Autonomous Energy Research Articles

Uncertainty analysis of the electric vehicle potential for a household to enhance robustness in decision on the EV/V2H technologies

Electric vehicles (EVs) and vehicle-to-home (V2H) technologies are regarded as promising technologies for optimizing household energy management, particularly as valuable resources for optimizing the management of distributed photovoltaic (PV) generation. However, the potential of EVs and V2H for households is closely related to their usage behavior. As EVs and V2H technologies are big investments for a family, especially for families in rural area, their benefits for households need to be analyzed in an uncertain environment to obtain robust results and mitigate investment risks for households. To achieve this, this study builds a 7-parameter stochastic model to simulate random driving patterns and employs a mixed-integer linear programming model to derive the optimal solution for the household energy system. Subsequently, the potential value of EVs and V2H technologies for a household is assessed based on three key performance indicators: economic viability, carbon emissions reduction, and energy and power autonomy. The findings of this study demonstrate that the EV is a viable technology for significantly reducing household energy expenditures, lowering household carbon emissions, and enhancing household energy and power autonomy. Furthermore, the V2H technology can provide additional benefits by further reducing carbon emissions as well as increasing the autonomy of the household energy system. However, the impact of V2H technologies on household energy expenditures is limited. The above conclusions still hold when the EV travel behavior stochasticity is taken into account, but an unexpected finding is that EV travel behavior stochasticity has almost no effect on the economy and carbon emission indicators, while significantly affecting the autonomy of the household energy system. Further investigation uncovers that the external charging price plays a critical role in determining the potential of EV + V2H technology as both stationary and mobile energy storage for households. Additionally, it is observed that the impact of EV travel behavior stochasticity on household energy expenditures becomes pronounced as the external charging price decreases, which can assist families in making reasonable decisions on configuring emerging technologies, like EV and V2H.

Design Optimization Of PV And WTE Integration In Electricity Supply System For Mandalay Urban Area

Hybrid energy systems, which combine two or more energy systems, arebecoming increasingly popular due to the rise in petroleum productprices, growing CO2 emission awareness, and advancements in renewableenergy technologies. These systems are being adopted to meet the energyand electricity demands of decentralized networks. In Myanmar, someareas still face significant challenges in accessing grid-based electricitysupply. In such cases, the hybrid renewable microgrid systems offer abetter alternative by reducing dependency on diesel fuel and meetingenergy demands in an environmentally friendly manner. To enhance thereliability of these hybrid systems, renewable sources can be integratedwith diesel generators and utility grid. This integration allows hybridsystems to compensate for the intermittent nature of renewable energysources and achieve higher overall energy efficiency. One of the mainadvantages of hybrid systems is their potential for energy autonomy, asthey are not reliant on a single energy source. This paper introduces anovel approach for designing a grid connected hybrid system thatincorporates photovoltaic, and biomass especially the municipal solidwaste. The Hybrid optimization model for electrical renewable (HOMER)is a powerful optimization model that simplifies the evaluation of off-gridand grid-connected power system designs for various applications. In thispaper, the grid connected hybrid renewable energy system is designedand analyze for Mandalay region.

Optimizing hydraulic retention time of high-rate activated sludge designed for potential integration with partial nitritation/anammox in municipal wastewater treatment

The integration of high-rate activated sludge (HRAS), an effective carbon redirection technology, with partial nitritation/anammox (PN/A) is a novel AB treatment process for municipal wastewater. In this study, an airlift HRAS reactor was operated in the continuous inflow mode for 200 d at a wastewater treatment plant. The balance between potential PN/A system stability and peak HRAS performance under decreasing hydraulic retention time (HRT) was optimized. Energy consumption and recovery and CO2 emissions were calculated. The results showed that the optimal HRT suitable with the PN/A process was 3 h, achieving 2–3 g/L mixed liquor volatile suspended solid, 67.8 % chemical oxygen demand (COD) recovery, 81 % total COD removal efficiency, 2.27 ± 1.03 g COD/L/d organic loading rate, 62 % aeration reduction, and 0.24 kWh/m3 power recovery potential. Such findings hold practical value and contribute to the development of the optimal AB process capable of achieving energy autonomy and carbon neutrality.

Machine Learning-Driven Energy Harvesting and Storage System Design for IoT Applications in Smart Buildings.

