Stand-alone Systems Research Articles

Development of Decentralized Speed Controllers for a Differential Drive Wheel Mobile Robot

This research presents a comprehensive mathematical model and a control-oriented model for a differential drive wheel mobile robot (DDWMR). The components and their interconnection within the robot are thoroughly modeled. The proposed mathematical models are used to analyze the characteristics of the robot. The control-oriented model is a simplified one which will be used to design speed controllers. The performance of the proposed system is evaluated through four case studies, focusing on both stand-alone motor systems and the entire DDWMR. The tracking performance is evaluated using metrics such as absolute error integration and root mean square error. Simulation results show that under ideal step command, the pole-zero cancellation PI speed controller achieves the best tracking performance, while PID controllers obtained from Matlab’s Auto-tuning App perform best for standalone motor systems. For motors in a DDWMR, the PID controller with parameters derived from the Ziegler-Nichols tuning rules provides optimal tracking performance. These simulation results show that there is no universal controller that can achieve the best performance in all situations; rather, each controller is suited to specific circumstances. Nonetheless, in all case studies, better motor speed tracking leads to improved trajectory tracking performance for the robot.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

Maximizing the use of hydrogen as energy vector to cover the final energy demand for stand-alone systems, application and sensitivity analysis for the Canary Archipelago by 2040

Fossil fuel-based economies must undergo a deep transition for complete decarbonization. To this end, it is widely recognized that all economies must move towards the electrification of energy end uses. Even though there is a part that cannot be electrified, at least at affordable costs; clear examples are heavy road transport, maritime and air transport, and some industrial processes. As a result of the limitations of electrification in certain energy end uses, the potential use of hydrogen as an alternative energy carrier has been examined in recent decades. Hydrogen is seen as a viable option for the medium to long term. Specifically, efforts are being made in the case of the Canary Islands to move towards a carbon-free energy mix. In fact, the aim is to advance the economy decarbonization by 10 years over the date foreseen for both Europe and the rest of Spain. To this end, the HOMER program has been used to analyze the possibility of producing the necessary hydrogen in a scenario applied to the Canary Islands in which the uses of this energy vector have been maximized. This research considers two possible scenarios, together with a sensitivity analysis under the different uncertain conditions associated with the used technologies. The results have been the estimation of hydrogen production costs for high demands, about 230,000 tH2/year, in 2040 for an isolated archipelago under two totally different generation scenarios. The first scenario is totally renewable, while the other is based on nuclear generation by means of high-temperature SMRs. The results show, that it would be possible to produce at a cost in the range of 1 €/kgH2 using nuclear technology and around 4 €/kgH2 using renewables, with uncertainty cost ranges of around 40%, i.e. costs between 0.85-1.48 and 3.29–4.99 € kgH2 respectively.

Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller

The Photovoltaic (PV) system is an eco-friendly renewable energy system that is integrated with a DC-DC buck-boost converter to generate electrical energy as per the variations in solar irradiance and outdoor temperature. This article proposes a novel Adaptive Fractional Order PID (A-FOPID) compensator with self-adjusting fractional orders to extract maximum power from a stand-alone PV system as ambient conditions change. The reference voltage is generated using a feed-forward neural network. The conventional FOPID compensator, which operates on the output voltage error of the interleaved buck-boost converter, is employed as the baseline maximum-power-point-tracking (MPPT) controller. The baseline controller is retrofitted with an online state-error-driven adaptation law that dynamically modifies the fractional orders of the controller’s integral and differential operators. The adaptation law is formulated as a nonlinear hyperbolic scaling function of the system’s state error and error-derivative variables. This augmentation supplements the controller’s adaptability, enabling it to manipulate flexibly the tightness of the applied control effort as the operating conditions change. The efficacy of the proposed control law is analyzed by carrying out customized simulations in the MATLAB Simulink environment. The simulation results show that the proposed MPPT control scheme yields a mean improvement of 25.4% in tracking accuracy and 11.3% in transient response speed under varying environmental conditions.

