Frequency regulation in a hybrid renewable power grid: an effective strategy utilizing load frequency control and redox flow batteries

Renewable energy sources (RESs) have become integral components of power grids, yet their integration presents challenges such as system inertia losses and mismatches between load demand and generation capacity. These issues jeopardize grid stability. To address this, an effective approach is proposed, combining enhanced load frequency control (LFC) (i.e., fuzzy PID- TI λ D μ ) with controlled energy storage systems, specifically controlled redox flow batteries (CRFBs), to mitigate uncertainties arising from RES integration. The optimization of this strategy's parameters is achieved using the crayfish optimization algorithm (COA), known for its global optimization capabilities and balance between exploration and exploitation. Performance evaluation against conventional controllers (PID, FO-PID, FO-(PD-PI)) confirms the superiority of the proposed approach in LFC. Extensive testing under various load disturbances, high renewables penetration, and communication delays ensures its effectiveness in minimizing disruptions. Validation using a standardized IEEE 39-bus system further demonstrates its efficiency in power networks grappling with significant renewables penetration. In summary, this integrated strategy presents a robust solution for modern power systems adapting to increasing renewable energy utilization.

Load frequency stabilization of distinct hybrid conventional and renewable power systems incorporated with electrical vehicles and capacitive energy storage

Maintaining a power balance between generation and demand is generally acknowledged as being essential to maintaining a system frequency within reasonable bounds. This is especially important for linked renewable-based hybrid power systems (HPS), where disruptions are more likely to occur. This paper suggests a prominent modified "Fractional order-proportional-integral with double derivative (FOPIDD2) controller" as an innovative HPS controller in order to navigate these obstacles. The recommended control approach has been validated in power systems including wind, reheat thermal, solar, and hydro generating, as well as capacitive energy storage and electric vehicle. The improved controller's performance is evaluated by comparing it to regular FOPID, PID, and PIDD2 controllers. Furthermore, the gains of the newly structured FOPIDD2 controller are optimized using a newly intended algorithm terms as squid game optimizer (SGO). The controller's performance is compared to benchmarks such as the grey wolf optimizer (GWO) and jellyfish search optimization. By comparing performance characteristics such as maximum frequency undershoot/overshoot, and steadying time, the SGO-FOPIDD2 controller outperforms the other techniques. The suggested SGO optimized FOPIDD2 controller was analyzed and validated for its ability to withstand the influence of power system parameter uncertainties under various loading scenarios and situations. Without any complicated design, the results show that the new controller can work steadily and regulate frequency with an appropriate controller coefficient.

Generalized global solar radiation forecasting model via cyber-secure deep federated learning

Recently, the increasing prevalence of solar energy in power and energy systems around the world has dramatically increased the importance of accurately predicting solar irradiance. However, the lack of access to data in many regions and the privacy concerns that can arise when collecting and transmitting data from distributed points to a central server pose challenges to current predictive techniques. This study proposes a global solar radiation forecasting approach based on federated learning (FL) and convolutional neural network (CNN). In addition to maintaining input data privacy, the proposed procedure can also be used as a global supermodel. In this paper, data related to eight regions of Iran with different climatic features are considered as CNN input for network training in each client. To test the effectiveness of the global supermodel, data related to three new regions of Iran named Abadeh, Jarqavieh, and Arak are used. It can be seen that the global forecasting supermodel was able to forecast solar radiation for Abadeh, Jarqavieh, and Arak regions with 95%, 92%, and 90% accuracy coefficients, respectively. Finally, in a comparative scenario, various conventional machine learning and deep learning models are employed to forecast solar radiation in each of the study regions. The results of the above approaches are compared and evaluated with the results of the proposed FL-based method. The results show that, since no training data were available from regions of Abadeh, Jarqavieh, and Arak, the conventional methods were not able to forecast solar radiation in these regions. This evaluation confirms the high ability of the presented FL approach to make acceptable predictions while preserving privacy and eliminating model reliance on training data.

