Solar Energy Supply Research Articles

Energy allocation and task scheduling in edge devices based on forecast solar energy with meteorological information

Offloading tasks from edge devices to the cloud is an important method to enhance the performance of the edge device. With the help of EH (Energy Harvesting) technology, the edge device can use the collected green energy to support its operations. Most offloading scheduling methods use as much green energy as the edge device collected. Unlike prior research, we consider the long-term benefits of energy. In this paper, we forecast the solar energy supply with meteorological methods which are based on the weather forecast data. Then, we use quadratic programming to allocate energy based on the forecast energy to maximize energy efficiency. Finally, we use NSGA (Non-dominated Sorting Genetic Algorithms) to offload tasks in the edge device. Simulations show that our proposed method not only minimizes the execution time and the energy consumption of clouds, but also enhances the QoE of users.

An irrigation scheduling algorithm for sustainable energy consumption in pressurised irrigation networks supplied by photovoltaic modules

To meet water demands, pressurised irrigation networks often need pumping devices, whose power demand varies with the pump head, the flow rate delivered and the pump efficiency. To satisfy the energy demand of pumps, solar photovoltaic panels can be used as a renewable energy source. Since the electricity supply of a solar photovoltaics plant depends on irradiance, the energy that powers the pump varies with the time of the day. This study presents a strategy for scheduling water delivery by irrigation pumps, synchronising energy production in solar photovoltaic modules and minimising the installation size. An optimisation algorithm is proposed, which changes the energy required by pumping devices and adjusts them to the available solar energy supply, minimising the number of panels required. This problem applies to a pressurised irrigation network, where the utility manager may irrigate crops at all hours of the day. By adopting the proposed algorithm, irrigation will follow a rigid rotation schedule to follow the new irrigation plan. This approach improves earlier studies by employing a least-square scheduling algorithm with little computing time. This results in a tool for managers and decision-makers when evaluating the possibility of converting their irrigation network into a stand-alone system supplied by photovoltaic panels. A case study handling this issue in the University of Alicante’s pressurised irrigation network in Spain is proposed to find potential energy savings by connecting the recommended scheduling irrigating plan to the present operation.Graphical abstract

An Energy Efficient Task Scheduling for a Cloud-edge System

With the widespread popularity of edge computing, the energy consumption of edge devices has attracted lots of research interests. This paper studies the cloud-edge system under the solar energy supply scenario, and optimizes the system parameter configuration according to the energy supply of photovoltaic power generation, to reduce the system energy consumption and prolong the system running time. Specifically, we built an edge video detection system based on Raspberry Pi, and deeply analyzed the energy consumption model of the system. Based on this, the problem of dynamically adjusting the video detection operating parameters is modeled as a long-term optimization problem. In order to solve this problem effectively, the long-term optimization problem is transformed to an instantaneous optimization problem, so that the problem can be solved efficiently in real time, and the rationality of this transformation is proved. Finally, we propose a low-energy-consumption scheduling algorithm to optimize the task scheduling and energy consumption of the system. Through simulation experiments, the performance of the proposed algorithm is evaluated. The results show that the scheduling algorithm can reduce the energy consumption of the system by an average of 18%.

Porous functional materials with excellent solar-thermal and electro-thermal properties for desalination of saline water

Desalination of saline water is a key technology to produce safe drinking water. Here, we report a novel type of reduced graphene oxide (GO) nanosheets modified porous functional materials (rGS) with both excellent solar-thermal and electro-thermal properties for efficient, portable, and continuous desalination of saline water. The rGS porous materials are prepared by modifying porous melamine sponges with GO nanosheets, and then reducing GO nanosheets into reduced GO (rGO) nanosheets. With sufficient rGO nanosheets coated on rGS porous materials, water evaporation fluxes of rGS-5 porous materials are > 1100 g m-2h−1 in solar-thermal desalination under 1000 W m−2 and > 3600 g m-2h−1 in electro-thermal desalination under direct voltage of 20 V due to the excellent solar-thermal property and Joule effect of rGS. The salt rejection values are always higher than 99.95% towards different saline waters including hypersaline water, and the salinities of distilled waters are always far lower than the WHO standard for safe drinking water. The strategy and results in this work provide valuable guidance for designing portable desalination systems to produce safe drinking water by simply using solar energy and/or direct-current power supply in certain applications with special needs such as remote regions and disaster situations.

