Renewable Energy Power Plants Research Articles

Solution for Integration of Renewable Energy Power Plants into Smart Grids with Active Power Control

This article addresses the integration of renewable energy power plants into smart grids and active power control. Renewable energy sources contribute to environmentally friendly and sustainable energy production, but the fluctuations inherent in these sources pose a challenge for energy grids. The article examines various technologies that can be used to overcome this challenge and make energy grids more reliable. Smart grids aim to improve energy grids by optimizing energy production, transmission, and distribution using data analytics, automation, and communication technologies. The integration of renewable energy power plants into these smart grids offers significant advantages, including the ability to predict energy production, integrate with energy storage systems, and manage energy demand. The article also emphasizes the importance of active power control. Active power control is used to manage energy production steadily, thereby maintaining grid stability. Balancing energy fluctuations from renewable energy sources and storing excess energy when needed enhances grid stability. In conclusion, this article discusses the crucial role of integrating renewable energy power plants into smart grids and implementing active power control in the energy sector. These integration and control methods are important steps in making energy grids more sustainable, efficient, and reliable.

Renewable energy trading: Assessment by blockchain

Renewable energy trading could be considered the next step in power trading's development. It is probable that individuals currently involved in power trading will need to upgrade their data collection, processing, and reporting systems. This article provides a comprehensive evaluation of renewable energy trading utilizing Blockchain technology. Initially, the paper examines country-specific renewable energy trading with a focus on India, China, the US, France, and Germany's renewable energy policies. Moreover, the paper presents potential renewable energy trading markets such as peer-to-peer, over the grid, and partially or fully independent microgrid's. This paper shows the appraisal of bond, commodity, derivative, and algorithm-based renewable energy trading using different Blockchain methods, including Ethereum and R3 Corda. It is find out during the renewable energy trading, proposers of bid, also include capital cost of the renewable energy power plant, salvage value after useful life of different component of renewable energy power plant. It is also find out proper trading is to be done with offering subsidies of up to 70 % of the capital cost, and with a 30 % viability gap finance (VGF) at this cost.

Research on Multi-Objective Energy Management of Renewable Energy Power Plant with Electrolytic Hydrogen Production

This study focuses on a renewable energy power plant equipped with electrolytic hydrogen production system, aiming to optimize energy management to smooth renewable energy generation fluctuations, participate in peak shaving auxiliary services, and increase the absorption space for renewable energy. A multi-objective energy management model and corresponding algorithms were developed, incorporating considerations of cost, pricing, and the operational constraints of a renewable energy generating unit and electrolytic hydrogen production system. By introducing uncertain programming, the uncertainty issues associated with renewable energy output were successfully addressed and an improved particle swarm optimization algorithm was employed for solving. A simulation system established on the Matlab platform verified the effectiveness of the model and algorithms, demonstrating that this approach can effectively meet the demands of the electricity market while enhancing the utilization rate of renewable energies.

Bi-level configuration and operation collaborative optimization of shared hydrogen energy storage system for a wind farm cluster

Energy storage is indispensable to achieve dispatchable and reliable power generation through renewable sources. As a kind of long-duration energy storage, hydrogen energy storage systems are expected to play a key role in supporting the net zero energy transition. However, the high cost has become an obstacle to hydrogen energy storage systems. The shared hydrogen energy storage (SHES) for multiple renewable energy power plants is an emerging mode to mitigate costs. This study presents a bi-level configuration and operation collaborative optimization model of a SHES, which applies to a wind farm cluster. Different operation modes, including the ‘electricity‑hydrogen-electricity (E-H-E)’ mode and the ‘electricity‑hydrogen (E-H)’ mode, are considered. Results show that SHES system offers substantial advantages over individual hydrogen energy storage solutions. It achieves a notable reduction in annual operation and maintenance (O&M) costs by 9.5 % and a significant increase in annual profit by 10.49 %. Moreover, the SHES system demonstrates a lower wind curtailment rate of 0.24 %, in contrast to the 0.37 % observed in individual cases. SHES will play a more significant role in larger wind farm clusters. The aforementioned advantages of SHES systems become even more pronounced in larger wind farm clusters, where their impact on cost reduction and efficiency is significantly amplified.