High-resolution dynamical downscaling experiment outputs data over Reunion and Mauritius islands in the South-West Indian Ocean

The present article describes a dataset encompassing model outputs generated by the Weather Research and Forecasting (WRF) regional climate model. A high-resolution (1km) downscaling simulation was performed over two tropical islands, Reunion and Mauritius, situated in the South-West Indian Ocean (SWIO), with initial and boundary conditions provided by the ERA5 reanalysis with a global resolution of 0.25° × 0.25°. The simulation used three nested domains sequentially configured with spatial resolutions of 9, 3, and 1km, respectively, with a downscaling ratio of 3. The physical configurations of this simulation were determined through previous modeling studies and sensitivity tests. The published simulation data currently covers a period of 10 years, starting from 1991 (with the possibility to be extended to 30 years). Over 60 output variables were selected for publication with open access, including those related to the intermittent energy resources (e.g., surface solar radiation and its direct/diffuse components, wind speed/direction at multiple vertical levels, and precipitation, of interest for the run-off-river hydropower), as well as the widely used climatic/meteorological variables (e.g., temperature, pressure, humidity, etc.) at a temporal resolution varying from a day up to 30 minutes. All the data are available through an open-access data server, where an intelligent algorithm is applied to simplify the download process for data users. For the first time, a long-term, high-resolution climate/meteorological dataset covering Reunion and Mauritius has been simulated and published as open-access data, yielding substantial benefits to studies on climate modeling, weather forecasting, and even those related to climate change in the SWIO region. In particular, this dataset will enable a better understanding of the temporal and spatial characteristics of intermittent climate-related energy resources, consequently facilitating their implementation towards a green and low-carbon future.

Comprehensive environmental and techno-economic feasibility assessment of biomass- solar on grid hybrid power generation system for Burdur Mehmet Akif Ersoy University Istiklal Campus

The worldwide use of clean and environmentally friendly renewable energy sources, has been increasing to prevent global warming and climate change. In this study, a hybrid renewable energy system (HRES) including biomass and solar as the source, has been investigated for Mehmet Akif Ersoy University Istiklal Campus in Burdur, Türkiye. The campus has an animal farm consisting of 300 cattle and 200 sheep. Therefore, manure of the animals will be used as the resource for biomass generation. HOMER software is used to simulate the system and to find the size and the quantity of the equipment according to the meteorological and biomass capacity of the campus. The optimum system is determined by means of net present cost (NPC) and the cost of energy (COE). In the simulation, wind energy is also investigated but since the wind speed is not sufficient to produce energy in the region, it is not considered in the optimum system. The optimum system is determined to be grid connected biomass-solar system with 5000 kW PV panels and a 1500 kW biomass generator assisted by the grid of 3000 kW. Also, the NPC of the system is estimated to be USD 18.800.000 and the COE for the system is calculated as 0,107 USD/kWh. The system also reduces the emissions causing the global warming.

Overview of policy and market dynamics for the deployment of renewable energy sources in Italy: Current status and future prospects

In recent years, the international community has been strongly committed to promoting energy transition due to the various challenges presented by the global energy market. In this context, renewable sources have increasingly assumed a significant role, representing a viable solution to accelerate decarbonization and promote diversification of energy mix. This paper examines Italian energy profile, its status, and future prospects. Policies and incentives on a European and national scale have been analysed to observe the commitment of institutions in promoting energy transition. Policies and incentives on a European and national scale have been analysed to observe the commitment of institutions in promoting energy transition. Projections on future investments (2030) and economic and employment implications have also been provided. The analysis shows that shared investments are essential to achieve climate goals in the short term and that existing plants need to be converted through the use of new, more effective, cost-efficient technologies. Thus, innovation and investments in research and development are key drivers of energy transition, and with proper management, climate change mitigation can be ensured. The analysis provides some useful implications for policymakers who should ensure tax incentives, feed-in tariffs, and clear regulation at the national and regional levels that do not hinder the deployment of renewable energy infrastructure.