Use of combined solar energy supply systems integrated in the structure of buildings

At present, installations based on alternative renewable types of energy are being introduced into energy complexes at an accelerated pace around the world. These energy systems do not use fossil fuels and do not produce harmful emissions. However, the low energy potential of such installations, calculated per unit of working surface (for example, for solar installations), and the variability of operation (due to climatic conditions), do not allow them to be fully used. As a result, the replacement of traditional energy with renewable energy is moving at a very slow pace. The present paper proposes the use on a significant scale of large solar power systems designed for a communal or individual consumer in order to provide it with thermal and electrical energy. At the same time, it is supposed to receive both electrical and thermal energy from the same working surface. So, the total coefficient of direct conversion of the solar radiation flux by the thermophotovoltaic systems shown here goes up a lot. In addition, to increase efficiency and save building materials, it is proposed to install such systems instead of building roofs. That is, the proposed solar converters can be integrated into the building structures. The use of such energy systems in traditional buildings makes it possible to obtain thermal and electrical energy from the flow of solar radiation without using additional space and significantly reduces the consumption of traditional energy resources.

Miniaturization of spacecraft electrical power systems with solar-hydrogen power supply system

The concept of solar-hydrogen systems for spacecraft, orbital stations, lunar and Martian bases is currently receiving a new impetus. The supply of solar energy to energy receivers aboard space vehicles is limited. The number of everyday tasks and energy-intensive experiments on board space objects is growing with the development of astronautics. To perform energy-intensive work and experiments, energy consumption exceeds the incoming solar fluxes. The modern solar-hydrogen system ensures the reception, conversion and accumulation of excess incoming energy in the form of chemical energy - hydrogen. Cryogenics makes it possible to miniaturize the solar-hydrogen system. The safety of the cryogenic solar-hydrogen energy system is ensured by hydrogen concentration and leakage sensors.The article proposes a comprehensive solution for miniaturization of Power Conversion Unit (PCU) of Energy Power System (EPS) of spacecrafts (SC), which consists in a joint solution of four key problems of miniaturization of power devices: energy, structural, design and technological, system. Miniaturization of the solar-hydrogen energy system (SHES) is achieved by installing onboard hydrogen and oxygen microcryogenic refrigerators, as well as hydrogen and oxygen cryogenic tanks, water tank, electrolyzer and hydrogen fuel cells (FC). The accumulation of chemical hydrogen energy on board the orbiting spacecraft ensures reliable operation when entering the shadow. Storage of hydrogen in cryogenic form significantly reduces the volume required. A cryocooler based on the Stirling cycle provides the process of liquefying hydrogen after the electrolysis of distilled water. In addition, cryogenic temperatures of 20.2 K can be used to thermostat precision instruments placed on board the spacecraft, For example, to ensure the operation of the SQUID. A 3D - model of a voltage stabilization module (VSM), on the basis of which EEC can be produced with different output power and redundancy depth. We give an example of a complete structural scheme of the EEC, which allows implementing all the fulfillment of all the tasks, assigned to the EEC of the PCU SC.

