Grid-connected Renewable Energy Sources Research Articles

Techno-economic utilization of hybrid optimized gravity-supercapacitor energy-storage system for enriching the stability of grid-connected renewable energy sources

Techno-economic utilization of hybrid optimized gravity-supercapacitor energy-storage system for enriching the stability of grid-connected renewable energy sources

A comprehensive study on energy management, sensitivity analysis, and inertia compliance of feed-in tariff in IEEE bus systems with grid-connected renewable energy sources

The need to incorporate renewable energy generators (REGs) into the electrical grid has become increasingly crucial due to the push for a more sustainable environment. This study advocates an innovative strategy for optimizing inertia-integrated generation and transmission expansion planning (GTEP) to implement feed-in tariffs (FiT). The application of the GAMS CPLEX solver to the model, which tested on an IEEE 6/IEEE 16 system, reveals that using FiT results in a 12.1 % drop in system cost ($599 million to $526 million) and a 7.91 % rise in total system inertia. Sensitivity analysis highlights the correlation between increased REG integration and FiT payment reduction at 50 % penetration. The model outperforms soft computing optimization techniques, showcasing rapid convergence and computational efficiency. The proposed model's validated superiority in rapid convergence and computational efficiency is demonstrated by comparing its results with those obtained from other soft computing optimization techniques.

Grid-Connected Renewable Energy Sources: A New Approach for Phase-Locked Loop with DC-Offset Removal

Renewable Energy Sources (RES) are widely used worldwide due to their positive effect on the environment, being sustainable, low cost, and controllable. The power generated from RESs must be configured to interface and perfectly synchronize with the grid by using Power Electronics Converters (PEC). A Phase-Locked Loop (PLL) is one of the most popular synchronization techniques used due to its speed and robustness. A growing issue that results in oscillations in the estimated fundamental grid phase, frequency, and voltage amplitude is the DC-offset in the input of the PLL. This study was developed to eliminate the DC-offset in the single-phase grid synchronization using Delay Signal Cancellation (DSC) and a fixed-length Transfer Delay (TD)-based PLL. Then, the small-signal model, stability analysis, and selection of controller gains were discussed. The proposed PLL was simulated using MATLAB/Simulink. Moreover, to evaluate the proposed method, several scenarios were developed in order to compare it with other powerful PLLs in terms of performance indicators such as settling time, frequency, and phase error. As a result, the proposed PLL has the fastest dynamic response, completely rejects the DC-offset effect, and fully synchronizes with the electrical grid.

RETRACTED: Renewable source uncertainties effects in multi-carrier microgrids based on an intelligent algorithm

High volatility and unpredictable behavior of renewable energy sources provide various challenges in the operation of power systems with maintaining the system's reliability. To solve the challenges of grid-connected renewable energy sources, microgrids (MGs) can play an essential role due to their tuning capability and flexibility. The fast growth of power-to-gas technology causes to support renewable energy integration and transforms the extra renewable generation to combined normal gas at a suitable time. The optimal type, size, and commissioning year of the accessible distributed energy resources through the economic application of nominated resources are evaluated to be applied in the suggested multi-carrier microgrid. This study focuses on the simultaneous operation of multi-carrier MGs and their equipment as an optimization problem. Small-scale energy sources and load demand in MGs are modeled to reduce costs of exchange between the main grid and MGs, as well as the load balance between MGs and load demand. Given that it is difficult to solve the desired problem considering various constraints, the developed meta-heuristic whale optimization algorithm (WOA) is used along with adaptive weighting coefficients and a local search operator. Moreover, this model investigates the unstable behavior of loads, renewables, and electricity prices using the probabilistic load flow method (PLF), considering multiple carriers simultaneously to match the real world. In this paper, MGs with multiple-carriers exchange energy with the upstream grid. The energy exchange between MGs is also considered. The results of simulations performed on the grid consisting of three interconnected multi-carrier MGs confirmed the effectiveness of the suggested model. Obtained numerical results prove the validity of the suggested multi-carrier microgrid expansion planning issue by economic, environmental, and technical points.

