A Service Restoration Method for Active Distribution Network

AbstractFor a large scale of distributed generations being connected to the power distribution network, the traditional service restoration methods cannot meet the demand of the distributed generation's large access which facing significant challenges. Service restoration of active distribution network (ADN) is a multi-objective, multiple-constraint, and complex optimization problem. Considering the user priority level, the load amounts restored, the counts of switch operation, the network loss after the power restoration, and the operation of power sources, this article establishes a restoration model based on grid actual situation, which is more realistic for the ADN. As a different dimension of different objective, this article proposes the generalized model in order to compare those solutions conveniently, the paper uses genetic algorithm to get recovery scheme. Results of case study show that the proposed model is effective

Stability model integration for large scale solar photovoltaic system using Western electricity coordinating council model

Due to the increased demand for renewable energy, the interest in the large-scale solar photovoltaic (LSSPV) power plant has recently grown dramatically. However, when a large amount of electricity is produced from the LSSPV power plant to the grid interconnection, the system commonly experiences instability and thus disrupt the grid system in disturbance issues such as bus fault, line-to-line fault, three-phase fault, and tripping. This sudden disturbance occurrence is tended to interrupt the stability of the system from providing balanced electrical production within the electrical grid. A dynamics response from the simulation is used to study the stability and the behavior of the photovoltaic (PV) plant into the grid interconnection by developing 118 bus system. The observation of critical clearing time (CCT) duration shows that the result from the simulation where the duration takes less than t=15 s for the system to get back to its pre-fault condition in three-phase fault and tripping in a dynamic simulation to shows that the system reaches its stability been observed through the simulation result by using from user-specific models to generic models like those advocated by the Western electricity coordinating council (WECC) in power system simulator for engineering (PSSE) software

Restoration of an active MV distribution grid with a battery ESS: A real case study

In order to improve power system operation, Battery Energy Storage Systems (BESSs) have been installed in high voltage/medium voltage stations by Distribution System Operators (DSOs) around the world. Support for restoration of MV distribution networks after a blackout or HV interruption is among the possible new functionalities of BESSs. With the aim to improve quality of service, the present paper investigates whether a BESS, installed in the HV/MV substation, can improve the restoration process indicators of a distribution grid. As a case study, an actual active distribution network of e-distribuzione, the main Italian DSO, has been explored. The existing network is located in central Italy. It supplies two municipalities of approximately 10,000 inhabitants and includes renewable generation plants. Several configurations are considered, based on: the state of the grid at blackout time; the BESS state of charge; and the involvement of Dispersed Generation (DG) in the restoration process. Three restoration plans (RPs) have been defined, involving the BESS alone, or in coordination with DG. A MATLAB®/Simulink® program has been designed to simulate the restoration process in each configuration and restoration plan. The results show that the BESS improves restoration process quality indicators in different simulated configurations, allowing the operation in controlled island mode of parts of distribution grids, during interruptions or blackout conditions. The defined restoration plans set the priority and the sequence of controlled island operations of parts of the grid to ensure a safe and better restoration. In conclusion, the results demonstrate that a BESS can be a valuable element towards an improved restoration procedure

Real-Time Multifault Rush Repairing Strategy Based on Utility Theory and Multiagent System in Distribution Networks

The problem of multifault rush repair in distribution networks (DNs) is a multiobjective dynamic combinatorial problem with topology constraints. The problem consists of archiving an optimal faults’ allocation strategy to squads and an admissible multifault rush repairing strategy with coordinating switch operations. In this article, the utility theory is introduced to solve the first problem and a new discrete bacterial colony chemotaxis (DBCC) algorithm is proposed for the second problem to determine the optimal sequence for each squad to repair faults and the corresponding switch operations. The above solution is called the two-stage approach. Additionally, a double mathematical optimization model based on the fault level is proposed in the second stage to minimize the outage loss and total repairing time. The real-time adjustment multiagent system (RA-MAS) is proposed to provide facility to achieve online multifault rush repairing strategy in DNs when there are emergencies after natural disasters. The two-stage approach is illustrated with an example from a real urban distribution network and the simulation results show the effectiveness of the two-stage approach