Optimizing cogeneration and desalination plants by incorporating solar energy

Typically, desalination facilities are integrated with thermal power plants that include steam turbines, simple-cycle gas turbines, and combined-cycle gas turbines. Desalination is accomplished using the following technologies: thermal (multistage flash desalination and multiple-effect evaporation) and membrane (reverse osmosis). Because of the significant economic and environmental impacts of power generation and desalination, there is a critical need to optimize costs and to reduce emissions, especially the carbon footprint. Solar energy is a promising approach to reducing CO2 emissions. The goal of this study is to minimize the total annual cost for desalination facilities powered by thermal power plants, photovoltaic arrays, and battery storage. A single-objective nonlinear optimization approach addresses economic and environmental factors. A multi-period strategy accounts for seasonal variations in energy consumption, water consumption, solar energy supply, fuel prices, and fuel availability. The model is applied to a case study on the water-energy nexus for desalination-power plants in Kuwait. The optimization scheme selects from among various types of fossil fuels: natural gas, gas oil, heavy fuel oil, and crude oil. The study includes optimization with implementation of a carbon tax and constraints on CO2 emission. Over a tax range of $20–120/t CO2, the optimal solutions have a constant capacity of the photovoltaic array. Above $120/t CO2, a sharp increase occurred in the array capacity, and all power was generated by the array.

Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression

Prediction of Total Cloud Cover (TCDC) from numerical weather simulation models, such as Global Forecast System (GFS), can aid renewable energy engineers in monitoring and forecasting solar photovoltaic power generation. A major challenge is the systematic bias in TCDC simulations induced by the errors in the numerical model parameterization stages. Correction of GFS-derived cloud forecasts at multiple time steps can improve energy forecasts in electricity grids to bring better grid stability or certainty in the supply of solar energy. We propose a new kernel ridge regression (KRR) model to reduce bias in TCDC simulations for medium-term prediction at the inter-daily, e.g., 2–8 day-ahead predicted TCDC values. The proposed KRR model is evaluated against multivariate recursive nesting bias correction (MRNBC), a conventional approach and eight machine learning (ML) methods. In terms of the mean absolute error (MAE), the proposed KRR model outperforms MRNBC and ML models at 2–8 day ahead forecasts, with MAE ≈ 20–27%. A notable reduction in the simulated cloud cover mean bias error of 20–50% is achieved against the MRNBC and reference accuracy values generated using proxy-observed and non-corrected GFS-predicted TCDC in the model’s testing phase. The study ascertains that the proposed KRR model can be explored further to operationalize its capabilities, reduce uncertainties in weather simulation models, and its possible consideration for practical use in improving solar monitoring and forecasting systems that utilize cloud cover simulations from numerical weather predictions.

Lacking energy storage, and nuclear contribution, wind, and solar photovoltaic electricity is expensive and scarce

Prices of electricity have skyrocketed phased with the uptake of non-dispatchable wind and solar photovoltaic energy supply, and the closure of combustion fuel plants able to produce electricity on demand. At the same time, blackouts have become more likely, with governments requesting citizens not to use electricity when they need to prevent their occurrence. If we were expecting cheap and abundant renewable energy, it seems something is not right. There are, however, solutions. These are the adoption of other energy sources, not only non-dispatchable wind and solar, but also dispatchable hydroelectric, geothermal, and biomass renewable energy, and baseload nuclear energy, plus the development of energy storage, by batteries, pumped hydro, thermal energy storage, and more than that, by hydrogen, to generate enough dispatchable energy to cover the requirements of a growing world.

Integration of Solar Energy Supply on Smart Distribution Board Based on IoT System

Today’s residential electricity management depends heavily on the Internet of Things (IoT). It is still challenging to create practical, affordable smart condition monitoring, protection, and control systems for residential distribution networks. The performance of the developed system is evaluated for a variety of residential electric loads with different energy consumption patterns. In this paper, a photovoltaic tracking system and also a cleaning system will be connected to a smart board. All input data will be gathered and sent over Bluetooth using a working prototype built on an Arduino board. The mobile application is also used to let individual users monitor the system in real-time, alert users about electrical system issues, display their energy use in real time, and provide other essential alerts and warnings.