Pump-stopping-induced hydraulic oscillations in long-distance district heating system: Modelling and a comprehensive analysis of critical factors

To achieve low-carbon goals, long-distance district heating (LDH) systems are widely applied, which utilize the waste heats from renewable energy power plants and waste incineration plants. The hydraulic oscillations induced by pump-stopping in LDH systems may give rise to critical incidents, such as pipeline ruptures and heating disruptions. The systematic analysis of hydraulic oscillations induced by pump-stopping and the subsequent revelation of critical factors that mitigate their intensity are fundamental prerequisites for ensuring the safety and reliability of LDH system. In this paper, firstly, a pump-stopping hydraulic transient model of the LDH system is established based on the distributed parameter method. Then, combining the method of characteristics (MOC) and the Newton iteration method, the numerical solution scheme for this model is proposed. Finally, taking a 20 km LDH system as an example, the characteristics of hydraulic oscillations induced by pump-stopping is analyzed, and the key factors influencing the intensity of these hydraulic oscillations are investigated. In addition, the differences between hydraulic oscillations induced by pump-stopping and those induced by sudden faults on pipelines are also analyzed. The results indicate that an optimal pump inertia moment value and a properly sized bypass pipe at the pump significantly mitigate hydraulic oscillations, while the influence of constant pressure at the heat source inlet on hydraulic oscillations can be negligible. Our study has important reference value for improving the safe and reliable operation of LDH systems.

Kajian Pemanfaatan Debit pada Saluran Irigasi untuk Pembangkit Listrik Tenaga Mikrohidro (Studi Kasus Saluran Induk Sawito Daerah Irigasi Sadang) Kabupaten Pinrang, Propinsi Sulawesi Selatan

Utilization of water as a new power plant reaches about 6.9% of the existing potential and most of it is built in rivers with very large costs and quite a long time. The demand for electricity is increasing more and more, but the government cannot add power plants from fossil fuels. In fact, they will gradually close all of them and replace them with new renewable energy plants, such as hydropower, solar power, PLTB and other renewable energy power plants. In general, hydroelectric power plants (PLTA) are built on river bodies in the form of weirs or weirs so that they require considerable cost, time and risk and are greatly influenced by fluctuations in discharge, sediment and so on. While there are many irrigation areas that have operated with discharge capacity and fall height that can be utilized for small-scale hydropower, one of them is the Sadang Irrigation Area with an area of ±64,000ha. Using topographic mapping methods, measuring surveys of existing channels, and analyzing the availability of discharge and irrigation water requirements, the research results showed that the height of falls in several irrigation buildings was obtained. By analyzing water availability and demand (water balance), a water supply plan for each existing irrigation canal is obtained. so that the potential power and electrical energy produced is obtained. The Sadang irrigation area is supplied with water from the Benteng weir through two intake buildings. The right intake building supplies the Pekkabata main channel, while the Sawito and Rappang Ha main channels are supplied from the left intake building. The Pekkabata sub-network has a potential power of 338 kW, the Rappang sub-network has a potential power of 158 kW and the Sawito sub-network has a power of 1,939 kW. So the total potential electrical power in the Sadang irrigation network is 2,436 Kw. The potential that has been developed in the Sadang irrigation area for electricity generation is 1,235 kW so there is still a potential of 1,200 kW. Especially in the Sawito main channel, in the building for tapping BSa. 9 has an electrical potential with a power of 492 kW, and annual energy production of 3,511,880 kWh, and the suitable turbine type is the kaplan type.

