Reliability Analysis and Optimization Configuration of Distribution Network Based on Autonomous Control Unit

Distributed generations (DGs) are widely used to meet electric energy demand in distribution networks. DGs are advantageous compared to the centralized generating units in many ways including reducing power loss, improving voltage profile, enhancing network stability, decreasing pollution, releasing transmission line capacity, and reducing congestion of distribution lines. The size and site of DGs logically influence power loss in distribution networks. The optimal place and capacity of DGs are determined aiming at minimizing power loss in distribution networks. In this article, firefly algorithm (FA) is used for optimum placement of various DGs in distribution networks. Optimum power factor of DGs along with active and reactive powers are obtained in this work. Various DGs of generating/consuming types are considered in the suggested method. Performance analysis of the proposed method has been done on standard IEEE 33 bus system in MATLAB.

This paper presents a new framework to analyze the penetration of distributed generation (DG) in distribution systems (DS) based on modified Monte Carlo simulation. The placement and capacity of DG are generated as random variables with probability density functions following the optimality principle of the system. The method of power flows analysis is employed to evaluate the economic and technical aspect of the network both with and without DG sources inside. The results in different scenarios are combined with weighted factors to form the performance indices. The proposed framework is testified in a practical 15 MVA, 22 kV, 48-bus DS in Thai Nguyen, Vietnam. The simulation result shows that many advantages can be achieved with DG such as lower power losses, smaller voltage deviation, over-load reduction, etc. The proposed framework can serve as a platform for DS planning with DG sources in practice.

With recent development of technology and management in power market and equipment, more and more distributed generation (DG) is embedded in the distribution network. However the approach of connecting DG in most cases is based on a so-called ‘fit and forget’ policy and the capacity of DG is limited rigidly by distribution system operator to avoid the negative effects of high level penetration. New management technologies have been proposed to handle the integration of DGs in the distribution networks. In this review, the micro grid (MG) was treated as the local control method to coordinate DGs within a small area of distribution network. And the active distribution network (AND) was treated as the global control mechanism to actively manage DGs, MGs and other equipment. The operation framework of ADN was firstly introduced. Then based on the static and dynamic models of DGs and MGs, impacts of DGs and MGs on the ADN are surveyed from power quality, stability to the operation. Finally, the conclusion and suggestion is given in this paper.

This paper presents an approach to coordinated planning of distribution network (DN) and distributed generation (DG) considering uncertainties of output of DG and load. To overcome shortage of traditional separated planning of DN with DG and maximize positive influence brought by DGs, the multi-objective integrated planning model of DN and DG is established, in which the types, location, capacity of DGs, lines in need of being upgraded and lines to be built for access of new load point are taken into account as variables, and investment, power purchasing, network loss and power failure are considered as objectives. In face of uncertainties of load and output of DGs, first the corresponding probability models are established, then latin hypercube sampling (LHS) based on those is adopted to get samples and research scenarios are obtained through samples reduction. A multi-objective chaos improved PSO based on theory of pareto optimal solution set is proposed to solve the model. Finally, the method is applied in improved IEEE 33-node distribution system and effectiveness and feasibility of the model and algorithm are verified.

This paper provides an analytical survey of the islanding detection techniques for the distributed generation systems. Islanding phenomena on takes place when the power supply from the main utility is intermittent due to numerous reasons, but the distributed generation keeps supplying power into the distribution networks. Islanding can be dangerous to workers and electrical equipment, even the power grid. Therefore, islanding detection is the priority among priorities. Islanding detection is a precondition of two working modes switching for distributed generation. In this paper, a detailed description followed by the classification of the islanding detection techniques has been made based on features, such as detection time, size of non-detection zone, power quality disturbances, system cost and operation under multiple distributed generation units. The merits and demerits of islanding detection methods are analyzed and summarized in this paper. In this manner, the greatest detection outcome can be achieved by exploiting the merits of each method. This paper is aimed to serve as a convenient reference and guidance value for deciding the islanding detection method for future islanding users in distributed generation system.

