Optimal Dispatching of Distributed Generators and Storage Systems for MV Islanded Microgrids

Conti, S.; Nicolosi, R.; Rizzo, Santi Agatino; Zeineldin, H. H.

doi:10.1109/tpwrd.2012.2194514

Cited by 215 publications

(101 citation statements)

References 22 publications

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“…Classical controlled generators as diesel generators and new technologies as storage systems and controlled demands help to maintain the power balance. Energy management systems aims to maximise the profit of the microgrid operation (or minimise the cost) [2][3][4][5][6][7], minimise the emissions [8], or using several objectives [9]. These systems use several optimization algorithms as linear programming or heuristic methods [10][11][12] as particle swarm or evolutionary algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimal management of microgrid with renewable generation

Domínguez-Navarro¹,

Bernal-Agustín²,

Dufo-López³

et al. 2024

RE&PQJ

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Abstract. An energy management system to minimize the operation cost of a microgrid is presented in this work. The microgrid is composed of the technologies more used as renewable energies and storage systems, as well as active consumers which demand depends on price. The proposed model is based on linear programming with the operating cost as the objective function and the operating limits as constraints. The model has two phases. The first phase does the optimal dispatch of generating units in function of the forecasting demand and the offers made by generators. The second phase minimizes the differences between the planning values obtained in the first phase and the real data, because there are differences as consequence of the uncertainties of renewable energies and the consumers' behaviour.

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Section: Introductionmentioning

confidence: 99%

Optimal management of microgrid with renewable generation

Domínguez-Navarro¹,

Bernal-Agustín²,

Dufo-López³

et al. 2024

RE&PQJ

View full text Add to dashboard Cite

show abstract

“…In [13], the authors present an optimization algorithm to minimize the total cost of buying power from multiple generations under the microgrid framework. In [14], an optimization procedure is developed to make a schedule for the distributed generators and the storage in the microgrid to minimize the operating cost and the pollutant emission. For multiple interconnected microgrids, the authors in [15] propose a pricing mechanism based on the potential game theory to study the anticipated benefits in an open market.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling of Microgrid with Multiple Distributed Resources Using Interval Optimization

et al. 2017

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Abstract:In this paper, an optimal day-ahead scheduling problem is studied for a microgrid with multiple distributed resources. For the sake of coping with the prediction uncertainties of renewable energies and loads and taking advantage of the time-of-use price for buying/selling electricity, an interval-based optimization model for maximum profits is developed. To reduce the computational complexity in solving the model, the possibility degree comparison between an interval and a real number is used to convert the interval constraints into the general ones; meanwhile, some slack variables and complementary conditions are introduced to eliminate the absolute-value operation. Unlike the stochastic optimization, the interval optimization only needs the upper-lower bounds of the uncertain variables instead of their probability distribution functions, which is beneficial to the practical application. Furthermore, the possible profit interval and the expected optimal profit can be determined by solving the optimization model. Numerical simulations are performed on a microgrid system modified from the benchmark low voltage network in the European Union project "Microgrid", and the results demonstrate the effectiveness of the proposed method.

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“…It became active networks that support more dynamic energy flows with real-time management. Information technology and power electronics have facilitated the control of these new active networks in order to withstand the increasing number of DG units connected at the low and medium voltage level of distribution networks [3].…”

Section: Introductionmentioning

confidence: 99%

Distributed Generation Islanding Effect on Distribution Networks and End User Loads Using the Load Sharing Islanding Method

et al. 2016

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Abstract:In this paper a realistic medium voltage (MV) network with four different distributed generation technologies (diesel, gas, hydro and wind) along with their excitation and governor control systems is modelled and simulated. Moreover, an exponential model was used to represent the loads in the network. The dynamic and steady state behavior of the four distributed generation technologies was investigated during grid-connected operation and two transition modes to the islanding situation, planned and unplanned. This study aims to address the feasibility of planned islanding operation and to investigate the effect of unplanned islanding. The load sharing islanding method has been used for controlling the distributed generation units during grid-connected and islanding operation. The simulation results were validated through various case studies and have shown that properly planned islanding transition could provide support to critical loads at the event of utility outages. However, a reliable protection scheme would be required to mitigate the adverse effect of unplanned islanding as all unplanned sub-cases returned severe negative results.

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Optimal Dispatching of Distributed Generators and Storage Systems for MV Islanded Microgrids

Cited by 215 publications

References 22 publications

Optimal management of microgrid with renewable generation

Optimal management of microgrid with renewable generation

Optimal Scheduling of Microgrid with Multiple Distributed Resources Using Interval Optimization

Distributed Generation Islanding Effect on Distribution Networks and End User Loads Using the Load Sharing Islanding Method

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