High Penetration Of Distributed Generation Research Articles

Dynamic impact of hybrid wind-solar photovoltaic power injection on small signal stability of Nigerian 11kV power system using Self Organizing Map neural network

Power industry reorganization, legislation on greenhouse gas emissions and inadequate conventional generation capacity encourage the idea of incorporating Distributed Generation (DG) into the distribution networks as unconventional sources of power generation. High penetration of DG has further increased the complexity of the analysis of small signal stability because the variability of renewable energy sources affects the stability of power system. Therefore, this research work investigates the effect of wind and solar photovoltaic power injection on small signal stability of Nigerian 11 kV power network. Wind and solar photovoltaic were modelled using probabilistic methods and output power at twenty-one different locations within Nigeria was computed. Using the real and reactive power data of the network, Self-Organizing Map (SOM) neural network was trained and tested for the assessment of the small signal stability of the distribution network before and after the injection of renewable power in python virtual environment. The integration of hybrid wind-solar PV distributed generation at 30 %, 60 %, 90 % and 100 % into the studied 11 kV power distribution network improved its small signal stability by 1.4 %, 2.1 %, 2.5 % and 3.2 % respectively. Moreover, increase in the injection of power gotten from wind and solar sources reduces the oscillation frequency of the system from 1.39 Hz to 1.01 Hz and increases the damping from 4.6 % to 13.2 %. Reactive power increment in the range of 5 %-20 % improved the small signal stability of the system by the range 2.4 %-7 %. This improvement will translate to better power transfer capability of the network.

DG Compensation Using Optimal Distribution in Microgrids with High DG Penetration

This study developed a model to compensate for both active and passive power in an electric microgrid with an optimal power flow to allow a detailed analysis of its power flow, which encourages the integration of renewable energy sources (RESs). Mixture integer linear programming (MILP) is proposed, with distributed generation (DG) integrated into the existing bars. It is developed in the GAMS tool to minimize operating costs in the microgrid as an objective function, to guarantee reliability, and quality in the microgrid. The algorithm calculates an optimal solution that meets all requirements for reliability and quality in the microgrid. Finally, a comparison of data between the two systems without and with DG was performed, showing an improvement in voltage profiles, reduced active power losses in the lines, a better power factor (PF), and improved angular behavior; that also adheres to the restrictions set forth at a minimum operating cost. A nine-bar model has been used to model the problem by IEEE standards.

Nonlinearity-Adaptive Data-Driven Power Flow Constraint for Distribution Network Optimization

Data-driven power flow (PF) analysis methods have higher practical value to deal with the inaccurate branch parameters in medium and low-voltage distribution networks, which can be easily integrated into the classic optimization framework as a constraint. However, the PF mapping relationship of the measurement data shows stronger nonlinearity, with the high penetration of distributed generation (DG), leading to the low accuracy of the linear PF constraint. To this end, we propose an incomplete dimension lifting (IDL) data-driven PF method for distribution network optimization. The state variables are divided into optimization variables and uncontrollable variables, among them, the optimization variables keep the original linear state space or converted into quadratic space to simplify the optimization solution; and the uncontrollable variables is dimension lifted to fit the nonlinearity of PF. In addition, in order to deal with the problem of gradient direction error caused by nonlinear model overfitting, the first-order sensitivity constraint is involved in parameter regression process. The standard IEEE cases with high penetration of DG demonstrate that the proposed method can achieve higher accurate PF constraint and better optimization results, compared to the existing data-driven PF constrain.

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 Allocation of Battery Energy Storage Systems to Enhance System Performance and Reliability in Unbalanced Distribution Networks

The continuously increasing renewable distributed generation (DG) penetration rate significantly reduces environmental pollution and power generation cost and satisfies society’s rapid growth in electricity demand. Nevertheless, high penetration of renewable DGs, such as wind power and photovoltaics (PV), might deteriorate the system’s efficiency and reliability due to its intermittent and stochastic natures. Introducing battery energy storage systems (BESSs) to the distribution system provides a practical method to compensate for the above deficiency since it can deliver and absorb power when needed. Hence, it is important to determine the optimal allocation of BESS to achieve maximum assistance in the grid. This study proposes an optimal BESS allocation methodology to improve reliability and economics in unbalanced distribution systems. The optimal BESS allocation problem is solved by simultaneously minimizing the cost of energy interruption, expected energy not supplied, power loss, line loading, voltage deviation, and BESS cost. The proposed technique is implemented and analyzed on a high renewable DG penetrated unbalanced IEEE-33 bus network using DIgSILENT PowerFactory software (version 2020 SP2A). An enhanced grey wolf optimization (EGWO) algorithm is developed to optimize BESS location and size according to the selected objective function. The simulation results show that the proposed optimal BESS optimization technique significantly improves the economics and reliability in unbalanced distribution systems and the EGWO outperforms the gray wolf optimization (GWO) and particle swarm optimization (PSO) algorithms.

Robust Distribution Network Reconfiguration in the Presence of Distributed Generation Under Uncertainty in Demand and Load Variations

In modern power systems, distributed generation (DG) plays an important role in energy losses reduction, but DG penetration in such networks is restricted by technical and investment limitations. Therefore, distribution network reconfiguration (DNR) and DG operation reduce power losses more efficiently than when only DG is utilized. Also, network reconfiguration mitigates improper DG placement in such systems which are subjected to high penetration of variable loads and DG. On the other hand, electrical energy demand is estimated by load forecasting methods and therefore is a time-variant and uncertain parameter. Moreover, DG power generation is uncertain and depends on variable load power. Consequently, models presented for the reconfiguration problem should be adequately robust against load and generation uncertainties. Thus, the present paper proposes an effective robust model for reconfiguring distribution networks with load and generation uncertainties. The proposed model is sufficiently simple for implementation and is accurate enough to find the optimal solutions in acceptable computational times. The main features of the proposed model are its high robustness against uncertain parameters, in which proposed configurations are not changed easily by small variations in DG power and load amounts, and its effectiveness, which means that uncertain parameters may change the obtained solutions.

Optimal Dispatch of Battery Energy Storage in Distribution Network Considering Electrothermal-Aging Coupling

With the rapid development of distributed generation (DG), battery energy storage systems (BESSs) will play a critical role in supporting the high penetration of renewable DG in distribution networks. The traditional dispatching approach of BESSs commonly adopts linear models with constant operational characteristics and neglects the aging cost. However, the operational characteristics of BESSs are related to operational states, i.e., temperature, state of charge and current. Furthermore, the aging cost is also an important issue to optimize the economic profitability of BESSs, which is affected by the operational states as well. To this end, this paper proposes an optimal dispatch model of BESSs in distribution networks that considers the electrothermal-aging coupling relationship. The nonconvex original model is reformulated as a second-order cone programming problem, which can be effectively solved. Case studies show that the proposed method accurately captures the operational characteristics and synergistically optimizes the operational cost of distribution networks and the aging cost of BESSs. Compared to the traditional dispatching approach, the proposed method largely avoids the deviation between the scheduled power and actual power of BESSs and effectively saves the total cost, leading to a 48% extension of lifetime and a 30% increase in profitability of the BESSs.

Faulty Feeder Detection for Single Line-to-Ground Fault in Distribution Networks With DGs Based on Correlation Analysis and Harmonics Energy

Faulty feeder detection helps ensure the stable operation after single line-to-ground (SLG) faults in distribution networks. However, the SLG fault currents are weak, the fault conditions are complex, and distortion of fault signals may occur owing to the effect of distributed generators (DGs), which would result in unacceptable performance of the existing detection methods. To improve the accuracy of faulty feeder detection under high penetration of DGs, this paper firstly analyzes the three-sequence networks after SLG faults occur in distribution networks with DGs connection, and points out that the DGs connection does affect the zero-sequence components when DGs are connected to the faulty feeder. Besides, the polarity differences between zero-sequence voltage (ZSV) and zero-sequence currents (ZSC) are revealed. Subsequently, variational mode decomposition is employed to characterize the overall trend of the ZSV and ZSCs, and cross-correlation analysis is applied to capture the polarity characteristics between ZSV and ZSCs. In addition, harmonics characteristics of ZSCs are used as an auxiliary criterion when ZSCs are highly distorted caused by DGs connection. Finally, both of them are utilized to construct the detection scheme. Simulation results and practical data test demonstrate the efficiency of the proposed method.

An Optimized Fuzzy Based Control Solution for Frequency Oscillation Reduction in Electric Grids

The demand for uninterruptible electricity supply is increasing, and the power engineering sector has started researching alternative solutions. Distributed generation (DG) dissemination into the electric grid to cope with the accelerating demand for electricity is taken into consideration. However, its integration with the traditional grid is a key task as sudden changes in load and their fickle nature cause the frequency to deviate from its adjusted range and affect the grid’s reliability. Moreover, the increased use of DG will significantly impact power system frequency response, posing a new challenge to the traditional power system frequency framework. Therefore, maintaining the frequency within the nominal range can improve its reliability. This deviation should be removed within a few seconds to keep the system’s frequency stable so that supply and demand are balanced. In a traditional grid system, the controllers installed at the generation side help to control the system’s frequency. These generators have capital installation costs that are not desirable for system operators. Therefore, this article proposed a comprehensive control framework to enable high penetration of DG while still providing adequate frequency response. This is accomplished by investigating a grasshopper optimization algorithm-based (GOA) fuzzy PD-PI controller (FPD-PI) for analyzing frequency control and optimizing the FPD-PI controller gains to minimize the frequency fluctuations. In this paper, interconnected hybrid power systems (HPS) are considered. In this study, the response of a system is analyzed, and the results validate that the oscillations in frequency are substantially reduced by the proposed controller. Moreover, our model is the best option for controlling frequency instead of conventional controllers, as it is efficient and fast to regulate frequency by switching the preferred loads on or off.

Impacts of Distributed Generation on Power System Protection

Distributed generation (DG) offers huge benefits to the power system network to cater to the rapidly growing demand for electric power. The integration of DG units into existing power networks is beneficial to both utilities and consumers. However, the installation of DG units in distribution networks might impose some operational, technical, and economic impacts. Increased short-circuit level and changes in load flow direction are examples of the technical issues arising from the high penetration of DG. Such issues will affect the existing protection system, mainly overcurrent relays. Thus, to ensure reliable and selective operation of protection relays, the impacts of DG should be considered. This paper discusses the impacts of DG on the protection systems by identifying various protection problems. The paper is complemented by a simulation case study on the impacts of DG on fault levels, protection coordination, and distance relays. The simulated system was modeled using DIgSILENT PowerFactory® software.

Flexible Interconnected Distribution Network with Embedded DC System and Its Dynamic Reconfiguration

Flexible interconnection transformation of a distribution network using all-control power electronics technology will help to overcome the technical bottleneck of distributed generation (DG) penetration and high-quality power supply in the traditional distribution network. However, the flexible interconnection form that uses back-to-back power electronic converters to replace tie switches has disadvantages such as high cost and large footprint, so its mass promotion and application are bound to be limited. Therefore, a new topology of flexible interconnected distribution network with embedded DC system (FDN+EDC) with a better economy is proposed. Firstly, the topology of FDN+EDC is introduced to improve the controllability level of the distribution network under high percentage DG penetration, and is compared with the conventional flexible interconnection method. Secondly, in order to realize the coordinated optimal economic operation of source, network and load in the FDN+EDC, a dynamic reconfiguration model of switches status and continuous adjustment of flexible interconnection device (FID) are proposed. Then, to achieve a fast and globally optimal solution of the model, a hierarchical coordinated optimization strategy is designed based on an improved particle swarm algorithm for the optimization of discrete and continuous variables. Finally, the validity of the algorithm is verified, and an 88-node FDN+EDC is constructed to verify the advantages of the proposed embedded DC flexible interconnection topology and realize the joint optimal dispatch of network-source-load.

Load Flow and Short-Circuit Methods for Grids Dominated by Inverter-Based Distributed Generation

The use of power-electronics-based devices in distribution generation seeks to improve energy quality and reduce costs. The inverter-based distributed generator, that works in different operation modes, has emerged as a promising technology. In a high distributed generation penetration scenario it is important to know the voltage profile and fault information due to the uncertainty in the generator operation and the impact that have on the network. This study aims to use two proposed methods of analysis: for power flow, based on backward/forward sweep method, and short-circuit, based on hybrid impedance matrix, that considers the inverter operation modes and represents each generator as a voltage-controlled current source. The chosen network is the IEEE 34-Node Test Feeder with a generator on each load per phase. The voltage profiles obtained will be validated with a Simulink/Matlab phasorial model. The results show an average error of 2.39% and a gain in voltage profile processing time of 2185.24%, making its use consistent for larger systems.

Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration

This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the BESS can reduce costs incurred in the systems, alleviate reverse power flow when the systems are in the high DG penetration level, and also achieve peak shaving during high demand. To find the optimal location and sizing of the BESS, three optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), and salp swarm algorithm (SSA), are applied, and their performances are compared. The considered objective function is the system costs consisting of transmission loss cost, peak power cost, and voltage deviation cost. The system performance improvement is compared in terms of transmission loss, peak demand, and voltage regulation reductions. IEEE 33- and 69-bus distribution systems with high DG penetration are tested to investigate the performance improvement of the BESS installation. The results found that the installation of the BESS could successfully decrease system cost, improve voltage profile, reduce power losses, alleviate reverse power flow, and achieve peak shaving where PSO and SSA are found to be the best competitive algorithms. So, the proposed method can be further applied to find the optimal location and sizing of the BESS to improve the performance of practical systems in the future.

Headroom-based optimization for placement of distributed generation in a distribution substation

This paper presents a headroom-based optimization for the placement of distributed generation (DG) in a distribution substation. The penetration limits of DGs into the existing distribution substations are often expressed as a function of the feeder’s hosting capacity (headroom). Therefore, it is important to estimate the reliability of the network's operation as well as that of the limits imposed by the power quality standards by evaluating of the hosting capacity (headroom) of the existing distribution feeder substation. This study aims at developing a novel algorithm for positioning a bus with permissible headroom capacity for DG positioning without causing voltage violations but maximizing the active power supply. Since DG increases short-circuit faults, the algorithm is useful for utility companies to select feeder substations that have permissible headroom capacity for DG installation and thus, contributing to reducing high DG penetration in the network. The modeling and optimization were carried out the Power System Software for Engineers (PSS/E) environment using the IEEE 14-bus test system. The results obtained from the case study show that only two (2) feeder substations out of fourteen (14) have the permissible headroom capacity for DG connections.

Hybrid Protection Scheme Based Optimal Overcurrent Relay Coordination Strategy for RE Integrated Power Distribution Grid

A directional overcurrent relay is commonly used to protect the power distribution networks of a distributed system. The selection of the appropriate settings for the relays is an important component of the protection strategies used to isolate the faulty parts of the system. The rapid growth of distributed generation (DG) systems present new challenges to these protection schemes. The effect of solar photovoltaic power plants on relay coordination is studied initially in this research work. A protection strategy was formulated to guarantee that the increased penetration of solar photovoltaic (PV) plants does not affect the relay coordination time. This paper addresses these issues associated with a high penetration of DG through the use of a hybrid protection scheme. The protection strategy is divided into two parts. The first part is based on an optimal fault current limiter value estimated with respect to constraints and the optimal time multiplier setting, and then the coordination time interval is estimated with respect to constraint in Part II. The results of these analyses show that a hybrid protection scheme can effectively handle the complexity of distributed generation (DG) and dynamic relay coordination problems. In this research, three optimization algorithms have been used for calculating the estimated value of impedance fault current limiter (Zfcl) and time multiplier setting (TMS). The response time of hybrid protection schemes is very important. If the computational time of their proposed algorithms is less than their actual computational time, then their response time to address the issue is also less. The performance in all algorithms was identified to arrive at a conclusion that the grey wolf optimized algorithm (GWO) algorithm can substantially reduce the computational time needed to implement hybrid protection algorithms. The GWO algorithm takes a computational time of 0.946 s, achieving its feasible solution in less than 1 s.

A Two-Level Simulation-Assisted Sequential Distribution System Restoration Model With Frequency Dynamics Constraints

This paper proposes a service restoration model for unbalanced distribution systems and inverter-dominated microgrids (MGs), in which frequency dynamics constraints are developed to optimize the amount of load restoration and guarantee the dynamic performance of system frequency response during the restoration process. After extreme events, the damaged distribution systems can be sectionalized into several isolated MGs to restore critical loads and tripped non-black start distributed generations (DGs) by black start DGs. However, the high penetration of inverter-based DGs reduces the system inertia, which results in low-inertia issues and large frequency fluctuation during the restoration process. To address this challenge, we propose a two-level simulation-assisted sequential service restoration model, which includes a mixed integer linear programming (MILP)-based optimization model and a transient simulation model. The proposed MILP model explicitly incorporates the frequency response into constraints, by interfacing with transient simulation of inverter-dominated MGs. Numerical results on a modified IEEE 123-bus system have validated that the frequency dynamic performance of the proposed service restoration model are indeed improved.

Wide area monitoring, protection, and control application in islanding detection for grid integrated distributed generation: A review

The assimilation of Distributed Generation (DG) into the electric power system (EPS) has become more attractive as the world is following a trend to reduce greenhouse gas emissions by introducing more renewable energy forms resulting in high penetration scenarios. This high penetration of DGs brings several challenges to the protection philosophy of the EPS which compromises its reliability, availability, and efficiency. Under high DG penetration scenarios, conventional islanding detection methods (Idms) fail to detect an island as the grid loses its inertia to leverage a significant frequency and voltage mismatch necessary for Idms to effectively detect an islanding event. This has given rise to the birth of Artificial Intelligent (AI) methods that are found to perform better in islanding detection. AI Idms are computationally intensive and require a lot of data to operate accurately. Because the computational burden of these methods requires fast computing hardware, the current trend of AI Idms are integrated with Wide Area Monitoring, Protection, and Control (WAMPAC) system. This paper aims at reviewing all these Idms and the WAMPAC’s system latency when hosting AI Idms which are currently the best in islanding detection. This is done to determine if the WAMPAC system latency plus Idms computational time meet the islanding detection time specified by the IEEE Standard 1547 framework.

Protection philosophy for distribution grids with high penetration of distributed generation✰

Distributed Generation (DG) can cause several problems in electrical systems that are not prepared to deal with these new sources: situations such as bidirectional power flow and large variations in short-circuit current values. This article presents changes in the actual distribution systems protection philosophy that intend to make the protection system always work properly and reliably eliminate any short-circuit. Furthermore, it shows that the actual philosophy is inefficient in systems with high DG penetration level and, through modifications in the actual philosophy, using available functions in the protection devices, it is possible to increase the reliability and assertiveness of the protection system for any fault.

An Approach for Optimal Coordination of Over-Current Relays in Microgrids with Distributed Generation

The ever increasing presence of renewable distributed generation (DG) in microgrids is imposing new challenges in protection coordination. The high penetration of renewable DG enables microgrids to operate under different topologies, giving rise to bidirectional power flows and in consequence, rendering traditional coordination approaches inappropriate to guarantee network security. This paper proposes an approach for the optimal coordination of directional over-current relays (OCRs) in microgrids that integrate renewable DG and feature several operational modes. As a main contribution, the characteristic curves of directional OCRs are considered to be decision variables, instead of fixing a single type of curve for all relays as considered in previous works. The proposed approach allows for the selection of several IEC and IEEE curves which combination results in the best protection coordination. Several tests were carried out on an IEC benchmark microgrid in order to show the applicability of the proposed approach. Furthermore, a comparison with other coordination approaches evidenced that the proposed approach is able to find lower operation times and, at the same time, guarantee the suitable operation of protections under different condition faults and operational modes.

Frequency control of droop‐based low‐voltage microgrids with cobweb network topologies

When distributed generation (DG) technologies are implemented in an islanded low-voltage microgrid (LVMG), the topological architecture directly affects the frequency synchronisability. Especially in cases of high DG penetration, the synchronisability of existing traditional topological architectures for LVMGs is very limited. However, a cobweb network topology, which combines the characteristics of several traditional topological architectures, has become a novel alternative for LVMGs. In this context, a compact criterion related to the Moore–Penrose inverse of the incidence matrix for the synchronisability of an LVMG is derived. Then, based on a linear transformation and Moore–Penrose inverse theory, a comparative analysis of the synchronisability of LVMG systems with different topological architectures is presented, the results of which indicate that the synchronisability can be significantly enhanced in a cobweb network topology and that the Braess paradox can also be effectively avoided during the corresponding topological transformation. The effectiveness of the proposed synchronisation criterion is validated based on the Iceland power network, modelled as a cobweb-based LVMG with large-scale DG integration, which exhibits excellent sychronisability.