firstly to study and analysis a distribution grid of small villagelocated in the southern west region of Libya. We analyzed the existed 11KV distribution overheadline supplied electricity of the village called Takarkibah using Power-World Simulator in order tointegrate it with PV plant. The results obtained show that injection of PV power about 70 % of thegrid power capacity gives good grid performance. After that, we use SAM simulation program todesign PV plant to improve the voltage profile in the distribution grid. Six designs (scenarios) aresimulated using different solar modules and inverters. The simulation results obtained from SAMillustrated the power capacity, energy yield, and losses of the designed PV plant.

Commercial EV fleet smart charging for cost reduction and renewables integration: A case study in Germany

The transition to electric mobility reduces transportation carbon emissions but presents challenges in integrating growing electricity demand with renewable electricity generation and power systems. Smart charging emerges as a key technology to minimize operational costs and support higher utilization of green electricity for electric vehicles (EVs). Market analysis indicates a trend towards dynamic electricity tariffs, incentivizing EV charging at times favourable to the electricity grid, yet existing literature fails to address smart charging technology in sync with times of lower electricity prices and higher renewables integration. This work examines different smart charging strategies for a commercial EV fleet in Germany, considering a Real-Time Pricing (RTP) tariff indexed to day-ahead market prices and renewable electricity integrations. HOMER Grid is used to model these smart charging strategies and generate new EV load profiles. Direct and indirect CO2 emissions and renewable electricity usage ratios are calculated based on detailed electricity grid and self consumption data. The resulting Levelized Cost of Energy (LCOE) is minimized, by adjusting solar PV and battery capacities. The adoption of an RTP tariff decreases the LCOE from €0.530 to €0.314 per kWh. A smart charging strategy designed to reduce peak demand and schedule charging at lower price times further reduces the LCOE to €0.283 per kWh. The lowest LCOE of €0.281 per kWh is achieved with 34.4 kWp of solar PV capacity and no batteries. The carbon impact is minimized with larger solar PV and battery capacities. The performed work indicates a favourable framework for EV charging integrators to maximize cost savings and renewable energy integration for an EV fleet charging use case.

Technological Paradigm Between the Production of Photovoltaic and Thermal Solar Energy in Sahelo-Sahelian Countries

The energy sector in Sahelian countries such as Burkina Faso, Mali and Niger is facing enormous challenges. Indeed, electricity shortages, characterized by recurrent breakdowns of means of production and import dependency due to an unfavorable energy mix, are numerous in these countries. Concerns about the high costs of facilities and operations, as well as environmental pollution, not forgetting to mention the matter of the countries' energy sovereignty, have led to the desire to use reliable, profitable and adapted means of production. The aim of this study is to review the literature on electric power generation systems in the world, in Africa and in Sahelian countries, with an emphasis focus on photovoltaic and thermal solar energy. In addition, it highlights, in views of the problems raised, works that have suggested solutions. To achieve this, scientific articles, theses and other scientific documents dealing with electric power generation systems from 2014 to 2024 have been consulted. This enabled us to get knowledge on the various electric power generation systems, to know their advantages and limitations, and above all the perspectives in terms of electric power generation. Additionally, they provided a source of inspiration for setting up an electric power generation system in line with the realities of the countries of the Alliance of Sahel States (ASS).

Fuzzy Modelling Algorithms and Parallel Distributed Compensation for Coupled Electromechanical Systems

Modelling and controlling an electrical Power Generation System (PGS), which consists of an Internal Combustion Engine (ICE) linked to an electric generator, poses a significant challenge due to various factors. These include the non-linear characteristics of the system’s components, thermal effects, mechanical vibrations, electrical noise, and the dynamic and transient impacts of electrical loads. In this study, we introduce a fuzzy modelling identification approach utilizing the Takagi–Sugeno (T–S) structure, wherein model and control parameters are optimized. This methodology circumvents the need for deriving a mathematical model through energy balance considerations involving thermodynamics and the non-linear representation of the electric generator. Initially, a non-linear mathematical model for the electrical power system is obtained through the fuzzy c-means algorithm, which handles both premises and consequents in state space, utilizing input–output experimental data. Subsequently, the Particle Swarm Algorithm (PSO) is employed for optimizing the fuzzy parameter m of the c-means algorithm during the modelling phase. Additionally, in the design of the Parallel Distributed Compensation Controller (PDC), the optimization of parameters pertaining to the poles of the closed-loop response is conducted also by using the PSO method. Ultimately, numerical simulations are conducted, adjusting the power consumption of an inductive load.