A current injection method for converter power loss representation in electromagnetic transient simulation

The power-electronics converters are increasingly applied in modern power system, which contains various sub-systems, such as renewable energy power plants and high voltage direct current transmission systems, etc. The electromagnetic transient simulation has been one of the important tools for the study of complex system containing large numbers of power converters. The coordination control of the power converters and corresponding power generation and load units is one of the challenges ensuring stability and obtaining optimal efficiency. However, the detailed modeling of the power converters considering the conduction and switching losses can cost a great number of computation resources, which makes it difficult to simulate a large system. This work proposed a current injection method for converter power loss representation, which can accurately consider the conduction and switching losses of the power-electronics switches with low computation complexity. A look-up table (LUT) of the power loss ratio is calculated before the simulation, and a current source representing the power loss is connected in parallel with the converter to track the reference loss generated by the look-up table. The proposed method can be combined with multiple converter modeling schemes, such as the two-resistance model, the switching-function model, and the average value model, etc. The topologies of the two-level converter and the modular multi-level converter (MMC) were used in the case studies to demonstrate the effectiveness of the proposed method. Compared to the device-level model, the simulation power loss deviation is 0.64% and 4.13% applying the current injection method model in the case studies of the two-level converter and the MMC.

Identification of surface defects on solar PV panels and wind turbine blades using attention based deep learning model

The global generation of renewable energy has rapidly increased, primarily due to the installation of large-scale renewable energy power plants. However, monitoring renewable energy assets in these large plants remains challenging due to environmental factors that could result in reduced power generation, malfunctioning, and degradation of asset life. Therefore, the detection of surface defects on renewable energy assets is crucial for maintaining the performance and efficiency of these plants. This paper proposes an innovative detection framework to achieve an economical surface monitoring system for renewable energy assets. High-resolution images of the assets are captured regularly and inspected to identify surface or structural damages on solar panels and wind turbine blades. Vision transformer (ViT), one of the latest attention-based deep learning (DL) models in computer vision, is proposed in this work to classify surface defects. The ViT model outperforms other DL models, including MobileNet, VGG16, Xception, EfficientNetB7, and ResNet50, achieving high accuracy scores above 97% for both wind and solar plant assets. From the results, our proposed model demonstrates its potential for monitoring and detecting damages in renewable energy assets for efficient and reliable operation of renewable power plants.

Real-Time Solar Power Estimation Through RNN-Based Attention Models

Solar power is an important renewable energy resource that plays a pivotal role in replacing fossil fuel generators and lowering carbon emissions. Since sunlight, which is highly dependent on meteorological factors, is highly volatile, the difficulty in collecting real-time data from renewable energy power plants poses a major threat to maintaining the stability of the entire power system in the target area. A high-performance wireless metering modem is required to monitor the renewable energy generation power of the entire target area in real-time. However, installing such devices on all sites is expensive, so we propose a system that uses deep learning to estimate the generation power of a target site based on the power generations of some sample sites. We use clustering and distance-based sampling to extract a sample site corresponding to each target site and use the recurrent neural network (RNN)-based attention techniques to estimate the generation of target sites from the sample sites. Our experiments show that the proposed RNN-based attention models significantly improve estimation accuracy compared to the baseline model or other deep learning models, irrespective of the number or location of sample sites.

Renewable energy power plants

Renewable energy power plants

Techno-economic Analysis of New Wind Power Plant Development in Southern Sulawesi Electrical Power System

Global warming due to carbon emissions has resulted in climate change, which negatively impacts the lives of living things. On the other hand, electricity demand is increasing every year due to the increasing human population, economic growth and equipment electrification. At the moment, most of the electricity generation in Indonesia uses fossil energy power plants which produce carbon emissions. PT. PLN (Persero) is a State-Owned Enterprise tasked with managing the electricity system in Indonesia. PT. PLN (Persero) through the General Plan for Electricity Supply (RUPTL) for 2021-2030 is targeting the construction of New and Renewable Energy Power Plants. One of possible plan is the Wind Power Plant (WPP) construction in the Southern Sulawesi electrical power system. The use of WPP is expected to reduce carbon emissions. However, the integration of WPP causes other problems in the existing system such as dropped voltage, increased equipment loading, increased short circuit current and decreased stability. So, it is necessary to conduct a study on the effects of integrating WPP into the existing system. Using DIgSILENT Power Factory software, Load Flow, Short Circuit and Transient Stability simulations were carried out. Then an economic analysis was carried out including calculating net present value (NPV), internal rate of return (IRR), profitability index (PI), payback period (PBP) and levelized cost of energy (LCOE. The use of WPP at a certain capacity will not disrupt the stability of the system's power because it is still supported by the fast response generators in the system during variable WPP output. Also voltage drop, equipment loading and short circuit current will not exceed the design value of the system. From financial aspect, with certain assumptions, WPP development can be proven to be economically feasible.