Rural electrification using renewable energy resources and its environmental impact assessment

Integrating a group of generation units and loads into a microgrid improves power supply sustainability, decreases greenhouse gas emissions, and lowers generating costs. However, this integration necessitates the development of an improved energy management system. The microgrid distributes electricity among energy resources to optimize either the generating cost or the quantity of greenhouse gas emissions, or both at the same time. The low-cost energy supply requires a precise cost model for each energy component. This article aims to develop the generation cost model that incorporates renewable energy to lower the total operating cost and curb greenhouse gas emissions. The suggested optimization problem deals with the low-cost energy solution for the rural area of India. The proposed system used particle swarm optimization, a global optimization strategy, in the study. Minimum cost and emission scenarios are objective issues while operating with tolerable emissions, and costs are multi-objective of the present study. The outcomes of the scenarios are used to provide viable optimized solutions to multi-objective problems using the optimization technique. Finally, a battery bank's potential to compensate for generation shortages while minimizing emissions is being studied. The study is performed on a microgrid comprising photovoltaic PV, diesel generator, battery, wind turbine, and an Indian rural scenario load profile. The finding suggested that the optimal configuration has a total net cost of operation is $59,195.61. The per-unit cost of energy is 0.20 $/kWh with a saving of [Formula: see text] emission is 5994 kg/year. This modular feasibility analysis demonstrates that utilizing a hybrid energy system to power the planning is cost-effective. This research is anticipated to aid rural communities and other stakeholders in making well-informed decisions throughout the planning stages of similar initiatives.

Recent Progress in Renewable Energy Based-Desalination in the Middle East and North Africa MENA Region

BACKGROUND

The Middle East and North African (MENA) countries are rapidly growing in population with very limited access to freshwater resources. To overcome this challenge, seawater desalination is proposed as an effective solution, as most MENA countries have easy access to saline water. However, desalination processes require massive demand for energy, which is mostly met by fossil fuel-driven power plants. The rapid technological advancements in renewable energy technologies, along with their gradually decreasing cost place renewable energy-driven power plants and processes as a promising alternative to conventional fuel-powered plants.

AIM OF REVIEW

In the current work, renewable energy-powered desalination in the MENA region is investigated. Various desalination technologies and renewable energy resources, particularly those available in MENA are discussed. A detailed discussion of suitable energy storage technologies for incorporation into renewable energy desalination systems is also included.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The progress made in implementing renewable energy into power desalination plants in MENA countries is summarized and analyzed by describing the overall trend and giving recommendations for the potential amalgamation of available renewable energies (REs) and available desalination technologies. Finally, a case study in the MENA region, the Al-khafji solar seawater reverse osmosis (SWRO) desalination plant in the Kingdom of Saudi Arabia KSA, is used to demonstrate the implementation of REs to drive desalination processes.

Nature and climate change effects on economic growth: an LSTM experiment on renewable energy resources

Global energy demand increases overtime, especially in emerging market economies, producing potential negative environmental impacts, particularly on the long term, on nature and climate changes. Promoting renewables is a robust policy action in world energy-based economies. This study examines if an increase in renewables production has a positive effect on the Brazilian economy, partially offsetting the SARS-CoV2 outbreak recession. Using data on Brazilian economy, we test the contribution of renewables on the economy via a ML architecture (through a LSTM model). Empirical findings show that an ever-greater use of renewables may sustain the economic growth recovery, generating a better performing GDP acceleration vs. other energy variables.

Solar exergy evaluation and empirical model establishment; case study: Iran

Iran with 300 sunny days in more than two thirds of its land is among the countries with high potential of solar energy. Nevertheless, to date no research has been conducted on status of solar exergy in Iran. In this study, in order to expand the perception of solar energy quality and to compensate the lack of research on solar radiation exergy in Iran, long term meteorological and solar data of eight capital provinces of Iran with five different climatic conditions are utilized. These properly distributed stations include Urmia, Bushehr, Isfahan, Ilam, Kerman, Mashhad, Zahedan and Zanjan. The monthly average daily solar radiation exergy on a horizontal surface for each station is obtained first, then it is recognized that the ratio of exergy to energy is almost independent of the month, the climatic condition and the geographical location; thus, can be considered 0.87 for the whole Iran. For predicting the solar exergy at every station, five empirical models with linear, quadratic, cubic, exponential and power functional forms, all dependent only on relative sunshine duration, are calibrated. Then, eight statistical indicators are utilized to evaluate the performance of the established models for every capital province. The best models recognized for Urmia, Bushehr, Isfahan, Ilam, Kerman, Mashhad, Zahedan and Zanjan have cubic, power, exponential, exponential, linear, quadratic, power and cubic functional forms, respectively. These models are simple and easy to apply and can be also utilized for other places with similar climatic classification and conditions.