Hybrid Data-Model Predictive Control for Enabling Participation of Renewables in Regulating Reserves Service

A long-horizon hybrid data-model predictive direct power control (HD-MPDPC) scheme is proposed. The hybrid control scheme is for grid-side power electronic converters (PEC) in grid-connected renewable energy sources (RES). Computational burden of conventional MPDPC is alleviated by reducing the number of candidate voltage vectors to be examined in the cost function. This is achieved by employing data-driven forecast of RES output power to identify and eliminate the voltage vectors that do not counteract active and reactive power errors appropriately. RES power is forecasted using recurrent neural networks. The method for eliminating voltage vector candidates is inspired from direct power control, where output of active and reactive power hysteresis controllers along with the sector in which grid voltage vector lies are used to determine the switching states of the grid-side PEC. Thanks to reduced computational complexity, the hybrid predictive control scheme dispatches RES power more reliably over long horizons. This in turn enables RES as a regulating reserves service provider in power systems. Hardware-in-the-loop studies of a grid-connected wave energy conversion system verify reduced computational complexity of HD-MPDPC and its effectiveness in controlling RES output power over long horizons.

Optimal economic scheduling of microgrids considering renewable energy sources based on energy hub model using demand response and improved water wave optimization algorithm

Unpredictable nature of renewable energy sources puts power system operators in different conditions in terms of maintaining the system reliability. Microgrids (MGs) can provide an effective solution for the problems of grid-connected renewable energy sources due to their tuning capability and flexibility. In this study, a stochastic optimization strategy was proposed for participating in energy market operations considering demand response (DR). The results indicated the operating cost decreased when the MG implemented DR programs. Also, DR program could shift energy consumption from on- to off-peak hours and flatten the load curve. Therefore, a scheduling model was presented for the operation of energy carriers and reserves considering security constraints of power and natural gas grids in interconnected hubs as well as responsive load participation using the developed water wave optimization (WWO) algorithm. The objective function of this model aimed to minimize the operating cost of sources to supply electrical and thermal loads applied to the proposed MG. WWO is a meta-heuristic algorithm inspired by the behavior of water waves. The waves formed on the sea surface have complex, but interesting, relationships that can be used to solve optimization problems. In this algorithm, each problem solution is encoded as a water wave and undergoes changes in the problem search space based on three behaviors of propagation, refraction, and decay of water waves or problem solutions. The simplicity of the structure of this method, elitism and the ability to escape from local points due to the existence of different search operators and the mutation of generations have led to the use of this method. The results indicated a decline in operating costs through electrical and thermal responsive load participation and thermal energy storage system. Results of the proposed model revealed a correlation between the electricity price and natural gas consumption, indicating multi-carrier energy grids should be examined and optimized simultaneously.

African Vulture Optimization Algorithm-Based PI Controllers for Performance Enhancement of Hybrid Renewable-Energy Systems

An effective maximum power point tracking (MPPT) technique plays a crucial role in improving the efficiency and performance of grid-connected renewable energy sources (RESs). This paper uses the African Vulture Optimization Algorithm (AVOA), a metaheuristic technique inspired by nature, to tune the proportional–integral (PI)-based MPPT controllers for hybrid RESs of solar photovoltaic (PV) and wind systems, as well as the PI controllers in a storage system that are used to smooth the output fluctuations of those RESs in a hybrid system. The performance of the AVOA is compared with that of the widely used the particle swarm optimization (PSO) technique, which is commonly acknowledged as the foundation of swarm intelligence. As a result, this technique is introduced in this study to draw a comparison. It is observed that the proposed algorithm outperformed the PSO algorithm in terms of the tracking speed, robustness, and best convergence to the minimum value. A MATLAB/Simulink model was built, and optimization and simulation for the proposed system were carried out to verify the introduced algorithms. In conclusion, the optimization and simulation results showed that the AVOA is a promising method for solving a variety of engineering problems.

Distributional Deep Reinforcement Learning-Based Emergency Frequency Control

Emergency frequency control is one of the most critical approaches to maintain power system stability after major disturbances. With the increasing number of grid-connected renewable energy sources, existing model-based methods of frequency control are facing up with challenges of computational speed and scalability for large-scale systems. In this paper, the emergency frequency control problem is formulated as a Markov Decision Process and solved through a novel distributional deep reinforcement learning (DRL) method, namely the distributional soft actor critic (DSAC) method. Compared with other reinforcement learning methods that only estimate the mean value, the proposed DSAC model estimates the distribution of value function over returns. This advancement can lead to more insights and knowledge for the agent, with the benefit of a much faster and more stable learning process, and the improved frequency control performance. The simulation results on IEEE 39-bus and IEEE 118-bus systems demonstrate the effectiveness and robustness of proposed models, as well as the advantage compared to other state-of-the-art DRL algorithms.