The advent of Internet of Things (IoT) technologies has revolutionized the concept of smart buildings, integrating diverse sensors and devices for enhanced automation and efficiency. Avinash B. Raut, Energy harvesting and storage technologies have emerged as promising solutions to address the power requirements of IoT devices in smart buildings. This abstract provides a comprehensive overview of machine learning-driven energy harvesting and storage system design tailored specifically for IoT applications in smart buildings. Traditional energy management systems often face challenges such as suboptimal energy utilization, limited scalability, and lack of adaptability to dynamic environmental conditions. In contrast, machine learning techniques offer adaptive, data-driven solutions to optimize energy harvesting, storage, and distribution in smart buildings. [1] This paper explores various machine learning algorithms, including supervised learning, reinforcement learning, and deep learning, and their application in optimizing energy harvesting from ambient sources such as solar, kinetic, and thermal energy. Moreover, machine learning enables predictive energy demand modeling by analyzing historical data and environmental factors, thus enhancing the efficiency of energy storage and distribution systems. Real-world case studies and experimental results are presented to demonstrate the effectiveness and potential of machine learning-driven energy management systems in improving energy efficiency, reliability, and autonomy in IoT-enabled smart buildings DOI: https://doi.org/10.52783/tjjpt.v45.i02.6318

Revving up energy autonomy: A forecast-driven framework for reducing reverse power flow in microgrids

Reverse power flow, defined as the continuous flow of electricity in a direction opposite to the normal direction of the power flow in a grid, typically occurs in microgrids when the energy generated by the distributed electric power plants exceeds the local load demand. This phenomenon imposes several risks related to inefficient operation or damage of equipment, grid instability, and energy losses. In order to reduce reverse power flow in microgrids and support energy autonomy, we introduce a forecast-driven framework. The framework builds upon deep learning models that forecast the electricity produced (photovoltaic systems) and consumed by the microgrid and an optimization algorithm that schedules its shiftable loads (electric vehicles) based on said forecasts. We conduct an ablation study to evaluate the effect that optimized scheduling and energy storage has on the autonomy of the microgrid, also investigating the impact of different capacities of batteries and sizes of electric vehicle fleets. Our results suggest that forecast-driven load shifting can significantly reduce reverse power flow, especially for relatively larger amounts of shiftable loads. Moreover, we find that electricity storage can complement load shifting, further improving its beneficial effect. Nevertheless, these improvements are subject to forecast accuracy and storage abilities.

EU-Chile Horizons: Climate Justice for a Shared Strategy on Critical Minerals

The European Union has not only raised the need for strategic autonomy, but has also opened up to re-establishing new relationships. One of these relationships in the spotlight is Latin America, which has the highest concentration of critical minerals, key, among other things, for the energy transition of the Union and Latin America itself. However, the instruments of European law have become more flexible beyond Mercosur and the prevailing formalism, and a new cycle of relations is being generated. To a large extent, this adaptation may combine new ways of conceptualizing the role of "strategic for both parties", since European energy autonomy and the business diplomacy experienced by some Latin American countries such as Chile are not mutually exclusive. The Chilean case is paradigmatic of this crossroads, as the country is part of the new wave of natural resource sovereignty, but at the same time it is considering executing the development imaginary together with the geopolitical interests of the European Union.

Power to the People: On the Role of Districts in Decentralized Energy Systems

The transition towards renewable and decentralized energy systems is propelled by the urgent need to address climate concerns and advance sustainable development globally. This transformation requires innovative methods to integrate stochastic renewable sources such as solar and wind power and challenging traditional energy paradigms rooted in centralized and continuous energy production. The present study focuses on the Swiss energy system to explore the optimization of energy planning strategies that incorporate decentralized energy production within a centralized framework. Here, we show that a strategic approach to decentralization can significantly reduce annual system costs by 10% to CHF 1230 per capita and increase self-consumption to 68% of the decentralized PV production, emphasizing the need for a hybrid energy-planning model that balances centralized and decentralized models for enhanced system resilience, efficiency, and cost-effectiveness. This research underscores the strategic importance of diversifying energy sources, enhancing energy storage, improving grid flexibility, and laying a foundational framework for policy making and strategic planning. It encourages further investigation into climate impacts, technology synergy, and the integration of district heating, aiming to establish a resilient, sustainable, and autonomous energy future.

