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Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids’ EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.
Hossein Shayeghi; Elnaz Shahryari; Mohammad Moradzadeh; Pierluigi Siano. A Survey on Microgrid Energy Management Considering Flexible Energy Sources. Energies 2019, 12, 2156 .
AMA StyleHossein Shayeghi, Elnaz Shahryari, Mohammad Moradzadeh, Pierluigi Siano. A Survey on Microgrid Energy Management Considering Flexible Energy Sources. Energies. 2019; 12 (11):2156.
Chicago/Turabian StyleHossein Shayeghi; Elnaz Shahryari; Mohammad Moradzadeh; Pierluigi Siano. 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources." Energies 12, no. 11: 2156.
Utilization of renewable energy sources (RESs) has been increased due to economic-environmental aspects. However, uncertain nature of wind, solar power, market clearing price (MCP), and load complicates the energy management (EM) process of microgrids. This paper studies the EM problem of a grid-connected microgrid from the generating side's perspective. Firstly, the mathematical formulation of microgrid components including wind turbine (WT), photovoltaic (PV), micro turbine (MT), fuel cell (FC) and energy storage system (ESS) has been presented. An improved incentive-based demand response program (DRP) is applied to provide generation-consumption balance by modifying the load pattern. Considering the intra-day market in the formulation of EM is the first contribution of this paper. Furthermore, a new hybrid copula-scenario based uncertainty modeling technique has been presented in this paper. Formulating operational cost and environmental pollution as the objective functions, the proposed EM problem will be solved by multi-objective group search optimization (MOGSO) algorithm. Simulation results demonstrate the good performance of the proposed method in solving microgrid EM problem.
E. Shahryari; H. Shayeghi; B. Mohammadi-Ivatloo; M. Moradzadeh. A copula-based method to consider uncertainties for multi-objective energy management of microgrid in presence of demand response. Energy 2019, 175, 879 -890.
AMA StyleE. Shahryari, H. Shayeghi, B. Mohammadi-Ivatloo, M. Moradzadeh. A copula-based method to consider uncertainties for multi-objective energy management of microgrid in presence of demand response. Energy. 2019; 175 ():879-890.
Chicago/Turabian StyleE. Shahryari; H. Shayeghi; B. Mohammadi-Ivatloo; M. Moradzadeh. 2019. "A copula-based method to consider uncertainties for multi-objective energy management of microgrid in presence of demand response." Energy 175, no. : 879-890.
By advancement and vogue of smart grid technologies, there is a strong attitude toward utilizing different strategies for participating in demand response (DR) programs in electricity markets. DR programs can be classified into two main categories namely incentive-based programs (IBPs) and time-based rate programs (TBRPs). In this paper, an improved incentive-based DR (IBDR) model is proposed. In our proposed IBP, the concept of elasticity is improved where it depends not only on the electricity price, but also is a function of consumption hour and customer type. In this program, the incentive value which is paid to the participating consumers is not a fix value and relates to the peak intensity of each hour. The proposed IBP can participate in both of day-ahead and intra-day electricity markets. The property of considering intra-day market enables consumers to provide maximum DR if possible. The proposed model is implemented on peak load curve of Spanish electricity market and a 200-unit residential complex. Different scenarios are considered to show effectiveness of the proposed DR model from various aspects including peak shaving as well as economic indices.
E. Shahryari; H. Shayeghi; B. Mohammadi-Ivatloo; M. Moradzadeh. An improved incentive-based demand response program in day-ahead and intra-day electricity markets. Energy 2018, 155, 205 -214.
AMA StyleE. Shahryari, H. Shayeghi, B. Mohammadi-Ivatloo, M. Moradzadeh. An improved incentive-based demand response program in day-ahead and intra-day electricity markets. Energy. 2018; 155 ():205-214.
Chicago/Turabian StyleE. Shahryari; H. Shayeghi; B. Mohammadi-Ivatloo; M. Moradzadeh. 2018. "An improved incentive-based demand response program in day-ahead and intra-day electricity markets." Energy 155, no. : 205-214.
In this paper, an optimum and intelligent method is proposed for islanding detection using wavelet transform. The suggested relay is based on neural network (NN) in which different heuristic algorithms are used for training the NN. In the proposed method, the appropriate signals for detection procedure as well as mother wavelet are selected optimally, based on the mean square error (MSE) concept. Lately, the desired relay is trained by the optimally selected signals using four different algorithms and the optimum condition of the fault detector is identified. Simulation results approved that non detection zone (NDZ) has a significant reduction utilising the proposed intelligent technique. The contributions of the proposed method include presenting an appropriate signal selection method based on MSE, selecting optimum number of relay input signals using the proposed technique, fast training of intelligent relay by using least information, solving threshold selection problem and reduction of NDZ approximately to zero.
Elnaz Shahryari; Mehdi Nooshyar; Behrooz Sobhani. Combination of neural network and wavelet transform for islanding detection of distributed generation in a small-scale network. International Journal of Ambient Energy 2017, 40, 263 -273.
AMA StyleElnaz Shahryari, Mehdi Nooshyar, Behrooz Sobhani. Combination of neural network and wavelet transform for islanding detection of distributed generation in a small-scale network. International Journal of Ambient Energy. 2017; 40 (3):263-273.
Chicago/Turabian StyleElnaz Shahryari; Mehdi Nooshyar; Behrooz Sobhani. 2017. "Combination of neural network and wavelet transform for islanding detection of distributed generation in a small-scale network." International Journal of Ambient Energy 40, no. 3: 263-273.