Tungsten oxide nanostructures for all-vanadium redox flow battery: Enhancing the V(II)/(VIII) reaction and inhibiting H2 evolution

Vanadium redox flow batteries (VRFBs) offer remarkable performance capabilities for renewable energy power plants. However, the kinetics of the VRFBs' redox reactions are slow and the efficiency is low due to parasitic reactions such as the hydrogen evolution reaction (HER). In this work, to overcome these limitations, the effect of modifying the carbon cloth electrode with tungsten oxide nanowires, nanoflakes, and nanospheres prepared was elucidated for the negative half-cell reaction V(II)/V(III). The physical and chemical properties of those nanostructures were characterized using FESEM, XPS, XRD, FTIR, and contact angle measurements. The effect of the catalyst loading and structure, pH and composition of the synthesis solution, and the presence of binder on catalytic activity was evaluated using CV and EIS. The results showed that the effective loading of all three structures is ~2 mg/cm2, with all of the structures showing a significant enhancement of the V(II)/(VIII) reaction kinetics in comparison to the untreated carbon cloth and greater stability than the thermally treated carbon cloth. The tungsten oxide nanostructures prepared at pH 2 showed the best catalytic activity, with the suppression of hydrogen evolution reaction (HER) being inversely proportional to the number of defects. Tungsten oxide nanoflakes prepared at pH 2 using water as a solvent exhibited the optimum balance between promoting the V(II)/(VIII) reaction kinetics and suppressing the HER. The performance evaluation in a two-electrodes setup of all‑vanadium RFB revealed that the WNFs structure have the highest charge/discharge capacity and energy efficiency at a relatively high current density of 60 mA/cm2 due to its improved kinetics.

Modelling the operation modes of local MicroGrid networks with mobile wind and solar power plants

The basis for the development of the global energy sector is the introduction of alternative energy and, accordingly, a complete change in approaches to the structural reorganisation of energy systems. An analysis of the state of electric power networks in Ukraine shows their almost complete depreciation, low reliability and structural obsolescence, which makes further development and expansion difficult to ensure the rapid growth of electricity consumption. Therefore, a trendy solution to the problem of modernising electric power networks while increasing their capacity and reliability is the use of MicroGrid systems, which are structural elements of the Smart Grid concept based on the intellectualisation of the management of the full cycle of electricity generation, use and storage. The miniaturisation and localisation of smart electric networks makes it possible to minimise power losses and ensure full control over their operating modes. A MicroGrid provides management of distributed energy resources and is essentially a hybrid, as it includes renewable energy sources alongside traditional ones. Regulation of MicroGrid operation modes and power flows in it is the key to increasing the sustainability of the operation processes. The article proposes the use of mobile wind-solar power plants as sources of distributed generation in the MicroGrid system, which is a new technical solution for improving the structural scheme of its implementation and optimising the management of operating modes. The structure of MicroGrid is substantiated and developed, and mathematical modelling of autonomous and hybrid modes of operation of the system with mobile renewable energy power plants is performed. The obtained results show the feasibility and energy efficiency of the developed MicroGrid system. Conclusions are drawn regarding the prospects for further development of MicroGrid with mobile power plants.

