Types Of Distributed Generation Research Articles

Maximum Penetration Level Evaluation of Hybrid Renewable DGs of Radial Distribution Networks Considering Voltage Stability

The issues regarding generation uncertainties associated with wind energy and solar photovoltaic (PV) systems along with load demand uncertainties are considered in this paper to evaluate the maximum penetration of renewable energy resources. The nodes which are less voltage stable are considered as the most suitable locations for distributed generations (DGs) placement. For identification of these critical nodes, a voltage stability index (VSI) has been utilized. To analyze the voltage profile, power losses and system voltage stability with large penetration of the wind energy and solar PV into the distribution networks, a probabilistic-based approach has been adopted. The penetration limit depends upon the type of DG that is connected to the distribution network. Usually, the integration of DGs reduces the power losses in the network, however as penetration level increases, the power losses begins to increase. The detailed mathematical models of wind and solar PV-based renewable resources are used. The Hong’s $$2m+1$$ point estimation method combined with Cornish–Fisher expansion is adopted in this paper to conduct the probabilistic studies. The effectiveness of the method is validated through IEEE 33-node radial distribution test network for four different scenarios. The results obtained have been verified and compared with Monte Carlo simulation technique.

Islanding detection in distributed generation system using intrinsic time decomposition

This study introduces the implementation of intrinsic time decomposition (ITD) based passive islanding detection technique for distributed generation (DG) system. The proposed method utilises voltage signals and decomposes it into a baseline signal and residual signal. The performance index in terms of energy computed from baseline signal is defined to discriminate between islanding and non-islanding events. The proposed ITD based technique for islanding detection has been analysed on different types of DGs connected to the system. The performance of the proposed technique is validated via simulation of distribution system modelled in EMTDC/PSCAD. The different critical operating conditions: lower end active and reactive power mismatch and events like capacitor switching, load switching, inception of fault, have been simulated to test the performance of the proposed scheme. The obtained results suggest that the proposed technique exhibits high reliability and has quick response time to detect islanding situation as compared to other passive islanding detection methods.

GA-based optimization for integration of DGs, STATCOM and PHEVs in distribution systems

Abstract This paper presents a Genetic Algorithms (GAs) for integration of various types of Distributed Generations (DGs), Static Synchronous Compensator (STATCOM) and Plug-in-Hybrid Electric Vehicle (PHEVs) with different static load models (DSLMs) such as LM-1, LM-2, LM-3, LM-4 and LM-5, respectively in distribution systems from minimization of total real power loss of the system viewpoint. In this analysis, the system power factor taken as power system performances in various cases such as without DGs, with various types of DGs, integration of DGs and STATCOM, integration of DGs, STATCOM and PHEVs in distribution system with DSLMs. The proposed methodology has been tested for IEEE-37 bus distribution test system. This research work is very much useful for researchers, scientific, industrial, academicians and practitioners for whose are working in the fields of integration of renewable energy sources, FACTS controllers and PHEVs in distribution systems with DSLMs from minimization of total real power loss of the system viewpoint. This research work also is useful for practical implementations of integration of renewable energy sources, FACTS controllers and PHEVs in distribution systems with DSLMs for enhancement of different power system performances from minimization of total real power loss of the system viewpoint.

Simultaneous Allocation of Multi-Type Distributed Generations and Capacitors Using Generic Analytical Expressions

This paper proposes a method for determining the optimal sites and sizes of multi-type distributed generations (DG) and capacitors for minimizing reactive power losses (RPL) in distribution systems. The proposed method is developed based on generic closed-form analytical expressions for calculating optimal sizes of DG units and capacitors at their candidate sites. The reduction in RPL with DG and capacitors is evaluated using another analytical expression that relates power injections of DG and capacitors with RPL. An optimal power flow algorithm (OPF) is incorporated in the proposed method to consider the constraints of the distribution systems, DG, and capacitors. Various types of DG are considered, and their optimal power factors can be accurately computed while optimizing the sizes of capacitors in a simultaneous manner to reduce RPL. The 69-bus distribution system is used to test the proposed method. An exact search method is employed to verify the accuracy of the proposed method. The effectiveness of the proposed method is demonstrated for solving the optimal allocation problem with different combinations of multi-type DG units and capacitors.