Performance assessment of a solar-assisted absorption-compression system for both heating and cooling

Combining renewable energy with building energy supply is an effective way to pivot the building sector to carbon–neutral. This paper proposes a novel solar-assisted energy supply system which is applied in residential buildings for heating, cooling and domestic hot water. The heating/cooling output of the proposed system is mainly contributed by a vapor compression system to address the supply–demand mismatch of solar energy supply system, and the other part is assumed by a solar driven absorption system that is operating with lower generation temperature and higher evaporation temperature to assist the vapor compression system. Therefore, a solar-assisted absorption-compression system (SAACS) exploits the full potential of solar heat for annual energy supply by improving the contribution of per unit solar collection area, with considerable electricity-saving compared to air-source heat pumps. A thermodynamic model is established and validated by the results of the built experimental prototype which is testing. Solar-assisted heating mode and solar-assisted cooling mode are compared in comprehensive evaluation criteria to illustrate the performance differences caused by the assisted solar energy. The results indicate that solar heat at 60 °C is feasible for heating and cooling, revealing the great potential for efficient conversion from solar energy for heating and cooling. Due to the introduction of solar energy, the cooling and heating COPele increases by 10.3 % ∼ 17.6 % and 32.3 % ∼ 56.3 %, respectively. Despite the lower increase in COPele, electricity-saving ratio shows greater value at low hot water temperatures, varying from 24.3 % to 19.6 % for cooling and from 44.1 % to 39.7 % for heating as hot water temperature increases from 60 °C to 85 °C. The maximum SCOP is 0.63 for cooling, and 1.14 for heating. Yearly investigation shows that the SAACS combined with 20 m2 CPC collector has an annual average solar fraction of domestic hot water of 0.85 and a discounted payback period of 3.12 years. These results demonstrate the feasibility and flexibility of the SAACS applied to residential buildings toward decarbonization.

Numerical Study of Heat Transfer Enhancement by Arc-Shaped Fins in a Shell-Tube Thermal Energy Storage Unit

Latent heat thermal energy storage (LHTES) technology can alleviate the mismatch between the supply and demand of solar energy and industrial waste heat, but the low thermal conductivity of phase change materials (PCMs) is an issue that needs to be solved. In this work, the effects of the bifurcated fins on melting and solidification are studied, and local and global entropy generation are discussed. The radial lag time and the circumferential lag time were defined to evaluate thermal penetration and thermal uniformity. Subsequently, a novel arc-shaped fin configuration was proposed to further enhance the heat transfer. The results showed that attaching the bifurcated fins could effectively reduce the global entropy generation. Increasing the trunk fin length was beneficial to enhance the thermal uniformity and promote the melting process, while increasing the branch fin was more effective in the solidification process. Overall, thermal uniformity determined the phase change process. More importantly, the concentric arc-shaped fins significantly reduced the heat transfer hysteresis region, showed better thermal performance than straights fins, and the energy storage and release time were reduced by 52.7% and 51.6%, respectively.

Fat Tails due to Variable Renewables and Insufficient Flexibility: Evidence from Germany

The large-scale integration of renewable energy sources requires flexibility from power markets in the sense that the latter should quickly counterbalance the renewable supply variation driven by weather conditions. Most power markets cannot (yet) provide this flexibility effectively as they suffer from inelastic demand and insufficient flexible storage capacity or flexible conventional suppliers. Research accordingly shows that the volume of renewable energy in the supply system affects the mean and volatility of power prices. We extend this view and show that the level of wind and solar energy supply affects the tails of the electricity price distributions as well and that it does so asymmetrically. The higher the supply from wind and solar energy sources, the fatter the left tail of the price distribution and the thinner the right tail. This implies that one cannot rely on symmetric price distributions for risk management and for valuation of (flexible) power assets. The evidence in this paper suggests that we have to rethink the methods of subsidizing variable renewable supply such that they take into consideration also the flexibility needs of power markets.