Operación económica de dispositivos almacenadores de energía para disminución de pérdidas

This paper presents an algorithm for the opti­mal operation of distributed energy storage units from perspective of active potential lost. An exact model based on Lagrange relaxation is proposed. Simulation results on the IEEE 37-bus test feed­er demonstrate that energy storage system can be used for minimizing transmission losses in a distribution system by reshaping the load curve. The main contribution of this approach is the ob­jective function and the optimization algorithm, Lagrange multipliers are used for determining optimal placement and sizing of the energy stor­age units. A discussion about the impact of energy storage units on the distribution planning is also presented.Este artículo presenta un algoritmo para la ope­ración óptima de unidades de almacenamiento de energía (UDAE), desde la perspectiva de las pérdidas de potencia activa. Se propone un mode­lo exacto basado en relajación lagrangeana. Los resultados de simulación sobre el alimentador de distribución IEEE de 37 nodos demuestran que un sistema de almacenamiento de energía puede ser utilizado para minimizar las pérdidas en un sis­tema de distribución, a través de la modificación de la curva de carga. La principal contribución de este enfoque consiste en el tratamiento de la función objetivo y el algoritmo de optimización. Los multiplicadores de Lagrange son usados para determinar la ubicación y el dimensionamiento óptimo de las unidades de almacenamiento. Se presenta además una discusión sobre el impacto de las UDAE en el planeamiento de la red de dis­tribución

A novel battery network modelling using constraint differential evolution algorithm optimisation

The use of battery storage devices has been advocated as one of the main ways of improving the power quality and reliability of the power system, including minimisation of energy imbalance and reduction of peak demand. Lowering peak demand to reduce the use of carbon-intensive fuels and the number of expensive peaking plant generators is thus of major importance. Self-adaptive control methods for individual batteries have been developed to reduce the peak demand. However, these self-adaptive control algorithms of are not very efficient without sharing the energy among different batteries. This paper proposes a novel battery network system with optimal management of energy between batteries. An optimal management strategy has been implemented using a population-based constraint differential evolution algorithm. Taking advantage of this strategy the battery network model can remove more peak areas of forecasted demand data compared to the self-adaptive control algorithm developed for the New York City study case

Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters

postprin

A novel model for smart grid as a network of networks with hybrid composite cross layer description

Rad predstavlja pokušaj izrade prihvatljivog modela automatizirane energetske mreže kao spleta mreža s mogućnošću procjenjivanja događanja pri pojavi bilo kojeg obilježja te energetske mreže. U tu su svrhu primijenjeni zakoni za modeliranje mreže kako bi se postigla odgovarajuća struktura za model, korištena je teorija automata za objašnjenje rada predloženog modela, a za definiranje odgovarajućeg matematičkog opisa upotrebljena je teorija hibridne funkcije. Evaluiranjem kooperativnih procesa energetske mreže i određivanjem uloge specijalnih karakteristika mreže u tim procesima, izabrana je hijerarskijska struktura od šest slojeva. Svaki se sloj te strukture promatra kao automat i njegova se autonomna performansa opisuje hibridnom funkcijom, matematički. Sastav tih šest hibridnih funkcija uvodi u završnu formulaciju modela. Za provjeru prikladnosti predloženog modela primijenjen je mehanizam inteligentne strategije upravljanja opterećenjem.This paper is an effort towards constructing a comprehensive model for the smart grid as a network of networks with the ability of evaluating events in presence of every smart grid feature. To this end, the network modelling laws are employed to attain a proper structure for the model, the automata theory is used to explain the performance of the proposed model, and the hybrid function theory is utilized to define an appropriate mathematical description for it. By evaluating the smart grid cooperative processes, and determining the role of special smart grid features in these processes, a six-layered hierarchical structure is chosen. Each layer of this structure is considered as an automaton and its autonomous performance is described by a hybrid function, mathematically. The composition of these six hybrid functions introduces the final formulation of the model. To verify the suitability of the proposed model the mechanism of the smart load management strategy is captured