Operation Of Renewable Energy Sources Research Articles

Design of adaptive protection coordination scheme using SVM for an AC microgrid

Microgrids have gathered a significant amount of attention within the past decade and becoming an essential asset in the energy industry. The ability to integrate sustainable renewable energy generation into the distribution network is one of the main reasons for microgrids' popularity. Besides technical advantages, renewable energy sources integration with the grid poses many technical challenges. Due to randomness in generation and different modes of operation, integrating renewable energy sources into power systems will be challenging. Reliable operation of renewable energy sources integrated microgrids even when faults occur, requires an adaptive protection scheme and relay coordination. In order to tackle those issues, this paper developed an adaptive protection coordination scheme using numerical overcurrent relays and support vector machines with a particle swarm optimization approach. Renewable energy sources based on microgrids use power electronics systems that require relays to operate in milliseconds, and the power system will be safe. particle swarm optimization's program execution time exceeds the primary relays. The machine learning algorithm is faster in computation time. This article proposes a method, particle swarm optimization, to estimate the optimum relay operating time. The machine learning model having a support vector machine is proposed to estimate the relay operating time. The proposed research is developed and tested on an IEEE12BUS and IEEE35BUS system. The support vector machine -based on adaptive protection coordination schemes estimates the operating time of directional overcurrent relays, with a lesser program execution time and a low percentage error rate. The derived result defined that the proposed approach is well-suitable for real-time applications of an AC microgrid system.

Assessment of the reliability of the mathematical model of the 0.4 kV rural electric network in Matlab Simulink on the example of a study of the steady-state mode of a single-phase short circuit

PURPOSE. Currently, modeling is one of the most reliable ways to study normal and emergency modes of operation of electrical networks. In this regard, a mathematical model of the 0.4 kV rural electric network was developed in the MATLAB Simulink program.PURPOSE. Evaluation of the accuracy of the parameters of the operating modes of the 0.4 kV rural electric network obtained by modeling in MATLAB Simulink by estimating the values of the steady-state single-phase short circuit current at different distances from the transformer substation.METHODS. The currents obtained using the 0.4 kV electrical network model developed in MATLAB Simulink were compared with the currents obtained using other calculation methods (according to GOST 28249-93, the simplified phase-zero loop method and the mathematical model «Project RZA»).RESULTS. It was revealed that the discrepancy in the results at individual points was 9-11%. When simulating a steady-state single-phase short circuit in MATLAB Simulink, it was found that the voltage of the damaged phase A decreases to 0 V, while the voltages on the two remaining intact phases increase by 1.4-1.5 times, i.e.E. by a factor of 2 to the values of 335-354 V when short-circuiting at the transformer terminals and to the values of 329-338 V when short-circuiting behind a section of a 0.4 kV power line.CONCLUSIONS. The resulting mathematical model of a 0.4 kV rural electric network in the MATLAB Simulink program can be used to study normal and emergency operating modes, study the modes of joint operation of renewable energy sources with a centralized network, and the processes of switching on backup generation sources.

ОПТИМІЗАЦІЯ ПРОЦЕСІВ РОЗПОДІЛУ ЕЛЕКТРОЕНЕРГІЇ В СИСТЕМІ ЕЛЕКТРОПОСТАЧАННЯ ЕНЕРГЕТИЧНОЇ СПІЛЬНОТИ

The objective of this study is to establish a methodology for the equitable distribution of loads among participants in an en-ergy community consisting of low-power renewable energy sources. This is achieved through the utilization of a modified resource allocation algorithm. The proposed approach effectively considers multiple criteria, limited initial information, and the need for flexible assignment and reprioritization of objectives and constraints. To achieve this, linguistic characteristics are employed. Furthermore, under specific conditions, the list of objective functions can be expanded to capture the diverse interests of actors in the electricity market, such as suppliers and operators. To validate the effectiveness of the proposed methodology, statistical data on the operation of renewable energy sources supplying electricity to consumers within a spe-cific region was utilized. Optimal operating modes for these sources were investigated. The focal point of this research is to develop a tool that ensures the optimal functioning of the network comprising low-power sources. To attain this, optimization criteria encompassing technical, economic, and environmental aspects were employed to derive the optimal operating modes for the renewable energy community. Bibl. 8, fig. 11, tabl. 2. Keywords: renewable energy sources, low power sources, multi-criteria decision-making, energy community, optimization.

