Optimization and Application of Power Grid Stability Control Based on Photovoltaic Rapid Power Control Technology

The integration of renewable energy sources (RESs) has become more attractive to provide electricity to rural and remote areas, which increases the reliability and sustainability of the electrical system, particularly for areas where electricity extension is difficult. Despite this, the integration of hybrid RESs is accompanied by many problems as a result of the intermittent and unstable nature of RESs. The extant literature has discussed the integration of RESs, but it is not comprehensive enough to clarify all the factors that affect the integration of RESs. In this paper, a comprehensive review is made of the integration of RESs. This review includes various combinations of integrated systems, integration schemes, integration requirements, microgrid communication challenges, as well as artificial intelligence used in the integration. In addition, the review comprehensively presents the potential challenges arising from integrating renewable resources with the grid and the control strategies used. The classifications developed in this review facilitate the integration improvement process. This paper also discusses the various optimization techniques used to reduce the total cost of integrated energy sources. In addition, it examines the use of up-to-date methods to improve the performance of the electrical grid. A case study is conducted to analyze the impact of using artificial intelligence when integrating RESs. The results of the case study prove that the use of artificial intelligence helps to improve the accuracy of operation to provide effective and accurate prediction control of the integrated system. Various optimization techniques are combined with ANN to select the best hybrid model. PSO has the fast convergence rate for reaching to the minimum errors as the Normalized Mean Square Error (NMSE) percentage reaches 1.10% in 3367.50 s.

This paper deals with the Photovoltaic (PV) power generation system ( PVGS) , it is a promising source of energy with great interest in clean and renewable energy sources and an electromechanical active power filter (APF). The rising number of power electronics-based equipment has posed a problem on the quality of electric power supply. Both high power industrial loads and domestic loads cause harmonics in the utility. Power quality problems may arise in the system or may be caused by the consumer itself. The proposed PVGS with APF is able not only to track the maximum power point of the photovoltaic energy but also to dampen harmonic currents from the grid line. To attain these purposes, for the first time in order to increase the output voltage of PV generator this paper presents the design, simulation and implementation of a simple power electronic interface connected PV array using boost converter. The controller extracts maximum power from the solar array. A closed loop scheme employing a PI controller has been modeled to regulate the DC-bus voltage feed the converter, in the second time the paper provides a study to a PV system combined with the function of the active power filter system which permits the cancellation of the most noteworthy harmonics from the utility current. To demonstrate the performance of abovementioned PVGS with APF, a Matlab/Simulink model was established and simulated. Results seem to be very promising.

Energy crises and the growth of the energy demand have increased the interest in utilizing unconventional power sources. Thus, renewable energy sources have become a topic of interest to mitigate rising energy concerns and cope with increased electricity demand. With remarkable merits including cleanness and abundance, photovoltaic (PV) solar energy systems are a key to solving these issues. The employed inverters should effectively utilize the maximum available power from the PV solar system and transfer this power to the utility grid without posing any further limitations. However, the unequal power generation of different PV systems caused by partial shading (PS) and other PV panel degradation factors leads to a reduction in generation capacity. One of the relatively new solutions to mitigate the mismatch concerns between the PV modules and sub-modules is to extract the maximum power of each sub-module individually. The main objective of this paper is to present a comprehensive review of such PV grid-connected inverters topologies associated with sub-module connection and control. It will classify the PV grid-tied inverters in accordance with the level where the maximum power point tracking (MPPT) system is implemented. A special focus has been placed on sub-module microinverters (MI) in terms of circuit topologies, conversion efficiency, and controller design. This paper provides a comprehensive analysis of employing the distributed MPPT (DMPPT) approach to maximize the power generation of PV systems by mitigating the mismatch issues inside the PV module. The circuit topology, PV system configuration, and MPPT algorithms used for applying DMPPT solutions in PV SMs are discussed in detail in this study.