Smart grid is a cyber-physical system containing two heterogeneous networks including power and cyber network (control, monitoring, and protection systems). Without the cyber network, the power grid cannot work effectively and reliably. The reliability indices of smart grid can obtain accurate results if the cyber-power interdependencies (CPIs) are taken into account. In this paper, a novel analytical method is proposed to evaluate the reliability indices. The eventual cyber impacts on reliability of smart grid are analyzed based on the distributed generation (DG) penetration. Because of the important factors such as CPIs effects in presence of DGs and investigating in probabilistic condition, they are included in the proposed method. Reliability assessment of smart grid using renewable DGs besides conventional ones is one of the novelties of this paper. The method is applied to a realistic distribution network of Hormozgan Regional Electrical Company (HREC). The test results indicate that reliability evaluation without considering the CPIs is along with significant inaccuracies. Moreover, results demonstrate the reliability variation, as a function of the DG penetration level, presenting a rather monastically increasing characteristic which saturates after a certain DG penetration level. Furthermore, to improve reliability indices, it is vital to consider cyber effects in presence of DGs in different scenarios especially with existence of renewable DGs having probabilistic nature.

Technical and economic impacts of active management on distribution network

More and more distributed generation (DG) and energy storage (ES) devices are being connected to the distribution network (DN). They have the potential of maintaining a stable supply load during failure periods when using islanding operations. Therefore, DG and ES have capacity value, i.e., improving the power supply capability of the system. However, there are strong fluctuations in DG outputs, and the operations of ES devices have sequential characteristics. The same capacity of DG has different load-bearing capabilities compared to conventional thermal or hydroelectric units. This paper proposes a method for evaluation of power supply capability improvement in DNs. First, the temporal fluctuation in both power source and load demand during fault periods is considered. A DN island partition model considering the secondary power outage constraint is established. Then, a modified genetic algorithm is designed. The complex island partition model is solved to achieve accurate power supply reliability evaluation. And the incremental power supply capability associated to DG and ES devices is calculated. Finally, a case study is conducted on the PG&E 69-bus system to verify the effectiveness of the proposed method. It is found that with a 20% configuration ratio of ES devices, the power supply capability improvement brought about by 6 MW DG can reach about 773 kW.

The transition from fossil fuel-based generation toward renewable-based distributed generation (DG) has motivated system operators to determine the maximum DG capacity that can be safely accommodated in distribution systems. Active network management (ANM) schemes can mitigate the technical issues arising from high DG penetration and, therefore, increase DG capacity in a distribution network. This paper develops an optimal power flow (OPF)-based DG capacity assessment approach that respects the local standard ANM schemes, particularly to control the grid-connected inverters. First, we investigate the effectiveness of different standard local ANM schemes on improving the DG capacity of distribution systems. We then compare them with the central approach that assumes a live, two-way communication infrastructure as an upper limit benchmark for the DG capacity. We use the proposed model to obtain the DG capacity of the three-phase IEEE 37-node and IEEE 906-node networks in the presence of different local and central ANM schemes. Our simulations show that real power based local control strategies are more effective than their reactive power based counterparts in improving the DG capacity of both networks. Additionally, in the voltage-constrained test system IEEE 906-node, the central approach enhances the network's DG capacity at least 25 % more than local approaches.

This paper investigates the impacts of circuit breaker performance on voltage instability corrective actions for power systems with distributed generations (DGs) under contingencies, and proposes a new computer network-aided strategy for stability improvement. This strategy aims to save a distribution system from imminent voltage collapse due to contingencies occurring in subtransmission system, distribution system, or DG systems from renewable energy resources. The proposed strategy is based on an instability corrective action using an optimal load shedding operation and a stability enhancive action using available capacity of DGs. This paper shows the use of state-of-the-art digital signal processing technology for determination of correct stability controls, and the application of modern computer networking technology for monitoring of distribution system operating states and transmitting of data and stability control commands. This paper presents a new two-layer fault-tolerant architecture designed for network-aided voltage instability corrective actions.