Integrated Energy Management System for Microgrid based on Renewable Energy Sources

An effective energy management strategy is crucial to ensure highest system reliability, stability, operation efficiency and cost-effective operation of renewable energy sources based standalone microgrid. This paper presents an efficient energy management system for microgrid incorporated with Photovoltaic system, PMSG based wind turbine and energy storages including battery, fuel cell-Electrolyzer. Implemented hybrid modified invasive weed optimization with perturbed and observed method for PV systems to harvest maximum energy during partial shading condition. A sliding mode controller is implemented for boost converter to work as maximum power point tracker for wind turbine. Three solar plants and three wind farms are considered in this paper to establish 1 MW microgrid. Each wind farm is established with multiple wind turbines and similarly each solar plant having multiple PV modules. Each wind turbine and solar plant has their own inverter to synchronize at point of common coupling (PCC). Effective controllers are proposed to supply quality power at PCC under linear status and nonlinear status of single and three phase loads. Small size battery is considered to work under transient time and electrolyzer-fuel cell set will be working under steady state condition to reduce the cost of the system. TS-Fuzzy based controllers are designed for all the converters and implemented hardware-in-loop on a Real Time Simulator (RTS) by using OPAL RT technology/modules. The results unveiled that the RTS precisely emulate the dynamics of the microgrid with proposed controllers.

A transient stability analysis method for wind power system with thyristor controlled phase shifting transformer based on branch potential energy index

With the growing usage of renewable energy technologies like wind power and photovoltaics, and the increased integration of FACTS (Flexible Alternating Current Transmission System) devices into the power system, the transient characteristics of the evolving power system undergo changes that require appropriate analysis methods. As a new type of FACTS device, TCPST (Thyristor Controlled Phase Shifting Transformer) is introduced to facilitate the superior operation of renewable energy sources by controlling the power flow of access branches. From the perspective of branches, the dynamic characteristics of renewable energy sources and TCPST might be uniformly studied and simply calculated in the transient stability analysis. Therefore, the paper proposes a transient stability analysis method for wind power systems with TCPST based on the branch potential energy index. First, considering the variation characteristics of branch potential energy, this paper employed the stability index to analyze the transient stability of branches and the system by finding vulnerable lines. Then, based on the stability index, the paper investigates the influence of wind turbine removal, the installation and control parameter adjustment of TCPST on the transient stability of wind power systems. The simulation results in PSAT demonstrate that the removal of a proper amount of wind turbine post-fault and the installation of TCPST can improve the transient stability of the wind power system. Furthermore, it can also be improved by reasonably adjusting the TCPST control parameters. All simulation results are verified by the time domain simulation method.

Grid Mode Selection Scheme based on a Novel Fractional Order Proportional Resonant Controller for Hybrid Renewable Energy Resources

The operation of Renewable Energy Sources (RES) on grid-connected and islanded operations is challenging due to the unstable generation of power. This challenge is due to the unregulated power supply. To mitigate this effect, several controllers were proposed, but they rely on smooth transition by controlling the power supply. The studies have not considered the regulation during switching between the grid connections. Hence this article investigates the novel Fractional-Order Proportional Resonant controller (FOPR) for the regulated supply to the grid connections. The controller aimed to achieve faster stabilization even with the intermittent power supply. The modified grid connection changes fetch the data of fault, unregulated supply. The Modified particle swarm optimization (MPSO) will test the data and send the signal for switching based on the available voltage to the switch and the controller. The controller’s stability is evaluated in both simulation and experimentation, and the employed method’s robustness is compared with other fractional order controllers. The experimentation result shows that the proposed controller has improved its performance to 35% with the intelligent-based control design and 81.25% over the Fuzzy fractional order proportional integral derivative (FFOPID) controller.

