Showing 4 results for Distributed Generation (dg)
Reza Noroozian , Mehrdad Abedi , Gevorg B. Gharehpetian , Seyed Hossein Hosseini ,
Volume 5, Issue 2 (6-2009)
Abstract
This paper presents the modeling and simulation of a proton exchange membrane fuel cell (PEMFC) generation system for off-grid and on-grid operation and configuration. A fuel cell DG system consists of a fuel cell power plant, a DC/DC converter and a DC/AC inverter. The dynamic model for fuel cell array and its power electronic interfacing are presented also a multi-input single output (MISO) DC/DC converter and its control scheme is proposed and analyzed. This DC/DC converter is capable of interfacing fuel cell arrays to the DC/AC inverter. Also the mathematical model of the inverter is obtained by using average technique. Then the novel control strategy of DC/AC inverter for different operating conditions is demonstrated. The simulation results show the effectiveness of the suggested control systems under both on-grid and off-grid operation modes.
A. Azghandi, S. M. Barakati, B. Wu,
Volume 14, Issue 4 (12-2018)
Abstract
A voltage source inverter (VSI) is widely used as an interface for distributed generation (DG) systems. However, high-power applications with increasing voltage levels require an extra power converter to reduce costs and complications. Thus, a current source inverter (CSI) is used. This study presents a precise phasor modeling and control details for a VSI-based system for DG and compares it with a CSI-based system. First, the dynamic characteristics of the system based on amplitude-phase transformation are investigated via small signal analysis in the synchronous reference frame. Moreover, the performance of the grid-connected system is determined by adopting the closed-loop control method based on the obtained dynamic model. The control strategies employ an outer active-power loop cascaded with an inner reactive-power loop, which the inner loop is a single-input single-output system without coupling terms. The sensitivity analysis of the linearized model indicates the dynamic features of the system. The simulation results for the different conditions confirm proposed model and design of the controller.
M. Sedighizadeh, S. M. M. Alavi, A. Mohammadpour,
Volume 16, Issue 3 (9-2020)
Abstract
Regarding the advances in technology and anxieties around high and growing prices of fossil fuels, government incentives increase to produce cleaner and sustainable energy through distributed generations. This makes trends in the using microgrids which consist of electric demands and different distributed generations and energy storage systems. The optimum operation of microgrids with considering demand-side management increases efficiency and reliability and maximize the advantages of using distributed generations. In this paper, the optimal operation scheduling and unit commitment of generation units installed in a microgrid are investigated. The microgrid consists of technologies based on natural gas that are microturbine and phosphoric acid fuel cell and technologies based on renewable energy, including wind turbine and photovoltaic unit along with battery energy storage system and plug-in electric vehicle commercial parking lot. The goal of the paper is to solve a multi-objective problem of maximizing revenues of microgrid operator and minimizing emissions. This paper uses an augmented epsilon constraint method for solving the multi-objective problem in a stochastic framework and also implements a fuzzy-based decision-maker for choosing the suitable optimal solution amid Pareto front solutions. This new model implements the three type of the price-based and incentive-based demand response program. It also considers the generation reserve in order to enhance the flexibility of operations. The presented model is tested on a microgrid and the results demonstrate the efficacy of the proposed model economically and environmentally compared to other methods.
M. Khajevand, A. Fakharian, M. Sedighizadeh,
Volume 16, Issue 3 (9-2020)
Abstract
Using distributed generations (DGs) with optimal scheduling and optimal distribution feeder reconfiguration (DFR) are two aspects that can improve efficiency as well as technical and economic features of microgrids (MGs). This work presents a stochastic copula scenario-based framework to jointly carry out optimal scheduling of DGs and DFR. This framework takes into account non-dispatchable and dispatchable DGs. In this paper, the dispatchable DG is a fuel cell unit and the non-dispatchable DGs with stochastic generation are wind turbines and photovoltaic cells. The uncertainties of wind turbine and photovoltaic generations, as well as electrical demand, are formulated by a copula-based method. The generation of scenarios is carried out by the scenario tree method and representative scenarios are nominated with scenario reduction techniques. To obtain a weighted solution among the various solutions made by several scenarios, the average stochastic output (ASO) index is used. The objective functions are minimization of the operational cost of the MG, minimization of active power loss, maximization of voltage stability index, and minimization of emissions. The best-compromised solution is then chosen by using the fuzzy technique. The capability of the proposed model is investigated on a 33-bus MG. The simulation results show the efficiency of the proposed model to optimize objective functions, while the constraints are satisfied.
