This paper presents both an extensive literature review and a qualitative and quantitative study conducted on nearly 200 publications from the last six years (based on international experience and a top-down analysis framework with five classification levels) to establish the main trends in the field of centralized energy management systems (EMS) for microgrids. No systematic trend analyses have been observed in this field in previous literature reviews. EMS attributes for several features such as objective functions, resolution techniques, operating models, integration of uncertainties, optimization horizons, and modeling detail levels are considered for main trend identification. The main contribution of this study is the identification of four specific existing research trends: (i) dealing with uncertainties (comprises 33% of the references), (ii) multi-objective strategy (29%), (iii) traditional paradigm (21%), and (iv) P-Q challenge (17%). Each trend is described and analyzed based on the main drive of these separate research fields. The key challenges and the way to cope with them are described based on the rationality of each trend, the results of previous reviews, and the previous experience of the authors. Overall, finding these main trends, together with a complete paper database and their features, serve as a useful outcome for a better understanding of the current research-specific challenges, opportunities, potential barriers, and open questions regarding the creation of future centralized EMS developments. The traditional numerical analysis is insufficient to identify research trends. Therefore, the need of further analyses based on the clustering approach is emphasized.
Abstract:The development of a proper protection system is essential for the secure and reliable operation of microgrids. In this paper, a novel adaptive protection system for microgrids is presented. The protection scheme is based on a protective device that includes two directional elements which are operating in an interleaved manner, namely overcurrent and undervoltage elements. The proposed protection scheme can be implemented in microprocessor-based relays. To define the settings of the protective device, a robust programming approach was proposed considering a finite set of fault scenarios. The scenarios are generated based on the predictions about the available energy and the demand. For each decision step, a robust optimization problem is solved online, which is based on forecasting with a confidence band to represent the uncertainty. The system is tested and compared using real data sets from an existing microgrid in northern Chile. To assess the performance of the proposed protection system, fault scenarios not considered in the optimization were taken into account. The results obtained show that the proposed protective device is able to manage those failure scenarios, as well as those included in the tuning of the settings. Practical considerations are also discussed.
The increasing integration of renewable energy sources into current power systems has posed the challenge of adequately representing the statistical properties associated with their variable power generation. In this paper, a novel procedure is proposed to select a proper synthetic time series generation model for renewable energy sources to analyze power system problems. The procedure takes advantage of the objective of the specific analysis to be performed and the statistical characteristics of the available time series. The aim is to determine the suitable model to be used for generating synthetic time series of renewable energy sources. A set of indicators is proposed to verify that the statistical properties of synthetic time series fit the statistical properties of the original data. The proposal can be integrated into systematic tools available for data analysis without compromising the representation of the statistical properties of the original time series. The procedure is tested using real data from the New Zealand power system in a midterm analysis on integrating wind power plants into the power system. The results show that the proposed procedure reduces the error obtained in analyzing power systems compared with reference models.
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