Poultry-Edge-AI-IoT System for Real-Time Monitoring and Predicting by Using Artificial Intelligence

Poultry farms have played a significant role throughout human history, in feeding the growing population. A good environment is a perfect condition for the growth of poultry, preventing disease, and effective production. The temperature higher and the humidity favor the growth of bacteria and hence the production of ammonia (NH3) by the decomposition of organic matter. Ammonia (NH3), carbon monoxide (CO), and carbon dioxide (CO2), Methane (CH4), hydrogen sulfide (H2S) are poisonous gases that can cause poultry diseases and mortality. The combination of Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing offer efficient and intelligent stand-alone systems of monitoring in real-time, predicting, and advanced automation. The paper aims to monitor in real-time and predict poultry barns' environmental conditions using an artificial intelligence algorithm. An intelligent system called Poultry-Edge-AI-IoT has been developed to gather, hash, store, pretreat, filter, knowledge extract, and transmit information from a heterogeneous wireless sensor network. The Poultry-Edge-AI-IoT system is based on IoT, AI, and Edge Computing for the detection of potential stress, the harmful gas concentration, and the prediction of poultry barns' environmental conditions. The system is modular and upgradeable.

Biomass power plants

Biomass power plants

Techno-economic Feasibility Analysis of Optimized Stand-alone PV and Hybrid Energy Systems for Rural Electrification in INDIA

Techno-economic Feasibility Analysis of Optimized Stand-alone PV and Hybrid Energy Systems for Rural Electrification in INDIA

Comparative techno-economic analysis of various stand-alone and grid connected (solar/wind/fuel cell) renewable energy systems

This article proposes a hybrid energy model comprising of various stand-alone and grid-connected energy systems including grid-connected hybrid, off-grid hybrid, fuel cell-photovoltaic, fuel cell-wind turbine, photovoltaic-wind turbine, wind turbine, and photovoltaic to fulfill the power requirements of an educational institute in Pakistan. These systems have been developed, simulated, and optimized for techno-economic feasibility, taking into consideration the electricity demand profile, geographic regions, and climatic data. A sensitivity analysis has been conducted to determine the most economical systems for producing 0.90079 MWh of energy per day. Simulation results show that the net present cost of the grid-connected hybrid system is between M$ 1.536859 and M$ 6.818162, while the cost of energy is between $ 0.155 and $ 0.3749 per kWh. The fuel cell -wind turbine system incurs a maximum energy cost of $ 0.3749/kWh. The solar and grid-connected hybrid systems offers the lowest net present cost and cost of energy, which are M$ 1.536859 and $ 0.155/kWh, respectively. The research findings suggest that utilizing photovoltaic, wind, and fuel cells is a more feasible and economical strategy due to system benefits. The study also showed the viability and efficiency of using solar and wind resources for hydrogen production and power generation. Additionally, the study demonstrated that hydrogen is a more affordable option for long-term energy storage than batteries.

Optimization of a Tidal–Wind–Solar System to Enhance Supply–Demand Balancing and Security: A Case Study of the Goto Islands, Japan

Due to the expected increase in electric power demand in the coming decades and the economic and environmental issues caused by power generation from the combustion of hydrocarbon fuels, the integration of renewable energy into the grids of remote islands has attracted attention. Among all renewable sources, tidal stream energy shows potential to contribute positively in areas with strong tidal currents due to the predictability and semi-diurnal periodicity of the resource, which makes it compatible with short-term energy storage. However, its performance in areas with lower available power density has not yet been addressed. In this paper, energy systems for the Goto Islands, Japan which combine solar, offshore wind, and tidal energy are evaluated based on whole-system performance indicators such as the annual energy shortage and surplus and the battery load factor. Without energy storage, an energy mix of 31% solar, 47% offshore wind, and 22% tidal energy provides the lowest values for annual energy shortage (29.26% of total power demand) and surplus (29.26%). When batteries are incorporated into the system, tidal stream energy is the main contributor to reducing these two parameters, with values up to 23.58% and 19.60%, respectively, for the solar and tidal scenario with 30 MW of installed storage capacity. These results show the advantages of tidal stream energy exploitation in stand-alone energy systems, even with relatively low capacity factors (0.33).