Stochastic flexible transmission operation for coordinated integration of plug-in electric vehicles and renewable energy sources

Optimizing peak shaving operation in hydro-dominated hybrid power systems with limited distributional information on renewable energy uncertainty

The radiation mechanism from the DC side of a photovoltaic (PV) power generation system is investigated at frequencies between 150 kHz and 30 MHz. To determine the source of the outbreak of the common mode noise, the balancing of the PV measurement model, which is composed of a PV panel and a 2-m-long DC cable, is measured by the mixed-mode S-parameter method. Results showthatthe PV model has good balance. Then, a balanced PV simulation model is proposed. To express the common mode noise, the input signal is supplied to only one of the two wires of the PV simulation model. To confirm the validity of the PV simulation model, the current flowing in the DC cable and the magnetic field from the PV simulation model are compared with those of the PV measurement model. A good agreement between the measured and simulation results is obtained. The PV simulation model is valid for evaluating the radiation noise from the DC side of the PV power generation system. Moreover, the effect of the frame wire of the PV power generation system on the radiation noise is evaluated. The radiation noise from the PV power generation system will strengthen or weaken depending on the layout of the frame wire, especially at low frequency. The radiation noise from the PV power generation system with a plurality of PV panels is also investigated. The peak of the frequency spectrum of the radiation noise shifts to lowfrequency when the number of PV panels is increased.

Lately, solar photovoltaic (PV) has received significant interest due to its economic and environmental benefits. As the integration of renewable energy sources (RES) increases into existing power grids, challenges such as the decrease in short circuit ratio (SCR) are introduced. This paper investigates a case study of the Saudi power grid, examining the voltage stability as the grid transitions from traditional power generation to 100% penetration of solar PV gradually. Moreover, the paper explores the relationship between the increase in solar penetration and the potential effects on the short circuit MVA (SCMVA), which could significantly impact the overall SCR of the system. To meet the North American Electric Reliability Corporation (NERC) recommendation of maintaining SCR at a particular level, synchronous condensers (SC)s were integrated into the grid. The effectiveness of utilizing SCs to maintain the system voltage at optimal levels in a fully solar grid is also considered. In addition, this paper covers the weak grid analysis via utilizing the Newton-Raphson load flow method, along with PV and QV curve analyses. The purpose behind that is to determine weak bus locations in need of voltage improvements, and to meet the amount of reactive power to be injected. Finally, the amount of power being delivered by SCs will be added progressively in three scenarios to show the enhancements on SCR more precisely.

Recently the growing demand for electricity has led to the increase of integrating renewable energy sources (RES) into the grid. This has proven to be an advantage for both power systems and environmental impacts. The introduction of RES has proven to be effective in minimizing power outages due to electricity shortage. Subsequently, this technology has been effective in preserving the atmosphere. However, RES integration has challenges which they bring into the power grid. In this paper, we analyzed the effect of connecting the wind turbine into the grid under fault conditions. From the results obtained, connecting RES increases the fault current which in-turn has the potential to increase the damages within the power grid.

A reactive scheduling and control framework for integration of renewable energy sources with a reformer-based fuel cell system and an energy storage device

Together with advancement associated with technologies things have gotten simpler and less complicated for people. Automation is usually the employment of manage devices along with details technologies to scale back the need regarding human being do the job inside creation associated with things along with products and services. Solar photovoltaic (PV) technology is regarded as the famous energy source amongst renewable energy sources which in turn that utilize to relieve usage of fossil fuel. PV energy is usually a lot of abundant energy sources among renewable energy. PV technology is change sunlight energy into electrical energy. The performance of electricity of PV module can be affected by solar irradiance and ambient temperature. When PV technology is process solar irradiance, producing lowered performance of PV modules and increasing temperature of PV module. When the temperature of PV module is reach at or more than 35 °C that detected by LM 35, PIC 18F4550 is switched ON the DC cooling system and vice versa. After switch ON the cooling system, the temperature of PV module is reducing. This controller system is an intelligent system because it will run the cooling system automatically when the temperature of PV module reaches setting level that detected by temperature sensors. The higher efficiency of PV cell, the payback period of the system can be shorted and the lifespan of PV module can also be longer.

In order to effectively improve the operating environment of large-scale power grid and effectively monitor the safety of power grid, this paper analyzes the concept of smart regulation system for large-scale power grid based on big data and artificial intelligence (AI) in the new era environment of smart operation, then analyzes problems existing in the current dispatching system of large-scale power grid in China, as well as the specific needs of smart dispatch system in the design process. And the corresponding smart control system is designed to effectively optimize and improve the operation environment of power grid, and upgrade and improve the core technology of smart dispatching system of power grid.

