Distributed Generation Units Research Articles

Reduction of medium voltage distribution network losses through the reactive power generation in PV systems

With inevitable increase in numbers of distributed generation units connected within the distribution network (DN), different aspects of their impact on DN operation must be evaluated. This paper deals with the problem of reactive power generation from photovoltaic (PV) systems, connected to the DN, and technical and economic benefits that can be achieved on DN operation with its optimal generation. Detailed consideration of four existing medium voltage DNs with their time-dependent loading and PV generation profiles, allowed the evaluation of annual losses of electric energy, for different scenarios of reactive power generation. Furthermore, the resulting financial savings were assessed as well. Results show that with reactive power generation from installed PV units, meeting the actual needs of the network, losses can be significantly reduced and financial savings achieved.

Compensation of Voltage Harmonics for LCL-filtered Inverters in Islanded Microgrids

In a microgrid (MG), it is possible to have some sensitive loads that require high voltage quality. In this paper, a new technique is proposed for selective compensation of main voltage harmonics in islanded MGs. The proposed technique is capable of adjusting the compensation percentage in proportion with the existing disturbance in the sensitive load bus (SLB) and sharing the compensation workload among DGs in proportion with their nominal power. This compensation, is performed by controlling of the interface inverters of distributed generation (DG) units with LCL filters. Also, to decrease the asymmetry among phase impedances of MG and mitigate the voltage distortion after the output LCL of filters, a novel structure is proposed to generate selective virtual impedance. At fundamental frequency, the proposed structure of the virtual impedance improves the control of the fundamental component. On the ather hand, at main harmonic frequencies, it tries to adaptively improve nonlinear load sharing among DG units and mitigate the voltage distortion after the output LCL filters. Simulation results in MATLAB/SIMULINK environment show the efficiency of the proposed approach in improving load load sharing and decreasing voltage harmonics.

Voltage dip ride-through capability of converter-connected generators

Voltage dips have been proven to be one of themost important aspects of power quality. In order to avoid ma-jor economical damage, grid-connected equipment should be de-signed with a good voltage dip immunity. This holds as well forconverter-connected loads as for converter-connected distributedgeneration (DG) units. This paper presents a control strategy forgrid-connected DG converters yielding an improved voltage dipride-through capability. Due to the implementation of the pro-posed control strategy, shutdown of DG units due to voltage dipsis avoided, resulting in a stronger utility grid. Experimental testson a single-phase full-bridge bidirectional converter are carriedout and validate the aforementioned postulations.

A review of recent control techniques of drooped inverter‐based AC microgrids

AbstractAs the penetration of distributed generation (DG) systems in the grid is increasing, the challenge of combining large numbers of DGs in the power systems has to be carefully clarified and managed. The control strategy and management concept of the interconnected systems should be flexible and reliable to handle the various types of DGs. This can be suitably met by microgrids. This paper introduces the microgrid structure and elements and states the main objectives that should be achieved by the microgrid controllers and each DG controller in both operation modes (grid‐connected and island mode). It also presents the challenges of having multiple DG units in a microgrid in terms of accurate power control/sharing, voltage and frequency regulation, power management between DGs, different renewable energy sources integration and deployment, seamless mode transfer, and the modeling issues. The centralized and decentralized control techniques as potential solutions have been discussed and compared by highlighting the advantages and disadvantages of each. Furthermore, the recent control techniques for drooped alternating current microgrids and the main proposed solutions and contributions in the literature have been exposed to finally overcome the droop control limitations and obtain a flexible and smart distributed power system.

Modelling of clustered distributed generation for economic requirements.

In this paper, economical and technicalconsiderations of distributed generation units (DGU)will be presented in two steps. The first one analyseseconomic side of the distributed generation units. Thecalculation of total cost as well as the specific generationcost will be presented. The last newly defined param-eter allows to compare different distributed generationunits with their own and with traditional thermal powerplants. In the second step, the technical restrictionslike power stability or load flow will be considered. Todo this, the model of a low voltage (LV) network hasbeen created. The network has been divided into clus-ter, where DGU and loads are included. The DGU willbe driven in two operating modes: firstly variable loadaccording to the load curve and secondly with full load.Bringing these two models together the following con-clusion will be drawn. The use of distributed generationunits cannot be considered only from the technical pointof view. The economic view plays also an important role.