Every year the popularity of the net metering system, for small producers of energy in the Brazilian electric system is increasing fast driven by the Normative Resolutions REN 482/2012 and REN 687/2015 of the National Electricity Agency (ANEEL). These resolutions can encourage investment in the sector and create the growth of renewable energies in the energy matrix through distributed generation (DG). The presence of DG at the distribution systems network can create reverse flows that could increase system power losses when the generation is higher than the load. On de other hand, energy storage systems (ESS), that are present in the intermittent energy sources, like solar generation, are being presented as a solution to various hitches and operating reliability in electric power systems. ESS and its management represent an important factor for efficiency and excellence in electric power systems. Hence, this paper proposes the verification of the operational impacts of DG that uses inverters as interface with the distribution grid from the perspective of reactive injection and in the management of Battery storage systems (BESS) in order to verify the behavior of Power Factor (PF) in the distribution networks and analyze its behavior toward losses, power dispatch and charging at the generation distributed.

The use of Distributed Generators (DGs) in distribution system has increased at fast pace in recent times. These DGs can work both as grid connected or standalone mode. Thus when it comes to DG placement, getting the optimal location for its placement and the optimal sizing becomes very important. In this paper, finding the optimal location and optimal size of DGs is dealt keeping active power loss as the objective, considering different load models. A novel method called Backtracking Search Optimization Algorithm is used to find the most significant positions for DG placement. DGs supplying both active and reactive power have been studied. Case studies have been done about the effect of 1, 2 or 3 DGs on the IEEE 69 bus test system for DGs operating at 0.85 pf. on different load models.

The reasonable regulation strategy of distributed generation (DG), which is a key link in the operation of distribution network (DN), can improve the penetration of new energy, reduce voltage fluctuations and network losses effectively. Therefore, the control model of DG should be fully considered in the planning stage to maximize its complementary ability. In this paper, a bi-level distribution network planning model with DG control model is established, aiming at economy and stability. In the upper level, the capacity and position of DG are determined with the minimum annual comprehensive cost as the objective. The lower level calculates the DG control strategy when the voltage deviation is minimized, and uses particle swarm optimization to solve the model hierarchically to obtain the DG installation position and capacity with the optimal annual cost and voltage fluctuation. Case study on IEEE 33-bus system verifies that the model can improve the collaborative control capability of source and network effectively and make DG regulation work.

Recent developments in the electric power and problems arising from construction and maintenance of large power plants have raised a great deal of interest in distributed power generation (DG). Distributed generation units due to specifications, technology and location network connectivity can improve system and load point reliability indices. In this paper, the placement and sizing of Distributed Generators (DG) in distribution networks are determined using optimization. The objective is to improve the reliability indices. The placement and size of DGs are optimized using a Genetic Algorithm (GA). To evaluate the proposed algorithm, the IEEE 34 buses distribution feeder,is used. The results illustrate the efficiency of the proposed method.)

The reliability of power supply to consumers is the main factor that is to be considered while designing, planning and operation of a distribution network. This problem can be solved by incorporating distributed generation (DG) at the consumer side itself. In order to enhance service availability, power quality, reliability, and loss reduction, DG is positioned optimally at the consumer end within the system. The optimal DG location and size is to be calculated in such a way that the total loss in the system should be minimal and cost savings should be maximal. In this study, for the investigation of effects of DG on reliability of distribution system, a practical 11 KV feeder with 41-bus, was employed. The selected practical feeder is modelled using the power world simulator (PWS) software and reliability of the system is verified by calculating various reliability indices such as system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), customer average interruption duration index (CAIDI), average system utility index (ASUI) and average service availability index (ASAI). After applying proposed loss sensitivity factor (LSF) method, the active and reactive power loss reduction are 41.30 % and 38.64 % respectively, least bus voltage is enhanced to 0.9405 pu from 0.8978 pu and the reliability indices are also improved.