Hybrid Data-Driven Modeling for an AC/DC Power System Considering Renewable Energy Uncertainty

The development of grid-connected renewable energy sources and the widespread use of power electronic devices have exacerbated the uncertain, time-varying, and non-linear characteristics of power systems, making accurate and real-time model design challenging. Modeling for unmodeled dynamics and random characteristics has inherent disadvantages in power system simulation. Conventional converter valve modeling ignores the high-frequency switching condition. This study aims to provide an effective modeling strategy that can accurately characterize the unmodeled dynamics and uncertainty of AC/DC hybrid interconnection systems with significant grid-connected renewable energy capacity. The model-data hybrid-driven modeling concept based on digital twin (DT) enhances the technique’s effectiveness. It models the proportional-integral control link of a voltage source converter (VSC). The time convolution neural network (TCN) algorithm can describe accurately the high-frequency switching state of the switching device and the operation state of renewable energy units that changes dynamically with weather conditions and other variables. The simulation experiments on a real-world power grid demonstrate the proposed modeling method’s efficiency and the hybrid-driven model’s performance.

Reduced Voltage Stress Asymmetrical Multilevel Inverter With Optimal Components

The article presents a single phase asymmetrical multilevel inverter with a reduced components and low voltage stress which reduces the size and cost of the system. The structure provides a maximum output voltage of 23 levels with asymmetrical DC sources. There exists several reliability issues in lowering the total harmonic distortion (THD) by utilizing higher components in the design of MLI despite of its merits. Achieving reliability and lowering the THD is a challenging task for the researchers. The proposed 23-level MLI has been investigated with various performance parameters like total voltage standing (TSV), cost function (CF), power loss and efficiency analysis. The suggested MLI is compared with the existing topologies in the recent past and found that it has less voltage stress across the switches and cost-effective. The TSV calculations show that the proposed structure is more efficient in reducing the losses and increasing the efficiency. Hence, based on the evaluations and the comparisons made with the other topologies, it is found that the proposed MLI is well suited for the medium power applications such as FACTS, SVC, DSTATCOM and DVR. As the proposed architecture provides the 23 level output voltage values with asymmetrical DC sources, the configuration can be utilized for improving power quality in grid-connected renewable energy sources. The topology provides a less THD value which is under IEEE standards. The proposed architecture has been designed in MATLAB/Simulink and is implemented experimentally in hardware prototype in the laboratory environment.

An Islanding Detection and Prevention Method Based On Path Query of Distribution Network Topology Graph

Due to the continuous expansion of grid-connected renewable energy sources (RESs), the local-based methods of islanding detection are facing new challenges. We propose a communication-based detection method based on topology graph path query that can achieve improved results. This method uses existing communication technology and intelligent electronic devices (IEDs) in distribution networks to construct a distributed islanding information system. The bidirectional breadth first search (B-BFS) algorithm is used to conduct an offline path accessibility query to establish the decision islanding path (DIP) database. Then the method can quickly obtain results of islanding detection from online verification when the state of the line changes. On this basis, according to the topological structure and operation characteristics of the distribution network, we propose to use the Dijkstra algorithm based on closed-loop constraints to query the shortest path and select appropriate tie switch. This can achieve the goal of preventing islands by maintaining connectivity through synchronous switch operations. The proposed method has been verified on testing systems, and the results show that: (1) The distributed islanding information system has outstanding performance in solving islanding problems; (2) The proposed detection method has a convincing real-time performance; (3) The method of islanding prevention can fundamentally avoid the emergence of unplanned islands and their subsequent negative effects.