Trade war effects: evidence from sectors of energy and resources in Africa

The US government proposes to impose tariffs on up to $50 billion of Chinese imports leading to significant concerns over the Trade War between the US and China. The article evaluates and examines the market responses of companies in both countries, depending on their direct and indirect exposures to US-China trade. Moreover, this paper fills the gap in literature about deglobalization in Energy and Resources Sectors in Africa. This paper proves the idea that US companies that are more dependent on exports and imports from China have lower stock and bond returns, and, at the same time, higher default risks in the short time aspect. The article found Trade War effects in energy and resources companies in Africa in the last years: on ownership rank, on credit country rank, on default risks and on their profitability. The paper also demonstrates that companies’ indirect exposure to US-China trade through domestic input-output links affects their responses to news on the subject matter. These findings suggest that the state of US-China trade of energy and resources is much more complex than the simplistic view of global trade that was in the beginning of Trade War with China. As a result of the Trade War, the real changes in stock prices of China companies (-0.07%) in energy and resource sectors is less than the same changes in US companies in Africa (-0.32%) in 2019. Also, the probability of default of Chinese companies (average default probability changed in -0.08%) in energy and resource sectors changed less than the same rank of US companies in Africa (average default probability changed by -0.84%).

Reconfigurable solar photovoltaic systems: A review

Even though solar power generation has become an emerging trend in the world, its penetration into the utility grid as a distributed generation source is not a satisfactory measure due to the inherent issues related to solar photovoltaic systems (SPVSs). In addressing these issues, microgrids have been identified as suitable integrating platforms for distributed, clean energy resources such as SPV. Different SPV and microgrid architectures are available for different applications depending on the resource availability and controllability. Reconfigurability is a concept that makes a system adaptable to two or more different environments by effectively utilizing the available resources. The review explains the applications of reconfigurable approaches on solar PV systems such as reconfigurable PV arrays, power conditioning unit (DC/DC converter, DC/AC inverter), microgrid controller and topology of distribution network with relevant studies. An analysis is also presented considering the unique features of reconfigurable systems in comparison to the static systems.

The impact of tourism arrivals, tourism receipts and renewable energy consumption on quality of life: A panel study of Southern African region

Improving wellbeing and livelihoods exemplify the third Sustainable Development Goal. Literature related to the tourism-renewable energy-quality of life nexus is limited and lacks consensus. This study contributes to the debate and examines the influence of international tourism arrival (TA), real international tourism receipts (TR), and renewable energy consumption (REC) on quality of life (QoL) by using a panel of 8 Southern African countries spanning 1995–2017. The results found a significant positive and long-run relationship between TA, TR, and QoL. A significant negative effect was found between REC, trade openness (TO), and QoL while urbanization (Urb) had an insignificant negative impact on QoL. A unidirectional causal relationship was found running from QoL to TR and bidirectional causality between QoL and REC. Feedback causality was found between QoL and Urb and unidirectional causality from QoL to TO. The results imply that tourism is an effective economic tool for improving human development in Southern Africa.

The impact of tourism arrivals, tourism receipts and renewable energy consumption on quality of life: A panel study of Southern African region

Improving wellbeing and livelihoods exemplify the third Sustainable Development Goal. Literature related to the tourism-renewable energy-quality of life nexus is limited and lacks consensus. This study contributes to the debate and examines the influence of international tourism arrival (TA), real international tourism receipts (TR), and renewable energy consumption (REC) on quality of life (QoL) by using a panel of 8 Southern African countries spanning 1995-2017. The results found a significant positive and long-run relationship between TA, TR, and QoL. A significant negative effect was found between REC, trade openness (TO), and QoL while urbanization (Urb) had an insignificant negative impact on QoL. A unidirectional causal relationship was found running from QoL to TR and bidirectional causality between QoL and REC. Feedback causality was found between QoL and Urb and unidirectional causality from QoL to TO. The results imply that tourism is an effective economic tool for improving human development in Southern Africa.