Fostering Sustainability through the Integration of Renewable Energy in an Agricultural Hydroponic Greenhouse

This research explores the feasibility of integrating renewable energy sources, such as solar and wind, to power a hydroponic greenhouse. In this way, the latter’s energy autonomy is ensured. The study begins by evaluating the annual electricity consumption of the examined system. A renewable energy system capable of meeting its energy requirements throughout the year is also designed. The main objective is to assess the efficiency of two types of renewable energy sources, namely photovoltaic panels and wind turbines, and to improve their integration within the agricultural chamber by implementing a model simulation. Two scenarios were examined: the first one represents a photovoltaic power plant with storage, connected to the grid, while the second scenario presents a wind power plant connected to the grid. This numerical analysis is supplemented by a one-year experimental study of a photovoltaic installation connected to the network with storage, which in turn is connected to the experimental device. To handle energy within the renewable energy greenhouse, an energy management system was developed based on a fuzzy logic controller. This system aims to maintain energy balance and ensure continuous power supply. The energy management system optimizes energy flow to minimize consumption, reduce grid dependence, and improve overall system efficiency, resulting in cost savings and certain environmental benefits.

The Socio-economic impact of decarbonising geographical Islands' energy systems

The impact of the transition to energy autonomy on two geographical island’s local economies, through maximising renewable energy generation and storage, is assessed. The different sectors and activities that impact employment and income generation in the local economies of each of the islands are described. An empirical assessment approach based on the Keynesian Income Multiplier (KIM) is developed and applied using Analytical Hierarchy Process (AHP). Data for AHP was collated through interviews with local experts and stakeholders on each island. Gender employment and wage data was used to calculate the impact on female waged employment within the islands’ economic sectors. The analysis conducted showed that the induced local economic impact per unit of electrical energy due to the new RES-based autonomy in all sectors for male waged employment for both islands, exceeds its unit cost (LCOE). While the profits from per unit of electrical energy for the female waged employment only exceeded the unit cost (LCOE) in tourism for La Graciosa, and three other sectors in Gotland. The local economic impact from decarbonisation and 100% energy autonomy is significantly influenced by how the income from this renewable energy is recirculated within the island’s economic sectors, most essentially, tourism. Our findings suggest that strategies for community ownership and training local people to manage renewable energy facilities is necessary to maximise the benefits of the transition to energy autonomy on local communities.

Decentralized Autonomous Energy Management Strategy for Multi-Paralleled Hybrid Energy Storage Systems in the DC Microgrid With Mismatched Line Impedance

Decentralized Autonomous Energy Management Strategy for Multi-Paralleled Hybrid Energy Storage Systems in the DC Microgrid With Mismatched Line Impedance

Autonomous self-healing hybrid energy harvester based on the combination of triboelectric nanogenerator and quantum dot solar cell

Realization of multi-source energy harvesting with one single device would maximize power output. Thus, it is emerging as a promising strategy towards renewable energy generation and has attracted worldwide attention in the past decades. Capable of capturing mechanical energy that is ubiquitous in the ambient environment, triboelectric nanogenerator (TENG) has been considered a novel yet effective source towards next-generation energy harvesting. In this work, a flexible hybrid energy harvester (HEH) is developed via the rational integration of autonomous self-healing TENG and high bending-stable lead sulfide quantum dot (PbS QD) solar cell, enabling independent electricity generation by two different mechanisms. The single-electrode mode TENG component with self-healing is realized by a polydimethylsiloxane/Triton X-100 (PDMS/TX100) mixture as the dielectric layer and the shared gold (Au) electrode, which generates 0.39 µA of output current (Iout), 24.6 V of output voltages (Vout), 15.4 nC of transfer charges (Qsc), and 7.80 mW m−2 of output power peak density. The thin-film solar cell component is based on a PbS QD layer as the light absorber with a planar structure fabricated under low-cost and compatible conditions, achieving 22.8 mA cm−2 of short-circuit current density (Jsc) and 4.92% of power conversion efficiency (PCE). As a proof of concept, an electronic watch is successfully powered by harnessing ambient mechanical and solar energy with a hybridized energy cell. This approach will offer more opportunities to construct a versatile platform towards remote monitoring and smart home systems.