Active Distribution System Expansion Planning Using Lion Pride Optimization Algorithm

Distribution expansion planning (DEP) is considered as one of the main challenges of distribution companies. The DEP problem deals with the optimal expansion of distribution equipment and network. Considering the number of parameters and decision-making variables, and also the complexity of modeling have made the solution of this problem very difficult and complicated. This study proposes a novel approach to solve the DEP problem, where distributed generation (DG) resources are also incorporated into the distribution system. The purpose of this paper is to meet economic and operational requirements using DGs as candidate equipment for expansion of distribution system in order to avoid uncertainties of substations and feeders expansion. In order to have a more precise simulation, the type of DG must be specified. This, in this study, the solid oxide fuel cell (SOFC) technology is utilized as a DG. In order to achieve the optimum solution, the lion pride optimization algorithm searches the solution space considering the solution of backward-forward sweep load flow problem for two modes of with and without integration of DGs in 30-bus test system. The results of simulations imply that the voltage profiles of the system are improved and the total expansion cost is also mitigated.

Linear Power Flow Calculation of Distribution Networks With Distributed Generation

To address the shortcomings of the existing linear power flow calculation methods for distribution networks with low versatility and calculation accuracy, a linear power flow calculation method considering distributed generation (DG) is proposed. According to the characteristics of distribution networks and using the Taylor series expansion technology, the nonlinear terms of the basic power flow equation are linearized. The reactive power generated by the non-PV type DG is simplified to a quadratic function of the voltage amplitude. Then, combined with linear approximation and the simplified DG calculation model, the basic power flow equation is simplified into a linear form. Based on the linear power flow equation, a linear power flow calculation method for distribution networks with DG is proposed. The proposed method, which considers various types of DG, has a strong versatility. Finally, the calculation results of typical test systems show that compared with the existing linear power flow calculation methods, the proposed method has a higher calculation accuracy and more versatility and can be used for rapid analysis of distribution networks.

Optimal Coordination of Double-Inverse Overcurrent Relays for Stable Operation of DGs

Due to the increasing penetration of distributed generations (DGs) in distribution networks, the performance of protective relays is becoming more critical to maintain the stability of the DGs especially during fault conditions. Among different types of DGs, squirrel cage induction generators (SCIGs) and synchronous DGs are sensitive to faults and might become unstable even after fault clearance. Since the fault clearing time depends on the overcurrent relays (OCRs) characteristic curves, this paper proposes a double-inverse OCR (DIOCR) characteristic to provide proper coordination while maintaining DGs stability. The proposed method defines the critical clearing time curve for each DG and combines them with DIOCRs curves and coordination time interval constraints for finding optimal DIOCRs settings. The proposed method is simulated on the IEEE 33-bus distribution network equipped with SCIG- and synchronous-based DGs. The obtained results highlight the capability of DIOCRs in protecting distribution system with DGs considering stability constraints.

Integration and Evaluation of the Impact of Distributed Generation on the Protection System of Distribution Network with DG Using Etap

Distributed Generation (DG) has been growing rapidly in deregulated power systems due to their potential solutions to meeting localized demands at distribution level and to mitigate limited transmission capacities from centralized power stations. Penetration of DG into an existing distribution system has so many impacts on the system. Despite the benefits a DG will provide; it has a negative impact on the power system protection, thus affecting both reliability and stability of the system. This paper evaluates the impact of DG on the power protection systems with DG integrated in the systems. IEEE 33 Bus system was modelled in full operational details using ETAP. Protection coordination was carried out using Modified PSO. To investigate the impact of DG on the protection systems, different fault scenario have been simulated with and without DG installed. The fault current level, false tripping, unintentional islanding, and behavior of the existing protection system were investigated considering two scenarios. Case one was the integration of single DG while case two was the integration of two DGs. The type of DG integrated was solar photovoltaic. Simulation results revealed that the fault current level for a 3 phase fault at bus 27 for the system increases by 2.5% for case one and 24% for case two. There was unitentational islanding and false tripping as a result of the current contribution from the DG. The sequence of operation of the protective devices clearly showed that there was mis coordination of the protective devices.