Organisation of the Structure and Functioning of Self-Sufficient Distributed Power Generation

During the operation of solar and wind power plants, it is necessary to solve issues related to the guaranteed capacity of these plants, as well as the frequency stabilisation in the power system where they operate, and maintain an operating mode of self-sufficiency conditions. One of the solutions to these problems is the use of energy storage systems. This article proposes a mathematical model for the study of frequency and power regulation processes in power systems with distributed generation, which includes renewable energy resources and energy storage systems. The novelty of the model lies in the possibility of determining energy cost indicators based on instantaneous energy power data. The model allows us to estimate the conditions under which distributed generation becomes self-sufficient. The results of the model calculations of two variants of power system operation, which includes wind generators with a capacity of 1500 MW, demonstrate the ability of the proposed model to accurately reproduce the dynamics of the frequency stabilisation process. The calculation results of the energy-economic indicators of a real power system combined with a powerful subsystem of wind generation and a battery-type energy storage system prove the competitiveness of self-sufficient renewable energy power plants.

INTEGRATION OF HEATING SYSTEM OPERATION

Ukraine has a huge asset in the form of existing district heating (DH) networks and demand for related services. DH is transforming the European energy sector, attracting efficient, local and renewable energy resources where this was not possible. However, due to the old material base of spare parts, insufficient level of investment and low level of management, Ukrainian DH systems are ineffective and do not meet the needs of consumers. The experience of European Union member states in central Europe shows that deep and sustained reforms can address the current challenges of the heating sector, including improving energy efficiency and economic competitiveness, strengthening environmental sustainability and enhancing energy security. The DH sector in Ukraine has not yet undergone the structural reform that other sectors of the economy have already gone through: over the past 30 years, the quality of services has decreased; subsidies have increased; the old material base is falling apart; The question arises whether it is worth continuing to support DH. As a result, Ukraine's DH sector is in dire straits, with financial, operational and technical problems compounding each other. Comprehensive and well-planned efforts must be made to create the conditions for exiting this state. Such structural reforms are essential to attracting the investment needed to improve the quality, efficiency and long-term potential of the district heating sector.
 The article examines the possibility of using modern technological solutions to modernize heat supply systems in order to improve their efficiency, which can lead to improved district heating services, transparency and financial stability.
 Keywords: energy resources, renewable energy sources, fossil fuels, automated heat and power plant, electricity, hot water, hot air, heating, private households, electric water heater, geothermal heat pump, wind power generator, low-power boiler house.

Analysis of the dynamic evolution process of the digital transformation of renewable energy enterprises based on the cooperative and evolutionary game model

Based on the cooperative-evolutionary game model, this paper studies the dynamic evolution process of the digital transformation strategy selection of renewable energy power plants and renewable energy selling enterprises under government supervision. Renewable energy power plants, renewable energy selling enterprises, and the government are taken as the game players. The Shapley value based on the cooperation game distributes the cooperation benefits brought about by the digital transformation of enterprises and analyses the dynamic evolution process of the strategy of the three-party game players based on evolutionary game theory. Then, based on the system dynamics model, Anylogic and Vensim software are used to simulate the cooperative evolutionary game model, and a sensitivity analysis of the key factors affecting the system stability is carried out. The results show that the "digital transformation" of renewable-energy power plants and renewable-energy selling enterprises will bring about cooperation benefits and promote their joint promotion of digital transformation. Government incentives can accelerate the digital transformation of renewable energy companies. The increase in economic, environmental, and social benefits brought about by the digital transformation of renewable energy enterprises promotes the speed of the digital transformation of renewable energy power plants and renewable energy selling enterprises.

Analysis of the joint trading of local green power certificates, carbon emissions rights, and electricity considering demand flexibility

Establishing synergy among distinct yet associated markets through market orientation is crucial because it can facilitate a clean and low-carbon energy transition. However, researchers have not yet developed a quantitative analytical dynamic model for studying market participants in the context of the joint electricity-carbon-green power certificates market. Moreover, the solution algorithm merits further exploration. This article proposes an analytical method for evaluating the joint trading of local green power certificates, carbon emission rights, and electricity, while taking into account the demand flexibility. First, a framework for the joint trading of local green power certificates, carbon emission rights, and electricity is designed. Second, market participants, such as traditional thermal power plants, renewable energy power plants, and load aggregators, are modelled via system dynamics theory. On this basis, a deep distributed reinforcement learning algorithm is applied to solve the problem. Finally, the effectiveness of the proposed theoretical approach is verified through real-life simulations, and the sensitivity of the key factors influencing joint trading is also analysed.