A Review of Power Conversion Systems and Design Schemes of High-Capacity Battery Energy Storage Systems

Battery energy storage systems (BESSs) are one of the main countermeasures to promote the accommodation and utilization of large-scale grid-connected renewable energy sources. With the rapid increase in the installed capacity of BESSs, the security problem and economic problem of BESSs are gradually exposed. On the one hand, fire accidents happen on occasion; on the other hand, the operation efficiencies and battery utilizations of BESSs are not high, resulting in considerable economic losses. In this paper, the relationship between the construction scheme of a BESS and the power conversion system (PCS) is analyzed. The structures, control methods, and grid-connected/islanding control strategies of PCSs are categorized, evaluated, and compared in detail. And the design schemes of high capacity BESSs as well as relevant considerations are systematically discussed. The test waveforms of a 10-kV BESS based on a cascaded H-bridge high-voltage straight hanging PCS are shown to prove the feasibility of this advanced transformerless BESS scheme. Finally, the future development directions of high-capacity BESSs and PCSs are prospected.

Renewable Energy Based Grid System Using UPQC for PQ Improvement

This paper proposes the grid-connected renewable energy sources (RES) based power quality (PQ) improvement is accomplished using the power compensation device of a unified power quality conditioner (UPQC). In recent days, power quality improvement is essential to the grid system and connected sensitive loads. The photovoltaic (PV) system is utilized to the power provision for the UPQC device through a boost converter which improves the Dc link voltage with pulse width modulation control. The inverters in the UPQC device are controlled using the model predictive controller (MPC), improving the voltage and power compensation. The proposed system results are validated using the MATLAB/Simulink environment.

Impact of installing renewable energy sources on a small-scale power network in the Caribbean

Many small island states in the Caribbean like Antigua and Barbuda depend heavily on petroleum-based products for power generation. Given the fluctuating oil prices, there is now an urgent push for increased energy security. Antigua is one of the fastest-growing islands for grid-connected Renewable Energy Sources (RES). Whilst the increase in grid-connected RES improves the islands’ energy security, and it is equally important to understand the impact that RES have on the network’s reliability and security. Thus, a base case model of the power network was built, and the following areas were analysed: load flow, contingency analysis, and fault analysis. The Antigua Public Utilities Authority (APUA) 69kV power network is used as a case study for this project. PowerWorld and Homer Energy software have been used to simulate and model the grid. Results from the project show that RES changes the power flow and could help to improve the system voltage profile if placed correctly. Whilst increased penetration of Wind Turbine Generators (WTG) on the grid increases the system fault levels, they also play a key role in active and reactive power control. This means that the APUA network must be more flexible, and system operators must have network visibility to react to changes on the network. The aim of this paper is to investigate the impact that RES (in particular, wind and solar PV) has on the operational, security, or reliability of a small-scale power network.

Grid-Connected Renewable Energy Sources

The use of renewable energy sources (RESs) is a need of global society. This editorial, and its associated Special Issue “Grid-Connected Renewable Energy Sources”, offer a compilation of some of the recent advances in the analysis of current power systems composed after the high penetration of distributed generation (DG) with different RESs. The focus is on both new control configurations and novel methodologies for the optimal placement and sizing of DG. The eleven accepted papers certainly provide a good contribution to control deployments and methodologies for the allocation and sizing of DG.

Optimum utilization of grid-connected renewable energy sources using multi-year module in Tunisia

This study aims to raise awareness of renewable energies' importance from an economic and environmental perspective and provide reference data for the investment decision in Tunisia's renewable energy. It focuses on the techno-economic analysis of a grid-connected photovoltaic-wind power system to supply residential load in 26 cities in Tunisia using the multi-year module. Three types of small wind turbines are studied to select suitable wind turbines for each site based on the capacity factor concept. HOMER simulation software is used to design and determine the feasibility of the systems. The optimal configuration is obtained at each site of the country in terms of the lowest net present cost and CO2 emissions using the Wes-tulipo wind turbine. The obtained results show that wind energy is suitable for most cities. It is even more profitable and competitive than photovoltaic (PV) in northern and central Tunisia. In contrast, the PV system has great potential for development in the southern regions of the country. The economic benefit of the renewable energy project for each site is between 11 and 16 years during the 25-years project lifetime, proving its economic attractiveness. Furthermore, this study's sensitivity analysis proves that the PV system becomes competitive if its capital cost is reduced to less than 57% of its current capital cost.