Penstock pipe’s hydraulic design for the mini hydropower plant at Besai Kemu, Bukit Kemuning, Lampung, Indonesia

Abstract Hydropower, as a renewable energy source, holds significant potential for electricity generation. However, optimizing the design of hydropower penstocks to ensure efficient energy conversion remains a complex challenge. This study aims to address this gap by investigating the optimal hydraulic calculations for designing a penstock system in Lampung, Indonesia, thereby contributing to the understanding of micro hydropower engineering. The research adopts an explanatory methodology, utilizing a case study approach in Bukit Kemuning, Lampung, Indonesia. Design data collection at the research site and relevant hydraulic design indicators from literature serve as the foundation for conducting comprehensive hydraulic calculations. The study focuses on key parameters such as penstock dimensions, power generation capacity, and energy loss assessments to inform the design process. The analysis reveals a flow rate of 11 m3/s and a flow velocity of 2.43 m/s, resulting in a targeted power output of 3234 Kilowatts. The findings underscore the critical role of key elevation parameters and design considerations in optimizing the penstock system for efficient electricity generation. Detailed calculations elucidate the determination of penstock dimensions, the evaluation of energy losses, and the consideration of surge pressure velocity to ensure system resilience. To withstand high water pressure, the research advocates for penstock pipes with specific dimensions: two pipes, each 116 m in length, with a diameter of 2.4 m and a cross-sectional area of 4.52 m2 requiring a thickness of 10 mm. The study identifies pressure reduction factors, including head loss due to penstock friction (0.169 m), friction losses (0.1635 m), and water hammer reaching 2 bar with an acceleration of 88.03 m/s2. The net head after turbulent and friction losses is determined to be 30 m. This study highlights the importance of tailored design strategies in effectively harnessing hydropower resources, offering valuable insights for micro hydropower projects globally.

Harvesting Energy from Rainfall: Initial Study by Exploring Diverse Piezoelectric Array Configurations for Enhanced Electricity Generation in Proteus Software

This paper presents an innovative approach to designing and analyzing a simulated piezoelectric energy harvesting system for electricity generation, employing various array connections using Proteus software. The ingenious concept of harnessing energy from rainfall through piezoelectric technology has become an exciting way to turn a common natural occurrence into a possible power source. The rainfall energy harvesting introduces a novel approach that capitalizes on the mechanical energy imparted by raindrops as they strike surfaces, such as rooftops, pavements, or specially designed structures. This study explores distinct piezoelectric connection types to determine their impact on output voltage, focusing on applications such as rechargeable battery and LEDs. The system begins by harvesting vibration and applying it to the piezoelectric disc. The investigation prioritizes identifying the optimal array connection design. Array configurations of series (S), parallel (P), and combination of series-parallel (SP) are assessed in the simulation. Notably, the series connection of 10 units of piezoelectric elements yielded the highest output voltage at 8.5V. The findings provide valuable insights into finding the optimal array connections in enhancing piezoelectric electricity generation. This research contributes to the leading of potential applications of piezoelectric energy harvesting from rainfall, offering insights into a greener and more self-sufficient energy future.

