Optimal operation of distributed generations in micro‐grids under uncertainties in load and renewable power generation using heuristic algorithm

Abstract:A microgrid (MG) is a small-scale version of the power system which makes possible the integration of renewable resources as well as achieving maximum demand side management (DSM) utilization. The future power system will be faced with severe uncertainties owing to penetration of renewable resources. Consequently, the uncertainty assessment of system performance is essential. The conventional energy scheduling in an MG may not be suitable for active distribution networks. Hence, this study focuses on the probabilistic analysis of optimal power dispatch considering economic aspects in a multi-carrier networked microgrid. The aim is to study the impact of uncertain behavior of loads, renewable resources, and electricity market on the optimal management of a multi-carrier networked microgrid. Furthermore, a novel time-based demand side management is proposed in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. The optimization model is formulated as a mixed integer nonlinear program (MINLP) and is solved using MATLAB and GAMS software. Results show that the energy sharing capability between MCMGs and MCMGs and the main grids as well as utilization of demand side management can decrease operating costs for smart distribution grids.

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“…In this paper, the solar radiation PDF is modeled through a beta distribution [46]. The beta distribution function is represented as:…”

Section: Modeling Of Renewable Generationmentioning

confidence: 99%

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

2017

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“…Accurate STLF predictions play a vital role in electrical department load dispatch, unit commitment, and electricity market trading [1]. With the permeation of renewable resources in grids and the technological innovation of electric vehicles, load components become more complex and make STLF difficult; therefore, strict requirements of stability and accuracy are needed [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Modular Predictor for Day-Ahead Load Forecasting and Feature Selection for Different Hours

Lin

et al. 2018

Energies

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Abstract:To improve the accuracy of the day-ahead load forecasting predictions of a single model, a novel modular parallel forecasting model with feature selection was proposed. First, load features were extracted from a historic load with a horizon from the previous 24 h to the previous 168 h considering the calendar feature. Second, a feature selection combined with a predictor process was carried out to select the optimal feature for building a reliable predictor with respect to each hour. The final modular model consisted of 24 predictors with a respective optimal feature subset for day-ahead load forecasting. New England and Singapore load data were used to evaluate the effectiveness of the proposed method. The results indicated that the accuracy of the proposed modular model was higher than that of the traditional method. Furthermore, conducting a feature selection step when building a predictor improved the accuracy of load forecasting.

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“…Solar based distributed generator (SDG) sources can reduce power loss and improve the quality of service with better voltage regulation. The recent growth of distribution technology provides an effective way for the use of renewable energy in the micro grid [1,2]. The distribution system defined by the Federal Energy Regulatory Commission is subject to reliability standards established through the North American Electric Reliability Corporation (NERC) as the Enforcement and Removal Operations (ERO) of United States of America (USA) [3].…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing and Placement of Solar Cell Distributed Generator Suitable for Integrated Power System Environment

2018

Teh. vjesn.

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A novel fuzzified Clustered Gravitational Search Algorithm (CGSA) has been employed for solving multi-objective problem formulated for solar based distributed generation. Optimal sizing and placement of solar distributed generation is considered. High solar penetration can lead to high-risk level in power system reliability. In order to maintain the system reliability, solar power dispatch is usually restricted based on the reliability level of the system. Two conflicting objective functions such as power loss and reliability level of the system are also considered for solving optimal placement of solar distributed generation (SDG). Binary coded CGSA is employed for solving optimal placement of SDG and sizing is determined using real coded CGSA. The fuzzy membership function for each objective is designed and multi-objective optimal placement problem has been presented. The proposed method is validated on IEEE standard 69-bus radial distribution networks. The efficiency of the proposed optimization technique is validated by comparing the results with other results available in the existing articles.

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Optimal operation of distributed generations in micro‐grids under uncertainties in load and renewable power generation using heuristic algorithm

Cited by 168 publications

References 25 publications

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

Modular Predictor for Day-Ahead Load Forecasting and Feature Selection for Different Hours

Optimal Sizing and Placement of Solar Cell Distributed Generator Suitable for Integrated Power System Environment

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