Distributed Generation Harmonic Interaction in the Active Distribution Network

Significant increase of distributed generation (DG) presence and active distribution network (ADN) development cause changes in distribution network’s power quality (PQ), mostly in distorted system voltages and currents. This paper analyses harmonics generation from multiple DG types, such as solar and biogas power plants, and simulates harmonic interactions in ADN in order to identify potential PQ issues. Each harmonic source observed in this paper was modelled according to IEC 61 000 with the model parameters provided by power quality measurements in the real system on several DG power plants and passive consumer nodes. A harmonic load flow is performed on a detailed ADN model for different presumed DG expansion scenarios that indicate the complexity of the DG impact on the AND’s PQ. Quantitative and qualitative graphical presentation for cumulative and the most significant ADN nodes is given and the assessment for the potential ADN development based on PQ indices is proposed.

A New Hybrid Technique for Minimizing Power Losses in a Distribution System by Optimal Sizing and Siting of Distributed Generators with Network Reconfiguration

Transformations are taking place within the distribution systems to cope with the congestions and reliability concerns. This paper presents a new technique to efficiently minimize power losses within the distribution system by optimally sizing and placing distributed generators (DGs) while considering network reconfiguration. The proposed technique is a hybridization of two metaheuristic-based algorithms: Grey Wolf Optimizer (GWO) and Particle Swarm Optimizer (PSO), which solve the network reconfiguration problem by optimally installing different DG types (conventional and renewable-based). Case studies carried out showed the proposed hybrid technique outperformed each algorithm operating individually regarding both voltage profile and reduction in system losses. Case studies are carried to measure and compare the performance of the proposed technique on three different works: IEEE 33-bus, IEEE 69-bus radial distribution system, and an actual 78-bus distribution system located at Cairo, Egypt. The integration of renewable energy with the distribution network, such as photovoltaic (PV) arrays, is recommended since Cairo enjoys an excellent actual record of irradiance according to the PV map of Egypt.

Phase Balancing Home Energy Management System Using Model Predictive Control

Most typical distribution networks are unbalanced due to unequal loading on each of the three phases and untransposed lines. In this paper, models and methods which can handle three-phase unbalanced scenarios are developed. The authors present a novel three-phase home energy management system to control both active and reactive power to provide per-phase optimization. Simplified single-phase algorithms are not sufficient to capture all the complexities a three-phase unbalance system poses. Distributed generators such as photo-voltaic systems, wind generators, and loads such as household electric and thermal demand connected to these networks directly depend on external factors such as weather, ambient temperature, and irradiation. They are also time dependent, containing daily, weekly, and seasonal cycles. Economic and phase-balanced operation of such generators and loads is very important to improve energy efficiency and maximize benefit while respecting consumer needs. Since homes and buildings are expected to consume a large share of electrical energy of a country, they are the ideal candidate to help solve these issues. The method developed will include typical distributed generation, loads, and various smart home models which were constructed using realistic models representing typical homes in Austria. A control scheme is provided which uses model predictive control with multi-objective mixed-integer quadratic programming to maximize self-consumption, user comfort and grid support.

A reliability-based stochastic planning framework for AC-DC hybrid smart distribution systems

This paper introduces a stochastic multi-objective optimization model for the planning of AC-DC hybrid smart distribution systems (DSs). The proposed model determines the optimal AC-DC network configuration that achieves two main objectives: (1) minimizing system costs, and (2) maximizing system reliability. The second objective is achieved through the minimization of the expected energy not supplied. Network buses and lines can become either AC or DC in order to achieve the planning objectives. The model features a Monte-Carlo simulation (MCS) for addressing stochastic variations related to load demands and renewable distributed generators (DGs). The hybrid planning problem has been solved by means of a multi-objective genetic algorithm, and the trade-off between the DS costs and reliability has been evaluated using the Pareto optimality concept. The proposed model has been tested using a case study involving a hybrid DS that included a variety of types of loads and DGs. Solving the same case study using a traditional AC planning technique provided verification of the benefits offered by the proposed model, whose efficacy was confirmed through a comparison of the AC and hybrid Pareto fronts.