Hydrogen production using nuclear power plants

In the coming years, the global demand for hydrogen can be expected to grow gradually, with increasing pressure to produce without the use of natural gas or oil. As a result, possible ways to produce hydrogen that will have a lower carbon footprint are being sought. Apart from the use of renewable energy sources, nuclear energy appears to be another possible source. This article provides an overview of available and suitable technologies that use nuclear energy. These include in particular water electrolysis, thermochemical decomposition of water or hybrid cycles. The article also includes an overview of individual research programs in the world. A nuclear power plant, in conjunction with hydrogen production, could serve as a backup flexible energy source in addition to coal and gas power plants to stabilize fluctuations in the electrical transmission system due to the operation of renewable energy sources.

Mitigation of power oscillations for energy harvesting capability improvement of grid-connected renewable energy systems

The increasing penetration of renewable energy sources in the power system raises several challenges from the power quality and output power fluctuations point of view. However, the output power oscillations and power quality problems caused by the low order harmonic oscillations at the second-order frequency of the utility grid on the dc-link capacitor are emerging as major issues for the efficient operation of power converters. In this manner, a novel method based on modification in the control algorithm to alleviate the output power oscillation and reduce the output current total harmonic distortion is proposed. The proposed control approach seems as a promising solution for the satisfactory grid operation of renewable energy sources regarding not requiring any additional circuit and increment in the capacity of the dc-link capacitor. Moreover, mitigation of oscillations enhances the active power reference tracking capability of the controller that enables the overall efficiency improvement of the system. The performed case studies reveal that the overall efficiency rate of the system is increased by 1.3%. On the other hand, the output current harmonic distortion is decreased below 3% even under low power operating conditions. Also, the complexity level of the control algorithm is quite low for real-time implementation.

Optimal Allocation of Renewable Energy Sources and Battery Storage Systems Considering Energy Management System Optimization Based on Fuzzy Inference

The main problem in planning the optimal operation of renewable energy sources and battery storage systems is the amount of data that must be considered to cover an entire observation period. If the observation period is one year, the characteristic days or averaged data (daily, weekly or monthly averages) are considered to reduce the number of data. Since the average values of the entered data differ from the actual values, it is better to work with hourly or 15-min data at the annual level. The study presents a framework for solving the problem of the optimal allocation and operation of renewable energy sources and battery storage systems. The proposed method simultaneously solves the optimal allocation and energy management problem considering hourly data at the annual level. The fuzzy inference-based system is proposed for scheduling optimal profiles of battery storage systems and renewable energy sources. The developed fuzzy inference system manages the power factors of the photovoltaic and wind power systems, the power factor and output of the biogas plant, and the operating status of the battery storage system. The presented method simultaneously finds the optimal parameters of the energy management system and the optimal allocation and operation of the renewable energy sources and the battery storage system. The developed method is based on the calculation of steady-state power flow. The proposed method is to be used in the design phase for the installation of various renewable energy sources and battery storage systems. In addition, the method is intended to be used to optimally control the power output of energy sources and the operation of energy storage systems during steady-state operation in order to operate the distribution network with minimum annual active energy losses. The developed method is applied to the test distribution system IEEE with 37 nodes. The reduction in annual energy losses in the tested distribution system is about 80% compared to the base case without renewable energy sources and battery storage system.

Optimization strategy based on robust model predictive control for RES-CCHP system under multiple uncertainties

The economic operation of renewable energy sources (RES) integrated with a combined cooling, heating, and power system significantly improves energy utilization and reduces environmental crises. However, multiple uncertainties in RES generation and load consumption predictions cause an imbalance between supply and demand, negatively impacting system efficiency and economics. To address this limitation, an integrated uncertainty rolling optimization framework for combining the probability distribution of prediction and uncertainty optimization is established. Under this framework, an optimization strategy based on a robust model predictive control is proposed for handling the multiple uncertainties of source-load. Here, the probability distributions of RES generation and load consumption predictions are determined using the Gaussian process regression method, and a minimum–maximum rolling optimization model is developed. Under the uncertain scenarios of RES generation and load consumption, the optimization model is converted into a tractable form to obtain a robust schedule that minimizes operating costs. The over-conservatism of robust optimization can be mitigated by adjusting the uncertainty budget. Many case studies are further conducted to confirm the effectiveness of the proposed method. Results show that the operating costs decreased by 11.5% compared with the traditional model predictive control strategies in an uncertain scenario.