Does the change in incentive policies promote renewable energy power generation in China?

ABSTRACT To reduce the financial burden brought by the feed-in tariff (FIT) policy, China is shifting its renewable energy support policy to the renewable portfolio standard with tradable green certificates (RPS/TGC). Moreover, the two policies are being implemented in parallel in the transitional period. In this context, this study investigates the game between renewable energy power plants (REPPs) regarding electricity outputs and tradable green certificate (TGC) prices under different renewable energy support policies practiced in China. We focus on analyzing the impact of policy changes on the competing REPPs’ decisions and the renewable electricity market with TGCs. The results show that implementing the RPS/TGC policy inhibits the development of renewable electricity unless the subscription of TGCs is promoted. Government subsidy arrears significantly affect electricity outputs and TGC subscriptions. The low subscription rate of TGCs is caused not by the subsidy-based TGC pricing mechanism but by government subsidies. This suggests that the government should implement the RPS/TGC policy, and demand-side power consumption responsibility weights should also be strengthened to promote TGC subscriptions.

Optimal design of standalone hybrid solar-wind energy systems for hydrogen-refueling station Case study

The optimization of renewable energy power plants (REPPs) to provide electricity and hydrogen for charging Electric Vehicles (EVs) and Fuel Cells Vehicles (FCVs) permits to achieve the sustainability goals in the near future. Indeed, REEPs, EVs, and FCVs have zero greenhouses gas emission. The optimization of the REPPs according to renewable energy sources potential and load requirements, results in costs minimization and increase in the REPPs efficiency. In this context, this paper presents the optimization and the analysis of four standalone REPPs providing electricity required for charging EVS and producing green hydrogen for charging FCVs. The analyzed REPPs consist of wind turbines, photovoltaic panels, power converters, fuel cell, electrolyzers, and hydrogen tanks. The obtained results of each technical solution are analyzed apart and compared with other results to identify the system having the lowest Net Present Cost (NPC), and the lowest levelized electricity and hydrogen costs. The renewable energy potential shows a wind average speed, and average solar radiation of 5 m/s and 6 kWh/m2/day, respectively. The optimization results show that the PV-battery system has a lowest NPC of 11 M€. The PV-wind fuel cell system has the highest NPC due to the high price of wind turbines and fuel cells. The minimum and maximum levelized cost of hydrogen are 4.78 €/kg and 5.55 €/kg, respectively. The optimized configuration produces around 11,756,589 kWh/year of electricity and 177,607 kg of green hydrogen. The total required capacity is 6 MWp PV system with 1800 kWh of battery for the storage of electricity.

Automating Quality Control of Irradiance Data with a Comprehensive Analysis for Southern Africa

A review of quality control for large irradiance datasets is applied as a case study for the Southern African Universities Radiometric Network (SAURAN) database. The quality control procedure is automated and applied to 24 stations from the database with a total of 848,189 hourly datapoints. From this, the individual station’s data quality is also analysed. The assessment validates the automated methodology without the need for a user-based review of the data. The SAURAN database can play a significant role in advancing solar and wind energy; however, the number of offline stations hinders this process. Data scarcity remains an obstacle to these goals, and therefore, recommendations are provided to address this. Recommendations regarding each site’s usability in time-series and discrete applications are made, which provides an overall indication of the SAURAN database’s irradiance measurement quality. Of the 24 measuring stations assessed, eight are recommended, 11 are recommended with cautious use, and five are recommended with extremely cautious use. These recommendations are based on multiple factors, such as whether a dataset has more than one full year of data or is missing minimal datapoints. Further, a study of the irradiance correlation between the stations was conducted. The results indicated groupings of different stations that showed highly correlated irradiance measurements and similar weather patterns. This is useful if a proposed renewable energy power plant, such as PV, falls within a cluster where the data from the SAURAN database can be used as a substitute if no data is available. SAURAN presents an opportunity for Southern Africa to increase its research outputs in solar and wind energy and lessen its dependency on fossil fuel-based energy production.