Comparative Analysis of DG Units with Shunt Capacitive Banks on the Improvement of Voltage Profiles in Distribution Networks.

Electrical distribution systems’ reliability is a critical parameter for electrical networks and their end-users. Among the different parameters associated with these systems’ reliability, voltage profile is most commonly affected in the electrical network due to different internal and external parameters such as lines and feeders’ impedance, system overloads, and increments on end-users. A poor voltage profile can have adverse impacts on the end user, such as long-term harm to their electric and electronic devices. For both consumers and companies that provide electricity, a low voltage profile thus leads to a loss of power. The Distributed Generation (DG) system is a viable option to improve voltage profiles while conserving the environment by unlocking the usage of any renewable energies following recent technological advancements and environmental concerns. This article proposes an alternative method to enhance voltage profiles in a distribution network (Abuja Electricity Distribution Company, AEDC) by comparing the most effective approach for power losses and voltage profile compensation through DGs and capacitor banks. Detailed simulations are conducted to explain and validate the results with the optimum system voltage improvement and loss reduction. This work has found that the voltage profiles are more enhanced with DG units compared to capacitor banks. The power losses were reduced from the initial value of 1196.4 kW to 762.4 kW with a saved energy of 36.3% with DG-unit as compared to FC with a power loss reduction of 1005.2 kW (energy saved of 16.0%).

Resilient distributed control of islanded microgrids under hybrid attacks

In this paper, a resilient control strategy is proposed to improve the stability of frequency and voltage recovery for the islanded microgrid (MG) under hybrid cyber attacks. To deal with the common false data injection attacks (FDI) and denial of service attacks (DoS) in MGs, the proposed resilient control strategy utilizes the observers to accurately estimate the potential FDI signals on both the sensors and actuators of each distributed generation unit (DG) and reconstruct the unavailable states in the system to enhance the system’s ability actively. The ultimate uniform boundedness (UUB) of the system under hybrid cyber attacks is proved by the Lyapunov stability theory. Finally, an islanded MG system is established in MATLAB/SIMULINK, and multiple scenarios are simulated to verify the effectiveness of the method.

Risk-averse stochastic capacity planning and P2P trading collaborative optimization for multi-energy microgrids considering carbon emission limitations: An asymmetric Nash bargaining approach

The increasing penetration of renewable energy with stochastic characteristics and continuous refinement of carbon emission policies put forward higher requirements for the construction of new power systems. This paper proposes a risk-averse stochastic capacity planning and peer-to-peer (P2P) trading collaborative optimization method for multi-energy microgrids (MEMGs) considering carbon emission limitations. First, a cooperative operation model for MEMGs considering the capacity planning of distributed generation units, uncertainty from renewable energy generations, carbon emission limitations and P2P electricity trading among MEMGs is formulated. Second, a risk-averse stochastic programming method is applied to avoid the potential risk losses caused by randomness and intermittence of renewable energy. Third, an asymmetric Nash bargaining approach is adopted to ensure the fair allocation of benefits and maintain the willingness of individual MEMGs to participate in cooperation. Then, to protect the privacy of individual MEMGs belonging to different stakeholders, the alternating direction method of multipliers is used to solve the two subproblems in a distributed manner. Meanwhile, to further alleviate the computation burdens, a diagonal quadratic approximation method is applied to linearize the quadratic penalty term in the augmented Lagrangian function and realize the parallel solution of all optimization subproblems. Moreover, the influence of different carbon emission targets on the optimal resource combination strategy of the system is investigated by introducing carbon emission factors. Simulations on different models, strategies, and distributed algorithms are conducted to verify the effectiveness and superiority of the proposed method.

An adaptive voltage control compensator for converters in DC microgrids under fault conditions

This paper proposes a voltage compensator for converters in multi-converter DC microgrids (MG), which enhances the DC-MG behavior under fault conditions. Among the four existing categories in the classification of the faults, this paper focuses on those faults that affect voltage generation of converter-based distributed generation units (DGUs). Such faults conceptually occur from the terminal voltage reference to actual voltage generated by DGUs. To compensate the adverse effects of the faults, an adaptive scheme is proposed, which considers the most general case of the faults by using the time-varying multiplicative and additive fault models. The proposed scheme benefits from an integrated structure, which does not require separate fault detection, isolation, and identification blocks. As an advantage of the proposed approach, it is designed independent of the primary and secondary controllers of DGUs, and hence its performance is not affected by using different primary and secondary controllers. The effectiveness of the proposed scheme is verified under various fault conditions and uncertainty in the system parameters. Using the proposed scheme, the results show that the performance of system under the fault condition is similar to that of the normal operation.

Hybrid technique for optimal placement and sizing of distributed generation units considering real and reactive power injection

ABSTRACT Distributed generation resources have played a major role in strengthening the performance of the distribution network (DN). Strategically placing and sizing these resources can relieve the stress on distribution line, fostering a more reliable and sustainable energy supply for a greener tomorrow. The literature outlines various optimization techniques, each with its pros and cons based on the methodology used. Some of these techniques are unable to find out the size and placement of DGs that can supply both active and reactive power, while others have a low rate of convergence and the probability of falling into local optima. This research presents a hybrid technique (AT-GSA) based on an analytical and grid search algorithm that can solve the aforementioned problems. Here the goal is to minimize power losses in the DN while enhancing the DN’s voltage profile and voltage stability index (VSI). IEEE 33-bus and IEEE 69-bus systems are being used to validate the proposed technique. The findings indicate that by injecting real and reactive power, the IEEE 33-bus and IEEE 69-bus systems experienced a reduction in losses of 88.26% and 93.21%, respectively, compared to base losses. The average absolute error (AAE) of the voltages shows a substantial decrease, declining from 0.0561 and 0.0268, respectively, to 0.0062 and 0.0069. The VSI for each DN has also shown a substantial increase in comparison to the reference case.

A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids

To ensure fast dynamics and the stability of multiple distributed generator units (DGUs) in DC microgrids, communication links among the controllers of DGUs are generally adopted. However, those communication channels are vulnerable to cyber-attacks. To alleviate this hassle, a Kalman Filter (KF)-based distributed cyber-attack mitigation strategy, which is highly involved in both primary and secondary control, is proposed in this paper. The KF, as a robust state estimator, is utilized to accurately estimate the authentic terminal voltages and currents of the DGUs. Based on the discrepancies between the estimated and measured parameters of the systems under cyber-attacks, the proposed control can adaptively compensate the attack signals via an adaptive proportional integral (API) controller and a fractional API (FAPI) controller in cyber-attack-mitigation layers. The main advantage of using the proposed control scheme compared to conventional schemes is the fast dynamic response. The simulation results verify this merit by comparing the adopted KF and comparing it with conventional artificial neural networks (ANN), while the experimental results validate that effectiveness of the proposed control and showcase the superiority of the FAPI control in terms of its perfect compensation for different types of cyber-attacks.

Communicationless Overcurrent Relays Coordination for Active Distribution Network Considering Fault Repairing Periods

This paper presents an integrated overcurrent relays coordination approach for an Egyptian electric power distribution system. The protection scheme suits all network topologies, including adding distribution generation units (DGs) and creating new paths during fault repair periods. The optimal types, sizes, and locations of DGs are obtained using HOMER software (Homer Pro 3.10.3) and a genetic algorithm (GA). The obtained values align with minimizing energy costs and environmental pollution. The proposed approach maintains dependability and security under all configurations using a single optimum setting for each relay. The calculations consider probable operating conditions, including DGs and fault repair periods. The enhanced coordination procedure partitions the ring into four parts and divides the process into four paths. The worst condition of two cascaded overcurrent relays from the DGs’ presence viewpoint is generalized for future work. Moreover, a novel concept addresses the issue of insensitivity during fault repair periods. The performance is validated through the simulation of an Egyptian primary distribution network.

Protection system planning in distribution networks with microgrids using a bi-level multi-objective and multi-criteria optimization technique

Microgrids are able to improve several features of power systems, such as energy efficiencies, operating costs and environmental impacts. Nevertheless, microgrids’ protection must work congruently with power distribution protection to safely take all advantages. This research contributes to enable their protection by proposing a bi-level method to simultaneously solve the allocation and coordination problems, where the proposed scheme also includes local protections of distributed energy resources. The uncertainties associated with generation and loads are categorized by the k-means method, as well. The non-dominated sorting genetic algorithm II is employed in the upper-level task to solve the protection and control devices allocation problem with two opposing objectives. In the lower-level task, a genetic algorithm ensures their coordination. Protection devices include reclosers and fuses from the network, and directional relays for the point of common coupling of microgrids, while control devices consist of remote-controlled switches. In contrast to related works, local devices installed at the point of coupling of distributed generation units are considered as well, such as voltage-restrained overcurrent relays and frequency relays. The optimal solution for the decision-maker is achieved by utilizing the compromise programming technique. Results show the importance of solving the allocation and coordination problems simultaneously, achieving up to $25,000 cost savings compared to cases that solve these problems separately. The integrated strategy allows the network operator to select the optimum solution for the protective system and avoid corrective actions afterward. The results also show the viability of the islanding operation depending on the decision maker's criteria.

Distributed Generation Control Using Ripple Signaling and a Multiprotocol Communication Embedded Device

Remotely performing real-time distributed generation control and a demand response is a basic aspect of the grid ancillary services provided by grid operators, both the transmission grid operators (TSOs) and distribution grid operators (DNOs), in order to ensure that voltage, frequency and power loads of the grid remain within safe limits. The stochastic production of electrical power to the grid from the distributed generators (DGs) from renewable energy sources (RES) in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the efforts of the DNOs to keep the grid’s operation within safe limits and prevent cascading blackouts while staying in compliance with the SAIDI and SAIFI indices during repair and maintenance operations. Also taking into consideration the aging of the existing grid infrastructure, and making it more prone to failure year by year, it is yet of great significance for the DNOs to have access to real-time feedback from the grid’s infrastructure—which is fast, has low-cost upgrade interventions, is easily deployed on the field and has a fast response potential—in order to be able to perform real-time grid management (RTGM). In this article, we present the development and deployment of a control system for DG units, with the potential to be installed easily to TSO’s and DNO’s substations, RES plants and consumers (i.e., charging stations of electric vehicles). This system supports a hybrid control mechanism, either via ripple signaling or through a network, with the latter providing real-time communication capabilities. The system can be easily installed on the electric components of the grid and can act as a gateway between the different vendors communication protocols of the installed electrical equipment. More specifically, a commercially available, low-cost board (Raspberry Pi) and a ripple control receiver are installed at the substation of a PV plant. The board communicates in real-time with a remote server (decision center) via a 5G modem and with the PV plants inverters via the Modbus protocol, which acquires energy production data and controls the output power of each inverter, while one of its digital inputs can be triggered by the ripple control receiver. The ripple control receiver receives on-demand signals with the HEDNO, triggering the digital input on the board. When the input is triggered, the board performs a predefined control command (i.e., lower the inverter’s power output to 50%). The board can also receive control commands directly from the remote server. The remote server receives real-time feedback of the acquired inverter data, the control signals from the ripple control receiver and the state and outcome of each performed control command.

Correction: Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks

Correction: Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks

Optimal Allocation and Energy Management of Units in Distribution Networks with Multiple Renewable Energy Sources and Battery Storage Based on Computational Intelligence

The paper deals with an optimization problem in an electricity distribution network with different types of distributed generation and a battery storage system in terms of a smart grid concept. The optimization problem considers two objectives, namely, the annual energy losses and the exchange of energy with the higher-level power grid. The decision variables of the problem are the allocation of the different distributed generation units and the battery storage system, the annual power profiles of the controllable distributed generation and the battery storage system, and the power factor profiles of the controllable and noncontrollable distributed generation. All decision variables are solved simultaneously in a single optimization problem. The variable load shapes of the grid consumers and the profiles of the photovoltaic and wind power systems are considered in the study. All data are observed at the annual level with hourly resolution. The problem solving method uses computational intelligence techniques, namely, metaheuristic optimization methods and artificial neural networks. The study proposes a framework for optimizing the decision variables in the planning phase of distributed generation and battery storage, and for controlling the variable power and power factor profiles based on an artificial neural network in the implementation phase. The optimization problem is solved with a power system simulation program and a metaheuristic optimizer in cosimulation synergy. The three cases of distributed generation and battery storage are considered simultaneously. The proposed method is applied to the test grid operator IEEE with 37 buses, and reductions in annual energy losses and energy exchange are obtained in the ranges 34–86% and 41–99%, respectively.

Islanding Event Detection in Grid-Connected Distributed Generation Systems Using Unscented Kalman Filter

A pressing concern in modern smart grid systems revolves around islanding, leading to unpredictable system parameters and a decline in power quality. In response to this concern, we introduce a novel passive method for identifying islanding in grid-connected distributed generation units. This method utilizes the unscented Kalman filter (UKF) to assess the voltage signal captured at the DG position. The triphase voltage signal observed at the point of common coupling (PCC) is used as the test signal. The UKF extracts and filters the harmonic content of the voltage signal to produce a residual signal, which detects changes in the power system. The estimation of total harmonic distortion (THD) follows, and its fluctuations help discern between islanding and typical events. This suggested approach undergoes assessment through a test system simulated in MATLAB/Simulink across different situations. Outcome findings underscore the efficacy of the suggested approach in distinguishing between islanding and regular occurrences, ensuring enhanced reliability and resilience against incorrect operations by removing the zone of nondetection. In our detailed experiments, we found that the proposed unscented Kalman filter (UKF) technique improved islanding detection accuracy by approximately 90% over traditional methods, under varied conditions. Specifically, the nondetection zone (NDZ) was reduced by 95% when compared to the most commonly used passive methods. Furthermore, in scenarios with high harmonic content and noise, the UKF showcased a 90% improvement in reliability over conventional techniques.

A PSO-TVAC for optimal installation of multiple distributed generations in a radial distribution system

<span>The integration of distributed generations (DGs) into distribution system networks has seen a significant increase owing to the depletion of conventional energy resources and the growing power demand. However, a high penetration of DGs can adversely affect the stability of the distribution networks due to the intermittent nature of their generation capabilities. Hence, it is crucial to design DGs optimally to support grid voltage regulation and improve distribution networks performance. This study utilizes a particle swarm optimization (PSO) with time-varying acceleration coefficients (PSO-TVAC) technique to optimize the location and size of various distributed generation units while minimizing the total active power loss. The initial system power loss was determined using a distribution load flow analysis based on the backward-forward technique. The PSO-TVAC algorithm was then employed to identify the optimal placement and sizing of DGs within the standard IEEE 33-bus radial distribution network. To assess the proposed algorithm's effectiveness, photovoltaic (PV) and wind turbine (WT) were considered as the DGs. In comparison with other algorithms, PSO-TVAC achieved the lowest power loss, measuring 72.79 [kW] and 12.14 [kW] for <br /> 3-PV and 3-WT installations, respectively. Furthermore, the optimal installation of 3-PV and 3-WT improved the distribution system performance by 65.49% and 94.25%, respectively.</span>

Optimal control strategy of photovoltaic system based autonomous micro grid for power quality improvement

<span>Due to the increasing number of distributed generation units being used in remote regions, the need for reliable and flexible operation of these systems has led to the development of microgrid technology. When a microgrid operates in an autonomous mode, it can experience unpredictable loads and other factors that can affect its operation. An optimal control mechanism is required to maintain the system's stability. Hence, in this paper optimal control strategy of autonomous microgrid for power quality improvement is presented. A test case of single phase 3.5 kW photovoltaic (PV) system based autonomous micro grid is considered. Particle swarm optimization (PSO) and Harris hawks optimization (HHO) optimal control strategies are implemented under standard test case and variable test cases. In all the cases </span><span lang="EN-IN">PV mean voltage-</span><span>Vmpv (V), </span><span>PV mean current</span><span>-</span><span>Impv (A), </span><span>RMS voltage-</span><span>Vrms (V), </span><span>RMS current-</span><span>Irms (A), </span><span>mean PV power-Ppv </span><span>(W), </span><span>autonomous grid power-</span><span>Pg (W)</span><span>, efficiency (%), total harmonic distortion (THD) (%), inverter losses (%) are evaluated. In all the cases HHO optimal control strategy for autonomous microgrid exhibits the best performance in comparison with PSO optimal control strategy. The inverter efficiency is improved, inverter losses are reduced and the THD is improved.</span>

Power Equalization Strategy Based on Adaptive Virtual Impedance

Due to the differences in the line resistance of each distributed generation unit, conventional sag control does not allow for precise distribution of power, which also reduces the problem of system reactive power accuracy. To address this problem, this paper analyzes the power equalization and distribution conditions. A method for adaptive adjustment of virtual resistance by system output power feedback is submitted. Reducing the variance among the original line resistances aims to solve the problem of power not being evenly divided and improve the equalization of reactive power. By building a Simulink parallel simulation model of the inverter, it is verified that the power feedback-based fetching and the improved droop control is effective.