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EN
In this paper, a control strategy for real-time operation of a master-slave controlled microgrid is developed. The basic idea of this control strategy is to schedule all dispatchable energy sources available into a microgrid to minimize its operational costs. Control actions are centrally evaluated by solving a two-stage optimization problem formulated to take place on two different time-scales: in the day-ahead and in the real-time. The first one provides a 24-hour plan in advance. It mainly draws up the active power levels that Distributed Energy Resources (DERs) should provide for each quarter hour of the next day by taking into account energy prices of the day-ahead energy market, the forecasted energy production of non-dispatchable renewables and loads. The real-time optimization problem updates the active power set-points of DERs in order to minimize as much as possible the real-time deviations between the actual power exchanged with the utility grid and its scheduled value. The effectiveness of the proposed methodology has been experimentally tested on an actual microgrid.
EN
In order to solve the problem of harmonic waves caused by battery energy storage (BES) and distributed generation (DG) inverters in an active distribution network, an intelligent optimal dispatching method based on a modified flower pollination algorithm (MFPA) is proposed. Firstly, the active distribution network dispatching model considering the power quality (PQ) problem caused by BES and DG is proposed. In this model, the objective function considers the additional network loss caused by a harmonic wave, as well as the constraints of the harmonic wave and voltage unbalance. Then, the MFPA is an improvement of a flower pollination algorithm (FPA). Because the MFPA has the characteristics of higher solution accuracy and better convergence than the FPA and it is not easy to fall into local optimal, the MFPA is used to solve the proposed model. Finally, simulation experiments are carried out on IEEE 37 bus and IEEE 123 bus systems, respectively. The experimental results show that this method can achieve satisfactory power quality while optimizing the total active power loss of the branch. The comparative experimental results show that the developed algorithm has better convergence than the FPA.
EN
The active distribution network (ADN) represents the future development of distribution networks, whether the islanding phenomenon occurs or not determines the control strategy adopted by the ADN. The best wavelet packet has a better time-frequency characteristic than traditional wavelet analysis in the different signal processing, because it can extract better and more information from the signal effectively. Based on wavelet packet energy and the neural network, the islanding phenomenon of the ADN can be detected. Firstly, the wavelet packet is used to decompose current and voltage signals of the public coupling point between the distributed photovoltaic (PV) system and power grid, and calculate the energy value of each decomposed frequency band. Secondly, the network is trained using the constructed energy characteristic matrix as a neural network learning sample. At last, in order to achieve the function of identification for islanding detection, lots of samples are trained in the neural network. Based on the actual circumstance of PV operation in the ADN, the MATLAB/SIMULINK simulation model of the ADN is established. After the simulation, there are good output results, which show that the method has the characteristics of high identification accuracy and strong generalization ability.
EN
This work presents an evaluation of the maximum capacity of renewable distributed generation that can be connected to active distribution networks to minimize the greenhouse gas emissions of the electric network. The study aimed at obtaining a methodology applicable to active distribution networks with characteristics of variable generation and demand in order to reduce greenhouse gas emissions from electric power generation activities. The formulation of the methodology is based on an optimal power flow model incorporating special system controls.
PL
W artykule rozważa się maksymalna pojemność odnwialnych źródeł energii rozproszonej która może być dołączona do aktywnej sieci rozdzielczej dla zminimalizowania emisji gazów cieplarnianych. Metoda polega na modelu optymalnego przepływu mocy uwzględniającym sterowanie systemem.
5
Content available remote Research on Solutions for Implement of Active Distribution Network
EN
Nowadays, distribution systems are facing the challenge to accommodate increasing quantities of Distributed Energy Resources (DERs), especially based on the intermittent renewable sources. So it is inevitable for distribution systems shifting from passive mode to active mode. This paper discusses some important issues for implementation of active distribution network (ADN) which is capable of allowing high penetration of renewable resources together with optimal operation by its flexible network, including planning for active distribution network considering renewable energy uncertainties, fully utilization of large scale intermittent renewable energy and active network management (ANM). Accordingly, some solutions are proposed to meet requirements of implement of active distribution network, basing on the issues aforementioned.
PL
W artykule omówiono zagadnienie implementacji aktywnej sieci przesyłowej, z naciskiem na wysoki poziom wykorzystania odnawialnych źródeł energii (OZE) poprzez zapewnienie elastyczności sieci. Przedstawiono rozwiązania dotyczące niestabilności generowanej przez OZE energii, optymalizacji pracy, maksymalnego wykorzystania generowanej energii oraz zarządzania siecią aktywną.
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