Energy Harvesting and Storage with a High Voltage Organic Inorganic Photo‐Battery for Internet of Things Applications

Integrated local energy harvesting and storage is a critical prerequisite for energy autonomy of distributed sensing arrays required for the implementation of the internet of things (IoT). In this context, the monolithic integration of solar cells with metallic lithium‐based batteries into stacked high voltage photo‐batteries allows to provide said energy autonomy, with the smallest possible footprint and the highest resource efficiency. However current photo‐battery designs require additional electronics to control and match power output like maximum power point (MPP) tracking and overcharge protection. Herein a novel and compact monolithic photo‐battery design is provided, advantageously combining an organic solar cell with a NMC 622 versus metallic lithium‐based battery, matched in terms of VOC and cut‐off voltage, thereby achieving photo‐charging without any control electronics and energy release on demand at a very compact footprint of only 2.5 cm × 2.5 cm × 0.2 cm. Additionally, by applying a power profile simulating a temperature and humidity sensor over the course of a 24 h light and dark cycle, real world applicability of the photo‐battery in this type of applications is demonstrated.

Implementation of a Wireless Sensor Network for Environmental Measurements

Nowadays, the need to monitor different physical variables is constantly increasing and can be used in different applications, from humidity monitoring to disease detection in living beings, using a local or wireless sensor network (WSN). The Internet of Things has become a valuable approach to climate monitoring, daily parcel monitoring, early disease detection, crop plant counting, and risk assessment. Herein, an autonomous energy wireless sensor network for monitoring environmental variables is proposed. The network’s tree topology configuration, which involves master and slave modules, is managed by microcontrollers embedded with sensors, constituting a key part of the WSN architecture. The system’s slave modules are equipped with sensors for temperature, humidity, gas, and light detection, along with a photovoltaic cell to energize the system, and a WiFi module for data transmission. The receiver incorporates a user interface and the necessary computing components for efficient data handling. In an open-field configuration, the transceiver range of the proposed system reaches up to 750 m per module. The advantages of this approach are its scalability, energy efficiency, and the system’s ability to provide real-time environmental monitoring over a large area, which is particularly beneficial for applications in precision agriculture and environmental management.

A techno-economic-environmental assessment and control strategy for hybrid renewable energy based autonomous microgrid energy infrastructure in island societies of Northern India

A techno-economic-environmental assessment and control strategy for hybrid renewable energy based autonomous microgrid energy infrastructure in island societies of Northern India

Just transitions and sociotechnical innovation in the social housing sector: An assemblage analysis of residents’ perspectives

Creating low-carbon pathways for domestic electricity and heating is a core aspect of the UK Government's housing strategy. Understanding issues of energy justice and the socio-technical dynamics of low-carbon innovation are vital for successfully implementing new technologies and retrofit measures across diverse communities and different housing types. The social housing sector is particularly important in the study of just domestic low-carbon transitions due to the challenges faced by residents concerning energy affordability and insecurity during the ongoing cost of living crisis in the UK. This qualitative study, conducted in the Northeast of England, adopts an assemblage thinking approach to examine the experiences of social housing residents. Through thematic analysis of interviewee responses, we identify themes related to cost and affordability; decision-making dynamics and energy justice; disruption, retrofit and ‘fabric first’; energy autonomy and the practicalities of technology choice; and environmental values and collective climate action. We find that justice in the low-carbon home requires social housing organisations to strengthen mechanisms for resident engagement and interconnectedness before retrofit roll-out, to identify independent sources and arbiters of information on upfront and long-term energy costs, to ensure effective mechanisms for the social control of energy use, and to provide a platform to encourage nascent energy citizenship through which residents link pro-environmental behaviours in the home to broader networks of social action on climate change.

Editorial: Optimization of energy autonomy in buildings with renewable energy sources and battery storage

Editorial: Optimization of energy autonomy in buildings with renewable energy sources and battery storage

Development of a solar powered multirotor micro aerial vehicle

Rotary-wing aerial vehicles offer manoeuvrability and vertical take-off and landing (VTOL) advantages over fixed-wing systems. Rotary-wing systems do however have comparatively higher energy demands and consequently shorter flight times and therefore a greater energy dependence over their fixed-wing counterparts. Advances in photovoltaic technologies have resulted in significant increases in the specific power (power-to-weight-ratio) of solar cells enabling the design of solar-powered rotary-wing aircraft, and now micro-sized variants. The micro aerial vehicle (MAV) presented, the Micro Solarcopter, is a 0.15 m ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 0.15 m ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 0.02 m solar-rechargeable radio-controlled aircraft. The 0.071 kg aircraft can fly for an average time of 3.5 min, recharge in approximately 68 min under 1000 W/m2 irradiance at 25 °C and can hibernate for 38 days without sunlight. The paper explores the use of commercially available photovoltaic cells for the purpose of increasing the energy autonomy of multi-rotor MAVs, by enabling them to stay out in the field without returning to base for charging. A working prototype has been presented which incorporates a battery management system, automatic power on and off, low-power sleep mode, and first-person-view (FPV) camera.