Analysis of factors affecting energy consumption and CO2 emissions in Thailand's road passenger transport

The transport sector is one of the important contributors of increasing energy consumption and CO₂ emissions in Thailand. Due to rapid development of transport infrastructure and technologies, patterns of energy consumption in this sector, as well as emissions, have changed considerably. To understand changes of aggregate energy consumption and CO₂ emissions in this sector, this study employs the decomposition technique of the additive LMDI-I index method to analyze influencing factors in the road passenger transport in Thailand during 2007–2017. Results indicate that major energy consumption and GHG emissions in Thailand's road passenger transport come from sedans, vans, and taxis. The decreasing GHG emissions from fuel share and emission factors revealed the success of biofuel promotion in the road transport. The policy implication on energy efficiency and CO₂ mitigation suggests that Thailand should continue promotion of energy efficiency improvement, public transport, biofuels and electric vehicles.

Sulfonated poly (fluorenyl ether ketone nitrile) membranes used for high temperature PEM fuel cell

A series of sulfonated poly (fluorenyl ether ketone nitrile)s with different equivalent weights (EW) ranging from 681 to 369 g mequiv.⁻¹ were used to assemble a series of single proton exchange membrane fuel cells (PEMFC) in their turns. The mechanical strength and morphology of the copolymer were studied systematically. This paper mainly evaluated and compared their cell performance. The polarization curves showed that the prepared films have good performance at low temperature and high relative humidity. Due to the increase of temperature, dehydration seriously deteriorated the performance of the cell, especially for the membrane with high electron flow and low proton conductivity. However, at 100 °C, the cell performance of the membrane containing 441 g mequiv.^{- 1} was even better than that of Nafion^@117 membrane. It could even be used at 125 °C. In the short life test, the output power density was stable at about 0.24 W•cm⁻² within 24 h. These results show that our membranes were suitable for the applications of PEM fuel cell at high temperature.

Energy optimization of Multiple Stage Evaporator system using Water Cycle Algorithm

Black liquor, a residual stream from the Kraft recovery process of paper mills is an incipient biomass energy resource which finds prospective biofuel-based industrial applications to ensure process self-sufficiency and sustainability. Black liquor is concentrated using Multiple Stage Evaporator, the utmost energy intensive unit, before using it as biofuel. Pertaining to the contemporary global energy scenario, improvement in energy efficiency of Multiple Stage Evaporator becomes indispensable. The present work investigates the non-linear modeling and simulation-based optimization of Heptads' stage based Multiple Stage Evaporator in backward feed flow configuration integrated with various energy saving strategies. A novel metaheuristic approach, Water Cycle Algorithm has been employed to search the optimum estimates of unknown process variables and therefore, the optimum energy efficiency parameters. The optimization results demonstrate the efficiency of Water Cycle Algorithm in screening the most appropriate operating strategy, i.e., hybrid model of all energy saving strategies (steam-split, feed-split and feed-preheating) with optimum energy efficiency i.e. Steam Economy of 7.092 and Steam Consumption of 1.919 kg/s. Moreover, a comparative analysis of the results with previous literature and real-time plant estimates reveal that the hybrid model offers improvement of 52.84% in Steam Economy and reduction in Steam Consumption by 28.13% when compared to the real plant data.

Biodiesel production from palm olein: A sustainable bioresource for Nigeria

Dangerous environmental consequences and market unpredictability of fossil fuels have necessitated the need for sustainable large-scale production of biofuel in Nigeria. Unrefined palm oil (UPO) is a significant product of commercially available oil palm plants in the country. This study experimentally investigates the production of biodiesel from refined, bleached and deodorised (RBD) palm olein extracted from UPO obtained from batch reactors. The transesterification process of the RBD palm olein with methanol and in the presence of potassium hydroxide (KOH) catalyst produced biodiesel with a 62.5% yield, thus confirming its feasibility for mass production. The derived biodiesel has properties equivalent to ASTM D792 standard for biodiesel fuels.