A novel multi-objective decision-making model to determine optimum resource and capacity configuration for hybrid electricity generation systems: A comparative case study in Türkiye

The rapid depletion of fossil fuels, their negative environmental impacts due to harmful carbon emissions, and the drawbacks of the sole use of intermittent renewable energy resources on system reliability necessitate the use of more advanced energy system technologies. As a result, hybrid electricity generation systems offer an innovative alternative to conventional energy systems. However, the technical complexity and variability of these systems require the application of multi-objective optimization techniques to determine the optimal sizing and system design. Therefore, in this study, we suggest a multi-objective decision-making (MODM) model that involves five conflicting objectives to find the optimal resource configuration and auxiliary source capacity allocation within the framework of the multi-source electricity production method in Türkiye. The MODM model aims to maximize the utilization of resource potentials and the jobs created, while simultaneously minimizing the levelized cost of energy (LCOE), construction duration, and carbon emissions. The MODM model was solved using fmincon and fgoalattain multi-objective optimization algorithms using the Goal Attainment Method in MATLAB and the model results were subsequently compared to the real-world data. According to the model results, the optimal capacity to be allocated for the auxiliary source units is 13,749.58 MWm, while the capacity allocated according to the real-world data as of March 2024 is 2495.49 MWm. In contrast to the model's prediction of 90.8 % solar-based auxiliary unit installations, 99.8 % of auxiliary units are based on solar PV in the actual case. Furthermore, hydro or geothermal-based auxiliary sources are not allocated any capacity, which is consistent with the actual situation. The capacity allocated for the wind (primary source) + solar (auxiliary source) configuration is 76.2 %, whereas in reality, it accounts for 65.6 % of the total installations. Consequently, the model findings suggest that the maximum capacity allocation is for the wind (primary source) + solar (auxiliary source) type hybrid electricity generation system.

Development of multi droplet-based electricity generator system for energy harvesting improvement from a single droplet

Abstract Due to high output performance, the droplet-based electricity generator (DEG) is garnering attention as a promising alternative power source for small electronic devices. Accordingly, to utilize the DEG as a power source, the efforts to boost the output have focused on methods to modify material modification and introduce surface structure. However, the behavior feature that the reconfigured droplet falls after the DEG operation leaves room for one more droplet energy harvesting from a single droplet. Here, a multi DEG system (MDEG) constructed with multiple DEG units is proposed to harvest more energy from a single droplet. The continuous movement of a water droplet is realized through the inclined stair structure of the MDEG, resulting in electrical energy generation from a single water droplet as many times as it falls. In particular, 2-step MDEG consisting of two DEG units can have 45% higher performance than a single DEG. Therefore, this study implies a contribution to the development of DEGs by considering the droplet dynamics, which has been overlooked in existing DEG studies.

The Effect of a Mixture of Methanol and Gasoline on the Operation of an Engine in an Electric Power Generator System

The Effect of a Mixture of Methanol and Gasoline on the Operation of an Engine in an Electric Power Generator System

Parametric optimization for enhancing the electrical performance of hybrid photovoltaic/thermal and thermally regenerative electrochemical cycle system

Globally, the efficient utilization of solar energy has garnered significant attention. A hybrid system of photovoltaic/thermal (PV/T) modules integrated with thermally regenerative electrochemical cycle (TREC), i.e., PV/T-TREC has emerged recently and shows higher efficiency for solar-to-electrical conversion than a standalone PV system. However, there is a trade-off between the electricity generation from PV/T and TREC because the thermal energy from PV/T degrades the efficiency of the PV/T but improves that of TREC. Previous studies have failed to investigate this problem. This study therefore focuses on the key parameters that significantly affect the thermal output of PV/T, i.e., different PV materials, air gaps, heat storage tank volumes, and working fluids to investigate the maximum electrical efficiency of the hybrid system. The mathematical and transient-state numerical models are developed with the validation/refinement from the experiments. The results show that the hybrid system with PV material of cadmium telluride presents the best overall electrical efficiency of 25.37 %. The case of the air gap fosters the solar-to-electrical conversion. The electrical efficiency versus heat storage tank volume shows a convex curve, peaking at 200 L. The nanofluid performs the best. This study may help guide the practical application of such a high-efficiency electricity generation system.

Risk assessment of electric power generation systems using modified jellyfish search algorithm

Risk assessment of electric power generation systems using modified jellyfish search algorithm