Advanced turbine generator torsional vibration evaluation method using Kalman filtering

Turbine generator torsional vibration is becoming a major concern in modern power grids with a high level of changeability due to the operation of renewable energy sources. The traditional absence of standard torsional vibration monitoring and a lack of experience with the operation of torsional vibration monitoring systems opens up a wide range of opportunities for the design of torsional vibration monitoring systems and the possibility of their installation in power plants. As the measured signals are adversely affected by noise, proper filtering is essential for capturing the torsional vibration information. The benefits of the designed Kalman filtering method are the computational efficiency and the possibility of tackling two different types of noise: the state noise and the measurement noise. The feasibility of the proposed method is demonstrated by case studies based on practical signals measured on steam turbine generators.

The Influence of Renewable Energy Sources and Electric Energy Storages on Grid Power Balances

In recent decades, increasingly more attention has been paid in our country and abroad to the use of renewable energy sources (RES). However, such factors as nonuniform distribution of RESs over the country territory and stochastic nature of their availability in time impede their wide-scale application. For RESs to be used on a wider scale, relevant regulatory and technical documents stipulating the electric power system designing should be developed, and a number of technical problems should be solved, e.g., those relating to the need of smoothing the electricity generation nonuniformity. In this study, distribution power grids containing RESs (wind and solar power plants) and electric energy storages are considered. The aim of the study is to develop proposals for a procedure of integrating RESs and energy storages into grids. The study results are supposed to be used in developing software and hardware solutions for control of an energy storage and predict the electricity consumption and electricity generation by RESs in power grids. In the study, mathematical modeling (computation experiment) methods were used for development of energy storage and RES models that take into account climatic factors (wind velocity, solar irradiance, and temperature) in certain geographical locations received from open data bases. For studying the grid power balance reliability, the operation of RESs within a generalized distribution grid is considered. The grid contains an equivalent centralized power system source, a distribution network, consumer loads, various types of RESs (wind and solar power plants), and a centralized electric energy storage. The power outputs produced by wind and solar power plants for a day (based on hourly averaged meteorological conditions) and month are analyzed for a number of regions in Russia; the annual amount of electricity generated by them is estimated, and the effect of smoothing the generation schedules due to combination of various types of RES and use of electric energy storages is evaluated. Universal models of RESs and electric energy storages for electric grid load flow analysis are suggested; the application of the developed models for power balance analysis of grids containing RESs and energy storages is illustrated; the key stages of introducing RESs and energy storage devices are identified and described, and tasks for which electrical operation modes have to be numerically analyzed are formulated.

Experimental Volumetric Hydrogen Uptake Determination at 77 K of Commercially Available Metal-Organic Framework Materials

Storage is still limiting the implementation of hydrogen as an energy carrier to integrate the intermittent operation of renewable energy sources. Among different solutions to the currently used compressed or liquified hydrogen systems, physical adsorption at cryogenic temperature in porous materials is an attractive alternative due to its fast and reversible operation and the resulting reduction in storage pressure. The feasibility of cryoadsorption for hydrogen storage depends mainly on the performance of the used materials for the specific application, where metal-organic frameworks or MOFs are remarkable candidates. In this work, gravimetric and volumetric hydrogen uptakes at 77 K and up to 100 bar of commercially available MOFs were measured since these materials are made from relatively cheap and accessible building blocks. These materials also show relatively high porous properties and are currently near to large-scale production. The measuring device was calibrated at different room temperatures to calculate an average correction factor and standard deviation so that the correction deviation is included in the measurement error for better comparability with different measurements. The influence of measurement conditions was also studied, concluding that the available adsorbing area of material and the occupied volume of the sample are the most critical factors for a reproducible measurement, apart from the samples’ preparation before measurement. Finally, the actual volumetric storage density of the used powders was calculated by directly measuring their volume in the analysis cell, comparing that value with the maximum volumetric uptake considering the measured density of crystals. From this selection of commercial MOFs, the materials HKUST-1, PCN-250(Fe), MOF-177, and MOF-5 show true potential to fulfill a volumetric requirement of 40 g·L−1 on a material basis for hydrogen storage systems without further packing of the powders.