Probabilistic Assessment of Hosting Capacity in Radial Distribution Systems

High penetration of distributed generation (DG) is mainly constrained by voltage-related issues. Due to the uncertainties associated with type, size, and location of DGs, it is difficult to quantify their integration limits in distribution networks, i.e., hosting capacity (HC). To address this issue, this paper proposes a probabilistic-based framework to determine the maximum integration limits of DGs considering the voltage rise and voltage deviation constraints. Such framework requires the use of the HC model, which can be formulated as a nonlinear optimization problem. Adding the voltage deviation constraint in the HC problem makes the model unsolvable. We address this issue by proposing a two-step algorithm to linearize the HC model. Then, using the linearized model, a probabilistic framework is proposed for considering the load variability and DGs uncertainties. To validate the efficacy and accuracy of the proposed framework, we identify the HC of a balanced and an unbalanced distribution networks and compare our results with those obtained from comprehensive power flow method and the traditional conservative planning. Finally, using the proposed framework, the impact of voltage deviation constraint, load growth, DG type and network structure on the HC are comprehensively studied using different DG technologies (i.e., Photovoltaics and wind).

Analytical and particle swarm optimization algorithms for optimal allocation of four different distributed generation types in radial distribution networks

In this paper, two algorithms, analytical and particle swarm optimization (PSO), are introduced and compared with each other for optimal allocation of distributed generation (DG) units in radial distribution networks (RDNs) to minimize the total loss in real power. Four different types of DG units are considered in this work. The two algorithms make use of a backward / forward load flow method for the load flow analysis of the RDN by which the node voltages and the total active power loss of the network are determined. The introduced algorithms are tested on the IEEE 41 bus radial distribution system and the results are obtained using MATLAB. Discussions are provided based on the results of case studies

Service restoration to critical loads using microgrids considering dynamic performance of DGs

When an extreme weather event strikes a distribution system, it is helpful to use microgrids to restore the interrupted critical loads. Due to the relatively small capacity and low inertia of distributed generators (DGs), the switching operations during the restoration process may cause severe fluctuations in voltage, current, and frequency, leading to prime-mover stalling or triggering protection relays. It is essential to investigate the dynamic characteristics of DGs during the restoration procedure. The dynamic models of different types of DGs are developed to analyse the dynamic characteristics. Analytical constraints on the dynamic performance of DGs are obtained from the simulation results, which can be incorporated into the optimisation models of critical load restoration problems. The modified IEEE 32-bus test feeder is simulated to validate the effectiveness of the proposed method.

Optimal installation of multiple type DGs considering constant, ZIP load and load growth

ABSTRACT Distributed generation (DG) has drawn the attention of researchers and industrialists for quite a time now due to its numerous advantages. This paper proposes an analytical approach for optimal installation of multiple type DGs in a radial distribution network with consideration of constant, ZIP load model (combination of constant impedance, current, power load models) and load growth. It mainly emphasises on: (i) optimal installation of multiple type DGs with a constant load, (ii) impact of considering ZIP load model on optimal installation of DGs, (iii) proposing load growth factor with load growth rate of 7.5% for the planning period of five years, (iv) impact of considering ZIP load model and load growth simultaneously and (v) cost–benefit analysis. The results are compared for IEEE 33 bus distribution network.