Planning stand-alone electricity generation systems, a multiple objective optimization and fuzzy decision making approach

This paper presents a fuzzy-multiple objective optimization methodology to plan stand-alone electricity generation systems. The optimization process considers three main objectives, namely technology cost, environmental and societal impacts. For each feasible solution of the Pareto set, a system reliability index is evaluated along the lifetime of the project. As a key contribution, the decision making process is carried out by applying a fuzzy satisfaction method (FSM). The FSM accounts simultaneously four key performance indexes (KPI): technical, economic, environmental and social. The novelty of the proposal lies on the inclusion of societal impact (local wealth creation) in the FSM used here to select the more appropriate solution. Previous contributions on FSM only accounts two of four indexes considered in this paper. The methodology was applied in a Colombian case study. The results show the importance of the simultaneous consideration of technical, economic, environmental and social objectives in the evaluation of off-grid energization solutions.

Biomass torrefaction as an emerging technology to aid in energy production

Biomass torrefaction has gained widespread attention due to its benefits as a standalone process to improve biomass properties to be at par or similar to those for coal in electricity generation or as a pretreatment step before pyrolysis and gasification processes. It has also found application in other processes like steel production where it is aiming to replace coal or work alongside coal by co-firing the coal with biomass at certain proportions. There have been a lot of papers on biomass torrefaction review, but this paper tried to look at a different angle to show other aspects of torrefaction and how it links to other technologies as well as the chemistry behind it. Overall, the process has seen a big shift in the technology it utilizes, and the hope is that it will make the process more viable and applicable in future. The focus starts from the raw biomass, how it is analysed and the different analysis that are performed to determine relevant information about biomass properties. There are different reactors that are used but to date there is not a preferred one as they have their pros and cons. However, the focus mostly is the process not which reactor to use as they have all not shown any significant differences. The main product of the process, torrefied biomass determines the efficiency and how it can be applied to other technologies. To date, biomass torrefaction is for co-firing with coal for energy generation and as a pretreatment step for pyrolysis and gasification. Due to varying types of biomass in different countries, the technology has not yet reached its full potential, but the hope is it will with calls for use of renewable sources of energy. Other areas like modelling torrefaction of biomass have not been looked at in this review. However, the paper sets the foundations for such detailed reviews.

Current status and future investment potential in renewable energy in Jordan: An overview

Jordan imports 94% of its oil and gas (fossil fuels) to meet its energy needs, leaving it vulnerable to variations in fuel price. Jordan's demand for energy is growing at a rate of 3% annually. In response, the government set a target of obtaining 10% of its energy needs from renewable energy resources by increasing electricity generation share from the present 1.13 GW–1.8 GW by 2020. The sources of generation include abundant solar, wind, and biomass resources, which also enhance economic growth and reduce pollution. This article analyzed the current energy situation in Jordan and assessed the available renewable energy resources potential for direct investments. The actual contribution of clean energy is still moderate at roughly 7% of total energy demand, despite the efforts placed on the development of alternative energy resources. The national electricity supply and demand are presented, and the government initiatives, financial incentives, and tax exemptions to encourage investments in clean energy are also discussed. The renewable energy policy generates future opportunities for investors with an ambitious $20 billion energy plans as does its strategy to improve energy efficiency. This article will benefit interested clean energy investors and developers and plans for 2,000 MW investments in wind and solar energy are ready for bidders. Such an endeavor and model will also benefit neighboring countries in the region.

A study of expected lifetime of XLPE insulation cables working at elevated temperatures by applying accelerated thermal ageing

Deterioration of cable insulation during its normal operation is a major concern. Usually, electric cables receive less periodic maintenance compared to the other electric components, although they are subjected to several environmental conditions during operation such as high temperature and oxidative atmospheres. In this study, a standardized accelerated thermal ageing technique was used, with the application of the Arrhenius model. This technique is commonly used in accelerated life testing to establish a lifetime-stress relationship and estimate cable lifetime. Two types of Cross-Linked Polyethylene (XLPE) material working at elevated temperatures between 95 and 105 °C were selected for testing. In such accelerated ageing processes, it is required for the insulation to reach a degradation level, which is considered the end of life for the material under evaluation. The end of life criteria (also called endpoint) is defined as a percentage reduction of elongation at break, which is considered in this study to be 50% retention of elongation at break. Thermal ageing was carried out according to the BS 7870-2 standard, while elongation at break was evaluated at several ageing stages. The uncertainty in the measurement was estimated. The short-term data points determined by ageing treatment is represented graphically in the Arrhenius plot. The extrapolation of such data was used to predict the long-term performance and estimate the cable lifetime. The lifetime for XLPE is expected to be between 40 and 60 years at 90 °C rated operating temperature. Experimental findings of this study show an estimated cable lifetime between 7 and 30 years for rated operating temperatures between 95 and 105 °C.