Power flow management of grid connected HRES system using a CFANN technique

ABSTRACT This manuscript presents a hybrid technique-based power flow management of grid-connected Hybrid Renewable energy sources (HRES). HRES has Photovoltaic (PV), Wind Turbine (WT) as well as Diesel Generator (DG). The proposed hybrid technique is the combined implementation of Cuttlefish Algorithm (CFA) and artificial neural network (ANN) and commonly called CFANN technique. Atproposed technique, CFA is used to create the precise control signals for system and builds the control signal database off-line based on power range among source side and load side. Dataset made to operate ANN online and lead the control procedure at less implementation time. The behaviours of system are examined depend on objective function. To analyse power flow management, equality and inequality restrictions are distinct that specifies the renewable energy source availability and power demand. By this appropriate control, HRES can considerably improve the dynamic security of power system. The result shows that the energy sources of renewable energy system and its power converters are controlled and the error is reduced by 92.42%. At that time, proposed model is implemented on MATLAB/Simulink work platform and implementation is evaluated to existing methods.

Zero-sequence current injection based power flow control strategy for grid inverter interfaced renewable energy systems

ABSTRACT This paper deals with an energy management issue for the grid-connected renewable energy sources connected with unbalanced loads. In the grid-connected energy systems, conventional energy management methods are used to manage balanced active power supplied from energy units to grids/loads. However, unbalanced load groups, like single-phase loads, parallel rectifiers, and three-winding transformers tied to the electric networks, cause zero-sequence currents and impair the power stability at the grid-side. For this purpose, in this study, an improved power flow controller method with zero-sequence current injection is proposed in order to compensate zero-sequence currents and ensure phase equilibrium at grid-side. Therefore, it is tested in a photovoltaic/fuel cell-based hybrid energy system with unbalanced loads, including zero-sequence. Instead of the conventional abc/dq frame used in energy management control, the proposed method makes use of triple αβ transforms and implemented in each phase to be controlled separately under designed unbalanced load groups. Hence, it abolishes the weakness of the conventional abc/dq frame method that generates the undesirable mean reference for zero-sequence situations. In addition, the designed system cannot only mitigate the grid-side zero-sequence currents but also supply active powers to three-phase loads/grids. The optimization of energy systems is also provided through a maximum power point tracking algorithm. In the performance testing, the energy generation units are performed under three states, which produce different supplied currents at the output. In the performance section, it is obvious that zero-sequence components at grid-side currents are significantly reduced via the proposed power flow controller-based system. Also, the results are compared to the conventional method in order to verify the validity of the proposed approach under the designed load groups.

Optimal LCL-filter design method for grid-connected renewable energy sources

This paper presents a design method based on the extended harmonic domain modeling for L and LCL passive filters of active-front-end PWM two-level voltage source converters for grid-connected renewable energy sources. The proposed design method is tested under several operating scenarios, such as high and low power levels and switching frequencies. Also, a dedicated graphical user interface (GUI) with five other design methods is provided to ease the evaluation of the proposed design method. The GUI also computes the power quality indexes and the steady-state waveforms for each design methodology. In addition to this, an in-depth overview of filtering technologies and applications is presented to identify the primary practical use of passive filtering and to justify the use of LCL filter in grid-connected systems. The obtained results show that the proposed design method leads to the smallest passive filter parameters, and it is the only method that fulfills all the imposed power quality requirements as well as power specifications.

Direct power control with neutral-point voltage balance of grid-connected three-level NPC inverter

Multi-level power converters are nowadays the most appropriate solution for medium-voltage grid-connected renewable energy sources (RES) such as variable speed wind-turbines and photovoltaic (PV) generators. This paper presents a three-level direct power control (DPC) scheme for a grid-connected NPC inverter with neutral point voltage (NPV) balance. The developed DPC scheme provides the active (P) and reactive (Q) powers control and commonly it preserves the voltages of the two DC-link capacitors at one half of the full DC bus voltage. At each sampling period, the adequate space vector is selected from a predefined switching table designed regarding the effect of the inverter's space vectors on both, P and Q powers, and their ability to achieve the NPV balance. Numerical simulations are carried out, and confirm the effectiveness of the proposed DPC approach in controlling the P and Q powers and minimising the fluctuations of the DC link capacitors voltages.