Optimal oversizing of utility-owned renewable DG inverter for voltage rise prevention in MV distribution systems

The penetration of renewable distributed generations (DG) is recently being increased in distribution systems. Due to the intermittent nature of these generation units, several technical problems are expected based on the environmental conditions and load profiles, such as voltage rise and increasing losses. A traditional way to alleviate these technical problems is to oversize their interfacing inverters for releasing their capacities to inject/absorb further reactive power. In the literature, the DG inverter is normally oversized by a certain percentage (e.g., 10%) for this purpose. In turn, an optimization-based method is proposed in this paper to calculate the optimal oversize of the interfaced inverter employed in various utility-owned DG types to regulate voltages and to reduce losses with minimum total costs. The proposed method considers the active power curtailment (APC) feature in the DG inverter and the transformer taps. Different control schemes of the interfaced inverter are considered and incorporated in the proposed optimization model. The simulation results demonstrate the effectiveness of the proposed method compared with existing methods.

Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

This paper presents an optimization solution for renewable Distributed Generation (DG), as imposed in the Green Building Rating System (GBRS) for a public hospital. Solar photovoltaic DG unit (PV-DG) is identified as a type of DG used in this paper. The proposed optimization via PV-DG coordination will improve the sustainable energy performance of the green building by power loss reduction within accepted lower losses region using Artificial Bee Colony (ABC) algorithm. The setup input data from one of Malaysian public hospitals’ power distribution system is been adopted and simulation results via MATLAB programming show that the optimization of DG forming into bigger-scale imposed system provides a better outcome in minimization of total power losses within appropriate voltage profile as compared to current PV-DG imposed in GBRS. The objective function representing total power losses which also supported by related literature give a measure that forming sufficient and optimal PV-DG assessment criteria is highly important, thus, current PV-DG assessment in GBRS is proposed to be reviewed into new parameter setting for public hospital due to its’ high energy demand and distinctive electrical load profile.

Distributed generation planning in active distribution network considering demand side management and network reconfiguration

This paper proposes a novel distributed generation (DG) planning methodology in active distribution network considering both demand side management and network reconfiguration. The objective function of the planning model is to minimize the total cost over the planning horizon, including investment cost of DG, operation and management cost of DG, fuel cost of DG, active management cost of DG, and demand side management cost. The constraints contain not only traditional DG investment and electrical restrictions (for instance, limitation of DG penetration, constraint of nodal voltage, constraint of branch capacity, etc.), but also the various restrictions of active management measures including regulating the on-load tap changer of transformer, controlling the output power of DG, demand side management and network reconfiguration. It is a large-scale mixed integer nonlinear programming model, which cannot be effectively solved by a single algorithm. Based on the idea of decomposition and coordination, the planning model is converted to a three-layer programming model. A hybrid solving strategy is developed to solve the model, in which differential evolution algorithm is used to determine the type, location and capacity of DG, and tree structure encoding-partheno genetic algorithm and primal–dual interior point method are applied to simulate the operation of active distribution network and find out the optimal operation state for each scenario. Case studies are carried out on a 61-bus active distribution network in East China, and results show that the total cost over the planning horizon can be reduced about 3.8% when demand side management and network reconfiguration are considered.

Adaptive directional overcurrent relaying scheme for meshed distribution networks

Distribution networks are evolving into active meshed networks with bidirectional power flow as the penetration of distributed generation (DG) sources is increasing. This necessitates the use of directional relaying schemes in these emerging active distribution networks. However, conventional directional overcurrent (OC) protection will not be adequate to protect these networks against the stochastic nature of renewable DGs and the changing network architectures. Hence, this study proposes an adaptive directional OC relay algorithm that determines optimal protection settings according to varying fault currents and paths induced by the DGs in active meshed distribution networks. The proposed algorithm consists of a two-phase approach that deduces: (i) optimal floating current settings through a fuzzy decision-making module, and (ii) optimal floating time settings through an optimisation algorithm. Extensive case studies are implemented on the modified power distribution networks of IEEE 14-bus and IEEE 30-bus by varying the type, location, and size of DGs. The results validate the ability of the proposed protection scheme to capture the uncertainties of the DGs and determine optimal protection settings, while ensuring minimal operating time.