A biogas‐steam combined cycle for sustainable development of industrial‐scale water‐power hybrid microgrids: design and optimal scheduling

AbstractLack of sufficient pure water resources and energy crises are two important issues in summer, especially for remote communities located in tropical zones. Electricity is used for seawater desalination, and power generation units need freshwater for energy extraction, conversion, transportation, and distribution. The design and operation of renewable energy sources based on water‐energy hybrid grids therefore reduce on‐peak electricity demand, potable water scarcity, and pollutant emissions, significantly. This paper proposes a combined cycle for water and power production and investigates its performance under different ambient air temperatures and various load levels. First, biogas is employed to fuel a gas turbine electricity generation process. Then, its waste heat is utilized in a steam turbine heat‐and‐power extraction cycle. This heating flow is used in a water‐heater air‐cooler desalination process. A non‐linear optimization problem is developed under engineering equation solver (EES) and generalized algebraic modeling system (GAMS) with the aim of finding the near‐optimal operating points of the proposed industrial‐scale co‐generation system, considering its technical constraints and changes of fresh water and power demands during a 24 h operating period. This stand‐alone microgrid is able to produce 2.8 L of drinking water per second and 5.8 MW of electricity for large industrial sectors with a minimum efficiency of 37%. Replacing natural gas with biofuels in the water‐power nexus contributes most to emissions mitigation, peak electrical‐demand reduction, and sustainable water treatment. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd

Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm

Microgrids are new technologies for integrating renewable energies into power systems. Optimal operation of renewable energy sources in standalone micro-grids is an intensive task due to the continuous variation of their output powers and intermittant nature. This work addresses the optimum operation of an independent microgrid considering the demand response program (DRP). An energy management model with two different scenarios has been proposed to minimize the costs of operation and emissions. Interruptible/curtailable loads are considered in DRPs. Besides, due to the growing concern of the developing efficient optimization methods and algorithms in line with the increasing needs of microgrids, the focus of this study is on using the whale meta-heuristic algorithm for operation management of microgrids. The findings indicate that the whale optimization algorithm outperforms the other known algorithms such as imperialist competitive and genetic algorithms, as well as particle swarm optimization. Furthermore, the results show that the use of DRPS has a significant impact on the costs of operation and emissions.

OPTIMAL REGULATION OF LOCAL ENERGY SYSTEM WITH RENEWABLE ENERGY SOURCES

The paper is devoted to solving the balancing problem in local power systems with renewable energy sources. For a power system optimization problem, whose operation depends on random weather factors, a convex parameter optimization or optimal control problem was solved using controlled generation, for each individual realization of a random process as a deterministic function, and then statistical processing of results over a set of random realizations was performed and distribution density functions of the desired target function were constructed, followed by estimation of expected values and their confidence intervals. The process describing current deviations of generated power from mean value is modelled as discrete stray model and has properties of Ornstein-Uhlenbeck process, which allowed varying the duration of unit interval, in particular to select data bases of operating objects with inherent temporal discreteness of their monitoring systems. Random components are investigated and modelled, while the average values are considered to be deterministic and are provided within a predictable schedule using also traditional energy sources (centralised power grid). A mathematical model of the combined operation of renewable energy sources in a system with variable load, electric storage device and auxiliary regulating generator is implemented as a scheme of sequential generation and consumption models and random processes describing the current state of the power system. The operation of the electricity accumulators is dependent on the processes mentioned, but in the full balance, it appears together with generation or load losses, which are cumulative sums of unbalanced power and may have a different distribution from the normal one. However, these processes are internal, relating to the redistribution of energy within a generation system whose capacity is generally described satisfactorily, given the relevant criteria, by a normal law. Under this condition, it is possible to estimate the probability of different circumstances - over- or under-generation, that is, to give a numerical estimate of the reliability of energy supply.

Sustainable Development Policy and Renewable Energy in Poland

(1) Background: This article aims to answer the question of whether the Republic of Poland, by stipulating in the Constitution of 1997 the principle of sustainable development and ecological security, has created favourable conditions for the development of renewable energy. (2) Methods: The research is conducted using descriptive methods and—due to the legal nature of the publication and the crucial role played by the dogmatic method—it consists of the interpretation of legal acts and court decisions. (3) Results: Over the last few years, state authorities have introduced a number of regulatory and legal mechanisms to increase the stability of the operation of renewable energy sources, including the development of biomass or geothermal energy, as well as the development of energy clusters and cooperatives. This article characterises specific solutions and assesses their effectiveness. (4) Conclusions: The state authorities should take further specific actions aimed at achieving the sustainable development of the renewable energy sector in Poland. These actions should be primarily aimed at the use of huge resources of renewable energy sources, saving the consumption of energy resources, reducing the demand for final energy, gradually converting electricity production from coal to renewable energy sources (RES), and moving away from fossil fuels for heat production in favour of RES.

DETERMINATION OF RESS GENERATION USING ARTIFICIAL NEURAL NETWORKS

Paper considers the perspectives and potential of using renewable energy sources to decide the global warming problem. The World trend of increasing electricity generation by photovoltaic power stations according to the International Renewable Energy Agency and the trend of increasing the installed capacity of photovoltaic power stations in Ukraine, which supply the generated capacity at a "green" tariff according to the National Commission for State Regulation of Energy utilities of Ukraine. Opportunities and conditions of using artificial neural networks to defined the power generation of photovoltaic power stations on the example of the power plant "Tsekinivska-2" 4–5 turns are investigated. A platform developed by the European Commission – Photovoltaic Geographical Information System – was used to create a database for the creation and training of artificial neural networks. Regularities of change of meteorological satellite data and their influence on electricity generation of photovoltaic power stations are established. For this purpose, the software complex MATLAB was used, namely the module for the creation of artificial neural networks – Neural Networks Toolbox. The height of the sun is conditionally considered constant and its value is repeated from year to year or has a slight deviation, so it can be used as an indicator of the hour and can be considered known in advance, so determined by empirical formulas and changes only under certain astrophysical laws. Regarding the temperature at 2 m and the wind at 10 m, these meteorological data are known, as they are needed not only for forecasting the operation of renewable energy sources but also in agriculture. Therefore, data related to solar radiation are considered to be the most problematic, as this value is the most difficult to determine. Satellite data may have an error, the installation of weather stations, namely quality pyranometers is a costly procedure, but will help provide a training sample of quality data. To forecast with satisfactory accuracy, it is necessary to collect data for 1 year of operation of the weather station. The nntool and Anfis MATLAB modules were used to predict generation. But the obtained results can be used to assess the effectiveness of the photovoltaic power stations, but they are unsatisfactory for the operational balancing of the system.

Практика внедрения гибридных систем теплоэнергоснабжения в России

The article has examined variants of combined heat supply systems development using solar panels and heat pumps in different climatic zones of Russia. The successful operation of renewable energy sources and heat pumps in Russia still depends on enthusiasts without government support. Rational use of combined and hybrid systems based on renewable sources of energy in these cases might quite possibly lead to more efficient solutions which result in different system`s multiplicative effects.

Optimal scheduling for solar wind and pumped storage systems considering imbalance penalty

ABSTRACT The safe and stable operation of the traditional power system has been tremendously affected by the large-scale integration of various renewable energy sources, which has tendency to deliver variable power. The coordinated operation of renewable energy sources has become a hot topic of research nowadays. Utilizing complementary characteristics of solar, wind, and pumped hydro, this paper presents a mixed-integer problem to find optimal scheduling of hydro plants to enhance the market profit. Considering the market schedule for the day ahead, a mathematical formulation has been developed for the operation of a hybrid system. For this problem, the pumping operation of the pumped storage plant has been done by using grid supply during low market price hours. The overall profit can be increased by using the stored energy when the market price is high. The mismatch in the demand and generation has been curtailed by including a penalty factor in the objective function. The results obtained depict reasonable improvement in terms of economic benefits when the coordinated operation suggested is utilized. The results show that the penalty cost has been reduced by a factor of , and profit earned during solar-wind alone was negative and whereas using the Solar-Wind-PSP system (SWPS) the profit has increased and was found to be approximately of total revenue generated. The overall revenue saw an increase of nearly .