Internet of Things based real-time electric vehicle load forecasting and charging station recommendation

Electric vehicles (EVs) are emerging as a favorable strategy to meet the increasing environmental concerns and energy insufficiency, and this trend is expected to grow in the near future. However, the inadequate charging infrastructure is becoming a major barrier to the wide acceptance of EVs. Deployment of this infrastructure is expected to maximize the adoption of EVs to facilitate users' range anxiety. Therefore, connectivity between the charging stations (CS) is mandatory. Understanding the real-time status of CSs can provide valuable information to users such as availability of charging provisions, reserves and the time to reach the CS. The intent of this paper is to provide a better EV charging system by utilizing the advantages of the Internet of Things (IoT) technology. The IoT paradigm offers the present facilities a real-time interactional view of the physical world by a variety of sensors and broadcasting tools. This research article proposes a real-time server-based forecasting application: i) to provide scheduling management to avoid waiting time; and ii) to provide a real-time CS recommendation for EVs with an economic cost and reduced charging time. In addition, the proposed scheme avoids third-party intervention and protects EV user privacy and complex information exchange between the user and CS. The end users can easily use the CS based on their requirements. This synergetic application is built up through the PHP programming language in the Linux UBUNTU 16.04 LTS operating system, and all relevant information is processed and managed through Cloud Structured Query Language (CSQL) from a Google cloud platform. The effectiveness of this application is also validated through a low-cost test system using LTC 4150, ESP 8266 Wi-Fi module and Arduino.

A sustainable mathematical model for design of net zero energy buildings

Energy is vital recourse for economic development of today's business. The services demanded of residential and commercial buildings require substantial energy use. Energy consumption in this sector has been growing in total, gradually. As a result the high emission of greenhouse gases is released and, hence, the saving energy with better building management have made a major priority of the energy and environment sectors throughout the world. In this direction, to reduce energy consumption and mitigate environmental impacts in buildings, net-zero energy buildings (NZEB) is a very effective solution. As a result, a multi-objective model is developed to identify the best combination of materials and construction options considering their related costs, energy efficiency, and environmental impacts of buildings, simultaneously. This sustainable model is presented to construct a building considering the construction costs and energy consumption of the design options. To design the NZEB, while minimizing costs and carbon emissions, use has been made of a combination of different types of active/heating and cooling systems and renewable equipment through such high-efficiency, effective, and updated technologies as the solar panel. Finally, the case study of a residential building with two scenarios is used to demonstrate the proposed framework. The results show that, for scenarios1 and 2 respectively using insulation thickness such as (wall, roof, and windows) and renewable equipment have the highest sustainable impact in NEBZ's performance.

Dependence of electric power flow on solar radiation power in compact photovoltaic system containing SiC-based inverter with spherical Si solar cells

A photovoltaic power generation system suitable for mobile applications was developed. A SiC integrated converter with the maximum power point tracking circuit provided the smallest photovoltaic inverter in ~200 W level. The SiC-based inverter exhibited a peak direct current (DC)-alternating current (AC) conversion efficiency higher than that of conventional Si inverters. A Li-ion laminated battery was mounted in the same housing as the inverter. The weight of entire system containing spherical Si solar cell panels was well below 6 kg. Continuous operation measurements of this system were carried out using four solar cell modules connected in parallel under irradiation by natural sunlight. The total inverter efficiencies under realistic operation conditions were slightly decreased compared with the DC-AC converter values because of loss by the maximum power point tracking device. Even under unstable weather conditions, the system provided power stability without ripples. The behaviors of the output powers of the solar cell, storage battery, and inverter modules were analyzed as a function of the solar radiation power density. The substantial efficiencies of the solar cell modules were dependent on the weather conditions and were approximately 10% on cloudy days. The present compact photovoltaic power generation system with SiC device and spherical Si solar cells is viable for sub kW-class inverter.