The current level of electrification necessitates higher standards for electricity supply quality, highlighting the importance of the efficient organization, operation, and management of electricity systems. Addressing these challenges has become more complex with the increased integration of renewable energy sources (RES). This is particularly relevant for distribution power grids, which, due to their structural characteristics, are generally not adapted to accommodate fluctuating energy sources owing to insufficient network automation. This paper presents an approach based on an integral metric to evaluate the readiness of power grids to meet specific electricity supply requirements. The proposed metric is derived from an analysis of electricity supply quality within the context of accelerated RES development and power grid characteristics critical to quality performance. Such a metric is valuable for forming general strategies and solutions for grid development, particularly with respect to RES integration and the intellectualization of power systems. The integral indicator components are expressed as the probability that the operational mode aligns with an 'ideal' mode. This «Ideal» mode is determined using the least-impact principle and corresponds to a substitute network scheme based on the rscheme, thereby reducing subjectivity in assessments and subsequent decision-making.It is demonstrated that this approach to defining the integral indicator of power grid performance quality enables not only an assessment of current grid readiness but also consideration of specific consumer preferences in design decisions. The methodology outlined here details a progression from relative performance evaluations of grid components to cost assessments, ultimately allowing for technical and economic analyses. This approach facilitates targeted planning for measures aimed at improving grid performance quality and the reliability of power supply to consumers.

This paper introduces a Modified Reptile Search Algorithm (MRSA) designed to optimize the operation of distribution networks (DNs) considering the growing integration of renewable energy sources (RESs). The integration of RESs‐based Distributed Generation (DG) systems, such as wind turbines (WTs) and photovoltaics (PVs), presents a complex challenge due to its significant impact on DN operations and planning, particularly considering uncertainties related to solar irradiance, temperature, wind speed, consumption, and energy prices. The primary objective is cost reduction, encompassing electricity acquisition, PV and WTs unit costs, and annual energy losses. The proposed MRSA incorporates two strategies: the fitness‐distance balance method and Levy flight motion, enhancing its searching capabilities beyond standard Reptile Search Algorithm and mitigating local optima issues. The uncertainties in load demand, energy prices, and renewable energy generation are represented through probability density functions and simulated using Monte Carlo methods. Evaluation involves typical bentchmark functions and a real 112‐bus Algerian DN, comparing MRSA's efficacy with other optimization techniques. Results indicate that the proposed DN optimization program with WTs and PVs integration reduces annual costs by 21.43%, from 6.2715E + 06 to 4.9270E + 06 USD, reduce voltage deviations by 21.67%, from 77.1022 to 60.4007 USD, and enhance system stability by 2.59%, from 2.3699E + 03 to 2.4314E + 03 USD, compared with the base case.

This paper presents an adaptive load-frequency control scheme for a grid-connected solar PV system which supplies a load locally. The grid is meant to complement the solar Photo-Voltaic (PV) system ideally, but because of different loading conditions and intermittent nature of the solar PV system grid support becomes necessary. The PV system is integrated to the synchronous generator based grid via power electronic converters which extracts maximum power from solar PV based using Perturb and Observe (P&O) algorithm to get maximum benefit from the PV system. Integration of renewable energy sources tends to reduce the overall inertia of the grid and hence threaten its stability. Also, perturbations on the load side are known to affect the frequency negatively and now with increased penetration of intermittent renewable energy sources, the frequency problem is expected to be aggravated. The proposed frequency control scheme incorporates a Model Reference Adaptive Controller (MRAC) on the grid side to ensure that the grid frequency is restored within a much smaller time post small disturbances on either the load or the generation side. The proposed system is verified using MATLAB-SIMULINK under wide variation in system conditions.

An accurate forecasting method for power generation of the solar photovoltaic (PV) system can help the power systems operator to reduce the risk of unreliability of electricity supply. This paper proposed a radial basis function (RBF) neural network method to forecast the power generation of PV system. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of power generation of a PV system. The good agreements between the realistic values and forecasting values are obtained; the numerical results show that the proposed forecasting method is accurate and reliable.