Design and assessments on a hybrid pin fin-metal foam structure towards enhancing melting heat transfer: An experimental study

Solar energy, as a kind of renewable energy, offers a large reserve to be harvested at a reasonably low cost for engineering applications. To decouple the temporal and spatial relevance of the continuous energy supply of solar energy, latent heat thermal energy storage can deal with this problem at different temperatures. Aiming to improve energy efficiency, a novel hybrid metal foam-pin fin structure is designed and assessed. Upon conducting measurements on a well-designed experimental bench, the phase change processes of paraffin that is filled in fins, metal foam, and a combination of both (hybrid structure) are evaluated. During the experiments, the transient melting interface is snapshotted and temperature development is documented under five different heat source temperatures of 61 °C, 63 °C, 65 °C, 68 °C, and 70 °C. In the foreground of the novel hybrid structure, each segment of the hybrid is also justified and discussed. Results indicate that the hybrid structure augments marked heat transfer. Compared to pure PCM, complete melting time decreases by 63.4% and simultaneously the temperature response rate increases by 143.9% as implementing the hybrid. Attempts to design hybrid structure find a solution to assess and operate thermal storage applications for solar engineering.

Experimental investigation of a solar-charged sorption thermal battery

In the present study, an integrated solar-driven sorption energy storage unit was investigated under real climatic conditions in Famagusta, North Cyprus. Vermiculite–CaCl2 was selected as the working material due to its high energy density, good cyclic ability and low cost. Three series of charging–discharging experiments were performed employing the developed solar-driven thermochemical heat storage system. The discharging tests were performed during the night for duration of 5 h. During the discharging experiments, temperature and relative humidity of inlet air were between 21 and 24°C and 80% and 90%, respectively. Under these conditions, the average energy output over three cycles was found to be 2.1 kWh, with an average energy storage density of 156 kWh/m3. A manufactured parabolic solar concentrator was utilized to provide the required thermal energy in the charging process. Hence, the average surface temperature of the reactor was in the range of 78°C–83°C. The average solar energy supply and desorption energy utilized in the charging process were 5.56 and 1.75 kWh, respectively. The rate of moisture desorption was 6.5 g/min while the thermo-cyclic efficiency was 38%.

Design, Construction and Performance Evaluation of Ginger Mixed Mode Solar Dryer Integrated with Latent Heat Storage

This study is concerned with the design, simulation, construction and performance evaluation of a ginger solar dryer integrated with latent heat storage. It was done to address the problem of complete non-availability of conserved energy to precede the drying process for some times immediately after the sunshine hours have elapsed; thereby reducing the wide gap between the solar energy demand and supply. The ginger solar dryer was tested to dry 6 kg of sliced ginger rhizomes. The dimensions of the dryer were calculated by design to be as follows: 1.5638 m, 1.6302 m2 and 1.155 m for collector length, collector area and chimney height respectively. An experiment was conducted to blend Aluminium powder with shea butter at elevated mass fraction of (1 – 5) %wt of Aluminium powder. The third level composition (3%/97%) was considered the most appropriate due to its moderate thermal conductivity of 0.053762 W/mK and highest latent heat of fusion - 164.53 KJ/kg. The ginger solar dryer was tested with ginger slices of (3 – 5) mm average thickness from 9:00 am to 11:00 pm of 11th June, 2019. The average drying rate, collector efficiency and drying efficiency for the period were kg/s, 77% and 30% respectively

Cubist Regression, Random Forest and Support Vector Regression for Solar Power Prediction

At a time when the energy transition is inescapable and artificial intelligence is rapidly advancing in all directions, solar renewable energy output forecasting is becoming a popular concept, especially with the availability of large data sets and the critical requirement to forecast these energies, known to have a random nature. Therefore, the main goal of this study is to investigate and exploit artificial intelligence's revolutionary potential for the prediction of the electricity generated by solar photovoltaic panels. The main algorithms that will be studied in this article are cubist regression, random forest and support vector regression. This forecast is beneficial to both providers and consumers, since it will enable for more efficient use of solar renewable energy supplies, which intermittency makes their integration into the existing electrical networks a challenging task.

Industry 4.0 enabling sustainable supply chain development in the renewable energy sector: A multi-criteria intelligent approach

The aim of this paper is to provide a multi-criteria decision-making intelligent approach based on Industry 4.0 and Triple Bottom Line principles for sustainable supply chain development in the renewable energy sector. In particular, the solar photovoltaic energy supply chain is used as a case study, encompassing the entire energy production process, from supply to disposal. An exhaustive literature review is conducted to identify the main criteria affecting social, economic and environmental sustainability in the photovoltaic energy supply chain, and to explore the potential impact of Industry 4.0 on sustainability. Subsequently, three Fuzzy Inference Systems combining quantitative and qualitative data are built to calculate the supply chain's social, economic and environmental sustainability. Experts' opinions are used to identify the impact of Industry 4.0 technologies on the three pillars of sustainability for each supply chain stage. Finally, a novel sustainability index, Sustainability Index 4.0, is formulated to compute the overall sustainability of the photovoltaic energy supply chain in seven countries. The results show the applicability and usefulness of the proposed holistic model in helping policy makers, stakeholders and users to make informed decisions for the development of sustainable renewable energy supply chains, taking into account the impact of Industry 4.0 and digital technologies.

Optimization and comparison of multiple solar energy systems for public sanitation service buildings in Tibet

Qinghai Tibet Plateau, known as ‘Roof of the World’, is the highest and largest plateau on Earth, with an average elevation of 4900 m and spanning nearly two-thirds the size of the European continent. The energy consumption characteristics of public sanitation service buildings in the Qinghai Tibet Plateau are significantly different from traditional public buildings. It has unique advantages that allow these facilities to use the local enriched solar energy resources to meet the energy demand. This study proposes eight potential solar energy system schemes to obtain a suitable solar energy supply system and design an optimization method for public sanitation service buildings. The optimization models aimed at the life cycle cost for each solar energy system are established, and the equipment capacity in the system is optimized and simulated. Firstly, the optimized life cycle cost and equipment capacity of different solar energy system are compared and analyzed. Then, the short-term dynamic operation performance and the system's energy conservation, economic and CO2 emission reduction performance are comprehensively analyzed. Finally, the sensitivities of economic parameters and equipment price to the system optimization results are analyzed. The results indicate that the life cycle cost of the integrated solar hot water and heat storage system is 43% lower than that of the standalone solar hot air heat supply system and the standalone photovoltaic system. An optimized integrated system consisting of photovoltaic, photothermal, thermal storage, and power storage has the best comprehensive performance. The annual energy saving ratio of the integrated system is ∼85%, and the life cycle cost saving rate is about 50%. In addition, the sensitivity analysis shows that the electricity price is the most significant factor for life cycle cost compared to the annual interest and inflation rates. The price of a solar collector and air source heat pump have the most significant impact on the life cycle cost optimization results of a photovoltaic-photothermal-thermal and power storage integrated system.

Optimization of energy balances of a photovoltaic power plant with electrochemical and thermal storage of solar energy

THE PURPOSE. Exploring the possibility of building hybrid power plants to reduce the shortage and cost of energy in Iraq through the combined use of solar electrochemical and thermal batteries.METHODS. Analytical methods in the field of construction of consumer energy supply systems from photovoltaic plants, methods of computer-mathematical modeling.RESULTS.The analysis of daily algorithms for the operation of a solar thermal energy supply system was carried out using the example of a social facility in Iraq using electrochemical and thermoelectric energy storage systems, taking into account the variation in the level of solar radiation, ambient temperature and energy consumption by seasons. An optimal algorithm for the conditions under study is proposed for the operation of the solar energy supply system and its elements. Methods for building an intelligent thermoelectric controller have been defined, which ensure the conversion of the maximum available energy of the PV power plant into thermal energy.CONCLUSION. It turns out that the proposed structure for the construction of photovoltaic power plants with combined storage of electricity is preferable to consumers with large thermal loads, because of the efficiency of direct conversion of electricity from photovoltaic modules to thermal energy is higher than the efficiency of thermal conversion through an intermediate link - an electrochemical battery. The paper proposes the principle of creating intelligent thermoelectric controllers, which ensure the operation of a photovoltaic power plant in maximum power mode.