Optimizing Energy Consumption: A Case Study of LVDC Nanogrid Implementation in Tertiary Buildings on La Réunion Island

In the context of an insulated area with a subtropical climate, such as La Réunion island, it is crucial to reduce the energy consumption of buildings and develop local renewable energy sources to achieve energy autonomy. Direct current (DC) nanogrids could facilitate this by reducing the energy conversion steps, especially for solar energy. This article presents the deployment and efficiency evaluation of a 48 VDC low-voltage direct current (LVDC) nanogrid, from conception to real-world installation within a company. The nanogrid consists of a photovoltaic power plant, a lithium–iron–phosphate (LFP) battery, and DC end-use equipment, such as LED lighting and DC fans, for two individual offices. For identical test conditions, which are at an equivalent cabling distance and with the same final power demand, the total power consumed by the installation is measured for several stages from 50 to 400 W, according to a 100% DC configuration or a conventional DC/AC/DC PV configuration incorporating an inverter and AC/DC converter. The methodology used enables a critical view to be taken of the installation, assessing both its efficiency and its limitations. Energy savings of between 23% and 40% are measured in DC for a power limit identified at 150 W for a distance of 25 m. These results show that it is possible to supply 48 VDC in an innovative way to terminal equipment consuming no more than 100 W, such as lighting and air fans, using the IEEE 802.3 bt power over ethernet (PoE) protocol, while at the same time saving energy. The nanogrid hardware and software infrastructure, the methodology employed for efficiency quantification, and the measurement results are described in the paper.

Multi-Power System Electrical Source Fault Review

The phrase “Multi-Power System (MPS)” refers to an application that combines different energy conversion technologies to meet a specific energy need. These integrated power systems are rapidly being lauded as essential for future decarbonized grids to achieve optimum efficiency and cost reduction. The fact that MPSs multiply several sources also multiplies their advantages to be environmentally friendly and increases the possibility of energy autonomy as they do not depend on a single source. Consequently, this increases the reliability and reduces the production costs and the size of the storage system. However, the main disadvantages of such a system are the complexity of its architecture and the difficulty in managing the power level, which leads the system to face many faults and sometimes failure. In this case, a fault-tolerant control (FTC) system can automatically adapt to component malfunctions while maintaining closed-loop system stability to achieve acceptable performance. However, on the way to build efficient FTC, one first needs to study the faults that may occur in the system in order to tolerate them. This review paper presents the faults of the MPS electrical sources used in a hybrid system, including a photovoltaic generator and a diesel generator, plus a lead–acid battery as a storage device. Only the most-encountered faults are treated.

Pv Off Grid System with Improved Charge Controller Using Closed Loop Control

A photovoltaic (PV) off grid system is a cutting-edge energy system that harnesses solar power to provide reliable electricity to localized areas. This abstract focuses on enhancing the performance of PV standalone off grid systems through the implementation of an advanced charge controller employing closed-loop control strategies. These autonomous energy systems, powered by solar panels, offer a decentralized solution to electricity generation and distribution. Traditional charge controllers may not efficiently adapt to varying solar irradiance levels, leading to suboptimal energy harvesting. The closed-loop control system proposed in this work addresses the need for dynamically adjusting the charging algorithm in response to real-time environmental conditions, ensuring maximum energy captured from the PV system. The open circuit voltage algorithm plays a pivotal role in increasing the overall efficiency of the PV micro grid. By responding intelligently to changes in solar irradiance and load requirements, the system minimizes energy losses and maximizes the utilization of available renewable resources, thereby addressing the need for efficient energy management. The results obtained from MATLAB simulation are compared with other methods in terms of maximum power efficiency. The results suggest that the open circuit voltage algorithm is efficient.