Thermo-economic optimization and comparative analysis of different organic flash cycles for the supercritical CO2 recompression Brayton cycle waste heat recovery

It is well known that the energy efficiency of the supercritical carbon dioxide recompression Brayton cycle (sCO2RBC) can be improved by employing the bottoming cycles to recover its large waste heat. To achieve better performance, three bottoming cycles with a good temperature matching with the sCO2 stream, namely the basic organic flash cycle (BOFC), the regenerative organic flash cycle (ROFC), and the organic flash Rankine cycle (OFRC), are employed to combine with the sCO2RBC in this work. The parametric analysis is performed to determine the variation trends of systems’ thermodynamic and exergoeconomic performance with five important parameters. The single-objective optimization is conducted for the sCO2RBC/BOFC, sCO2RBC/ROFC and sCO2RBC/OFRC systems with six organic fluids. The single-objective optimization results show that the highest exergy efficiency of the sCO2RBC/OFRC is higher than that of the rest combined sCO2RBC/OFCs by up to 1.95%. And the lowest total product unit cost for the sCO2RBC/OFRC is up to 0.93% lower than that of the rest combined sCO2RBC/OFCs. Finally, a comparative analysis is performed for the three combined sCO2RBC/OFCs, sCO2RBC/ORC and stand-alone sCO2RBC systems under the multi-objective optimization conditions. Results show that the integrated systems can improve the ηex by 4.62–6.06% and reduce the cp,tot by 2.68–3.14% when taking the sCO2RBC system as the baseline system. The sCO2RBC/OFCs and sCO2RBC/ORC are recommended to use R1336mzz(Z) and R245fa as working fluids, respectively. Moreover, the sCO2RBC/OFRC system achieves an improvement of 0.41%–1.37% in exergy efficiency with a comparable total product unit cost, compared to other aforementioned integrated systems.

Increasing photovoltaic system power output with white paint albedo – a scenario in Al-Mausaib City using PVSyst. software

<p>Sundry circumstances influence on the photovoltaic (PV) performance, <br />a ground albedo one of an important factor that effect on the PV panel work. This research study is to improving the output solar structures fixed on horizontal of the buildings of the even surface with adjustable roof albedo; this study incorporates integrating innovative PV and levelheaded surface techniques to boost the energy production of photovoltaic system. The modeling and simulation study were utilized as part of the system to examine the effectiveness of the solar structure installed on concrete horizontal even tiles structures with a roof albedo of 0.25, After that, white paint was applied to the concrete surface in front of the solar system to raise the albedo to 0.70. The important findings demonstrate that a rise in surface albedo from 0.25 to 0.7 will contribute to an increase in yearly solar PV power generation. The case study scenario in Al-Mussaib Technical College (L at 32° 46′ 59.99″ N, 44° 19′ 0.01 E), this paper will study the effects of two different materials top surface on the yield of PV module, for these studies, the PVSyst. program version 7.2 is utilized to analysis data from PV solar stand-alone systems.</p>

Determination of a New Performance Indicator for the Assessment of Stand-Alone PV System

The use of stand-alone PV systems (SAPV) must be efficient and profitable for a better integration of solar energy in the global energy mix. However, the performance indicators that allow the evaluation of SAPV systems do not clearly inform us about the actual level of use of their sized and installed capacity. This article aims to determine a new performance indicator, called the theoretical power factor (TPF) by an original method based on the modelling of the SAPV system in the form of a matrix equation. The resolution of this matrix equation, makes it possible to bring out the reactive energy of the system during operation. A case study is presented and scenario I represents the case where the main elements are all assumed to operate at their rated capacity. scenario II represents the case were the rated capacity of storage system is reduced of 40%, scenario III represents the case were the rated current capacity of charge controller is reduced of 40%, and finally scenario IV represents the case were the rated power capacity of inverter is also reduced of 40%. The results obtained after implementation in the Spyder environment (python 5.1) show the effectiveness of TPF in the performance evaluation of SAPV systems. And also show how the TPF is substantially related to the capacity of each main element of the system. This being proved by the results obtained after the simulation of the four scenarios mentioned above. One can observe an increase in TPF of 0.1% in Scenario II during the period of low irradiance, and no change in TPF for the other scenarios in the same period. During the period of high irradiance, an increase in TPF of 17.9% is observed in scenario II and a decrease in TPF of 15.4% and 1.2% respectively in scenarios III and IV.

Synchronous Light Harvesting and Energy Storing Organic Cathode Material 1,4-Dihydroxyanthraquinone for Lithium-Ion Batteries

The electrode materials for lithium-ion batteries which offer integrated conversion of light and storage of electricity are auspicious for compact and stand-alone energy systems. Herein, coin-cell lithium batteries based on organic compound 1,4-dihydroxyanthraquinone coupling porous carbon derived from MOFs (1,4DHAQ&ZIF-8C) are demonstrated. The proposed material simultaneously acts as lithium storing and photoactive electrode. Along with the electrochemical lithium-ion reactivity, 1,4DHAQ&ZIF-8C offers notable photoelectric properties, its specific capacity increases to 285mAh g-1 (1.58 times of the specific capacity without light) when illuminated, and the lithium-ion mobility improves to 0.313cm2 s-1 (up by 55%), meanwhile its charge transfer resistance decreases to 95.6Ω (down to 39%). Moreover, theoretical excited state analysis and microsecond measurements reveal the existence states of photogenerated carriers, demonstrating obvious intramolecular charge transfer and nanosecond-scale exciton lifetime (∼5ns). Our findings suggest valuable directions to advance the current strategies for the assembly of efficient photo-rechargeable lithium-ion batteries.

Technical and economic evaluation of a novel liquid CO2 energy storage-based combined cooling, heating, and power system characterized by direct refrigeration with phase change

Energy storage systems combining cooling, heating, and power have higher flexibility and overall energy efficiency than standalone systems. However, achieving a large cooling-to-power ratio in direct-refrigeration systems without a phase change and in indirect refrigeration systems driven by heat is difficult, limiting the energy output of the system. Therefore, this study proposes a novel combined cooling, heating, and power system based on liquid CO2 energy storage. Using direct refrigeration with a phase change, the system has a large cooling capacity and can achieve a wide range of cooling-to-power ratios through the mass flow regulation of the refrigeration branch. Energy, exergy, and economic analyses were conducted based on models of the proposed system. Adjusting the split ratio of the system splitter S1 can realize a wide range of changes in the cooling- and heating-to-power ratios of the system and can flexibly meet the demand for cooling, heating, and power generation. The system with the best overall performance was obtained by optimizing the levelized cost of storage as the objective function, where the system’s power efficiency, exergy efficiency, energy efficiency, levelized cost of storage, and energy storage density were 0.56 %, 18.15 %, 319.76 %, 0.10 $/kW·h, and 19.17 kW·h/m3, respectively. The proposed system in the standalone power-storage mode has technical and economic performance advantages, as compared to other systems reported in the literature.

Contribution to strengthening Bus voltage stability and power exchange balance of a decentralized DC-multi-microgrids: Performance assessment of classical, optimal, and nonlinear controllers for hybridized energy storage systems control

Stability is the primary goal in standalone power systems due to the high penetration and uncertainties of renewable energy resources, so the system reliability is affected, and the hybrid energy storage system (HESS) and diesel generator (DG) compensate for renewables' failures. This study contributes to managing and controlling DC-coupled multi-Microgrids fed by Photovoltaic, HESS, and DG resources and subjected to pulsed loading and uncertain PV outputs, besides battery SOCs and DG fuel constraints. The Dual-loop control structure compares classical Proportional Integral (CPI), Super-Twisting-Sliding-Mode-Control (ST-SMC), and Linear Quadratic Regulator with Integral Action (LQR-I) to evaluate the robustness and control performance of the HESS. For the supercapacitor (SC), a hysteresis current control (HCC) tracks its setpoint currents using a frequency decoupling-based power-split control. Matlab simulations confirmed system reliability by combining controllers with different Key Performance Indicators, where adopting the LQR-I for bus voltage regulation and the ST-SMC for HESS current control outperformed the other combinations and revealed superior system performance, improving Bus voltage regulation, DG current tracking, overall system efficiency, and loading convergence by 67.63(%), 83.63(%), 77.92(%), and 2.72(%), respectively. Instead, the basic CPI enhanced battery and SC current control with 51.55 and 63.94 (%) compared to the winner scenario.

Optimal coordinated energy management strategy for standalone solar photovoltaic system with hybrid energy storage

Energy storage devices and renewable resources, especially rooftop photovoltaic (PV), are vital to the operation of standalone systems. In this study, an energy management strategy (EMS) for battery energy storage systems (BESS), PV, and supercapacitors (SC) is presented. The proposed control strategy is designed to optimize the BESS flow rate, discharge, and charge cycles of the energy system using the Meta-heuristic Jaya algorithm by properly coordinating SC and PV. SC is employed in HESS to fulfill the transient energy mismatches and reduce the transitory high charge/discharge current rate impacts on BESS using EMS. The proposed controller also has the benefit of keeping the battery's SoC within limitations for a long period. To extend the life of BESS, the EMS is aimed at minimizing deep charging and discharging by reducing PV generation, particularly under light load (no-load) situations and when battery and SC's SoC≥SoCmax or charging. Similarly, the optional load shedding is employed when battery and SC's SoC≤SoCmin to avoid deep discharge. The proposed EMS is validated in both simulation environment and hardware-prototype under different perturbations and operating conditions. The charge and discharge rate performance of BESS and SC under different charge and discharge time durations, i.e., 1 s, 2 s, and 3 s, were evaluated in both simulation and hardware, and compared to conventional charge and discharge methods for HESS, whose charge and discharge time durations are nearly 0.3 s to 0.4 s. As a result, battery stress is significantly reduced. Furthermore, the economic analysis of the complete system is carried out. In this, it is observed that standalone PV and HESS systems with the proposed EMS are cost-effective and economical compared with PV and BESS systems when operated for a long horizon beyond 6 years.

Energy Independence of a Small Office Community Powered by Photovoltaic-Wind Hybrid Systems in Widely Different Climates

Hybrid renewable energy systems are an optimal solution for small energy communities’ energy supply. One of the critical issues is the strong correlation of these systems with outdoor climatic conditions. The goal is to make local communities increasingly energy independent. To this end, an in-depth analysis of the behaviour of hybrid photovoltaic (PV)–wind systems powering small office communities in 48 locations around the world characterized by widely varying climates was conducted. System sizes, assumed to be stand-alone or grid-connected, were varied, for a total of 343 system power configurations. Highest satisfied load fraction (SLF) values are obtained with a significant predominance of PV over wind; the trend is more pronounced in dry and continental climates (zones B and D according to the Köppen climate classification). The utilization factor (UF) values of 1 are rarely reached and never in the wind-only or PV-only configurations. In all climates, the grid energy interaction factor (GEIF) values of zero are never reached but come very close. The benefit-cost ratio (BCR) of grid-connected systems is significantly higher than stand-alone systems.

Forecast-based charging strategy to prolong the lifetime of lithium-ion batteries in standalone PV battery systems in Sub-Saharan Africa

Standalone PV battery systems have great potential to power the one billion people worldwide who lack access to electricity. Due to remoteness and poverty, durable and cheap systems are required for a broad range of applications. However, today’s PV battery systems do not yet fully meet this requirement. Especially batteries still prove to be a hindrance, as they represent the most expensive and fastest-aging component in a PV battery system. This work aims to address this by prolonging battery life. For this purpose, a forecast-based charging strategy was developed. As lithium-ion batteries age slower in a low state-of-charge, the goal of the operation strategy is to only charge the battery as much as needed. The impact of the proposed charging strategy is examined in a case study using one year of historical data of 14 standalone systems in Nigeria. It was found that the proposed operation strategy could reduce the average battery state-of-charge by around 20% without causing power outages for the mini-grids. This would significantly extend the life of the battery and ultimately lead to a more durable and cheaper operation of standalone PV battery systems.

Efficiency analysis of grid tied PV system with KY integrated SEPIC converter

Today's power generation relies heavily on renewable energy, which also contributes to distributed generation, microgrids and smart cities. PV system is a rapidly developing source of renewable energy and acts as stand-alone or grid-connected systems. The utilization of PV energy faces a drastic increase due to the high efficiency of solar cells and enhancements in the design of PV panels. It demands high gain converters for major applications but existing converters generate pulsating outputs leading to output voltage with ripples. In this view, researchers are constantly focusing on converters with increased efficiency and gain generating minimized ripples in resulting current and voltage. Considering these dilemmas, an efficient PV system with KY integrated SEPIC converter is introduced in this article. The KY converter provides improved voltage conversion ratio as well as minimizes the voltage stress while the SEPIC converter offers added step up gain. The proposed converter is regulated by a GWO tuned PI controller for solving the optimization issues. It prevents the local optimum and is robust, simple with the application to complicated optimization tasks. A grid connected 1φ VSI is adopted for ensuring smooth operation with the aid of PWM generator. The simulations are carried out in MATLAB simulation software to prove the efficacy of the introduced approach. The obtained outputs reveal that this developed system has minimal THD value of 1.6% and hence it has higher efficiency which is marked as 97%.

More than two decades of research on IoT in agriculture: a systematic literature review

PurposeAgriculture is one sector where the Internet of things (IoT) is expected to make a major impact. Yet, its adoption in the sector falls behind expectations. The purpose of this paper is to present the state-of-the-art of IoT in agriculture and investigate its slow adoption in the sector.Design/methodology/approachThe authors have undertaken a systematic review and a synthesis of 1355 relevant publications over the last decade.FindingsThis literature review reveals that the “big three” barriers for the overall sector are cost, skills and standardization. The lack of connectivity and data governance are two key reasons why most of the proposed IoT solutions are standalone systems of limited scope, while the majority of commercial IoT efforts focus on practices in the protected indoor environment. Lastly, the analysis of past research along the five layers of the IoT system architecture reveals limited attention to barriers and solutions at the business layer, which represents a research opportunity for information systems scholars.Research limitations/implicationsIt is possible that some of relevant publications were missed in the literature search, although the search queries were kept as broad as possible to avoid the exclusion of any relevant work. Any publication written in any other language other than English was excluded from the review. Given the geographical distribution of the reviewed English publications (see section 4.1), it is highly likely that important works written by Chinese and European scholars in their native language were overlooked.Practical implicationsThis study provides practical insights into the technical and organisational challenges on the ground. It is the hope that this literature review lays the groundwork for IS researchers who are well positioned to investigate technology adoption challenges in the relatively understudied agriculture sector.Originality/valueTo the best of the authors’ knowledge, this is the first comprehensive review of adoption barriers and solutions across all five layers of the IoT system architecture.

Active hybrid energy storage management in a wind-dominated standalone system with robust fractional-order controller optimized by Gases Brownian Motion Optimization Algorithm

Accessibility to sustainable and reliable electrical energy for remote area power supply (RAPS) systems under high penetration levels of wind energy requires adopting appropriate technologies and controllers. In recent years, energy storage has gained significant attention for smoothing inherent voltage and power fluctuations of standalone systems. This paper presents a filtration-based fractional-order PI (FOPI) controller optimized by Gases Brownian Motion Optimization (GBMO) algorithm to manage an active battery-supercapacitor hybrid energy storage system (HESS) in a wind-dominated RAPS system. The GBMO algorithm has a high accuracy and convergence rate among optimization algorithms introduced in recent years. Moreover, a fuzzy logic controller (FLC) guarantees the wind turbine generator's maximum power point tracking (MPPT) at any wind condition while mitigating its fluctuating torque. The proposed RAPS system uses the advantages of the FOPI controller, the GBMO optimization algorithm, the FLC-based MPPT algorithm, and a high-pass filter to manage precise coordination between different components of the RAPS system. The high-pass filter decouples high and low-frequency voltage oscillations to modify the HESS performance and relieve battery stress, thereby extending its lifespan. The proposed controller's performance and robustness are verified in comparison with an optimal PI controller based on GBMO under turbulent wind speed and load step changes in a detailed model of the system. The results demonstrate the superiority of the optimal FOPI controller over the optimal PI controller.