Survey and analysis of the quantitative methods used in electricity research on GCC countries: 1983-2018

This study provides a systematic analysis of research on the electricity sector in Gulf Cooperation Council (GCC) countries in the period 1983–2018. GCC countries have experienced tremendous economic growth in the past few decades. This was accompanied by a corresponding increase in electricity consumption. Therefore, a thorough review is needed to understand the research conducted on the electricity sector in GCC countries. This study reviewed articles published in five well-known energy journals: Applied Energy, Energy, Energy Economics, Energy Policy, and Renewable and Sustainable Energy Reviews. The articles were classified into seven categories based on the analysis tools implemented in the papers: 1. Simulation tools, 2. Scenarios tools, 3. Equilibrium tools, 4. Top-down tools, 5. Bottom-up tools, 6. Operations optimization tools, and 7. Investment optimization tools. This study also provides an overview of the research, including the increase in publications over time, an authorship analysis, a keywords analysis, and an analysis of the length of the publications.

Low-cost web-based Supervisory Control and Data Acquisition system for a microgrid testbed: A case study in design and implementation for academic and research applications

This paper presents the design and implementation of a low-cost Supervisory Control and Data Acquisition system based on a Web interface to be applied to a Hybrid Renewable Energy System (HRES) microgrid. This development will provide a reliable and low-cost control and data acquisition systems for the Renewable Energy Laboratory at Universitat Politècnica de València (LabDER-UPV) in Spain, oriented to the research on microgrid stability and energy generation. The developed low-cost SCADA operates on a microgrid that incorporates a photovoltaic array, a wind turbine, a biomass gasification plant and a battery bank as an energy storage system. Sensors and power meters for electrical parameters, such as voltage, current, frequency, power factor, power generation, and energy consumption, were processed digitally and integrated into Arduino-based devices. A master device on a Raspberry-PI board was set up to send all this information to a local database (DB), and a MySQL Web-DB linked to a Web SCADA interface, programmed in HTML5. The communications protocols include TCP/IP, I2C, SPI, and Serial communication; Arduino-based slave devices communicate with the master Raspberry-PI using NRF24L01 wireless radio frequency transceivers. Finally, a comparison between a standard SCADA against the developed Web-based SCADA system is carried out. The results of the operative tests and the cost comparison of the own-designed developed Web-SCADA system prove its reliability and low-cost, on average an 86% cheaper than a standard brandmark solution, for controlling, monitoring and data logging information, as well as for local and remote operation system when applied to the HRES microgrid testbed.

Environmental and economic analysis of power generation in a thermophilic biogas plant

This paper investigates the environmental and economic performance of the power production from biogas using Life Cycle Assessment, Life Cycle Costing and Cost Benefit Analysis methodologies. The analysis is based on a commercial thermophilic biogas plant located in Spain where is installed a Combined Heat and Power system that produces electricity that is sold to the grid. Power generation has been assumed as the only function of the biogas system, expanding the system boundaries to include the additional function related to the end-of-life management of the biowastes. Thus environmental burdens from the conventional management of residues were calculated separately and subtracted. The base scenario involves using agri-food waste, sewage sludge and pig/cow manure as substrates. This situation is compared against an alternative scenario where the production of synthetic fertilizer is surrogated by the digestate. The results have shown that the most impacting activities in all impacts categories of power production are primarily attributable to the operation and maintenance of the biogas plant except for water resource depletion and climate change. The avoided emissions associated with the conventional management of pig/cow manure more than offset GHG emissions of the biogas system resulting in a negative impact value of -73.9gCO₂eq/kWh in the base case scenario. The normalized results show that local impact categories such as primarily human toxicity, fresh water ecotoxicity and particulate matter are the most significantly affected by the biogas system while global impact categories as climate change and ozone depletion are less severely affected. The operation and maintenance phase is also shown to be the largest contributor after the life cycle cost analysis, followed by the construction and dismantling of the biogas plant and the profitability of the project is primarily related to the income obtained from the management of the biowastes used as substrates.

Event triggered state estimation techniques for power systems with integrated variable energy resources

For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90%. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables.