Real-time implementation &amp; evaluation of grid-connected microgrid energy management systems

Rangel, Carlos Mauricio; Mascarella, Diego; Joós, G.

doi:10.1109/epec.2016.7771717

Cited by 25 publications

(9 citation statements)

References 23 publications

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“…It is the initial cost of investment for the successful working of the micro-grid. Once the micro-grid capacity is updated, this value should be recalculated by considering the life of the equipment, return of investment, and other factors [15][16][17][18][19][20][21][22][23][24]: A similar application of this concept is beneficial in a situation when the power generation is still high and the demand decreases. In such a case, surplus energy can be utilized to charge the batteries.…”

Section: Capital Expenditure (Capex)mentioning

confidence: 99%

Design and Performance Investigation of a Pilot Micro-Grid in the Mediterranean: MCAST Case Study

Jately

Azzopardi

et al. 2021

Energies

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This paper discusses the simulation framework developed for an in-campus pilot micro-grid at MCAST, Malta, to enhance its efficiency and reliability. One year of real-time metered data were used to arrive at the load curves, categorize the loads as essential and non-essential ones, and decide the micro-grid domain within MCAST. The potential scenarios were modeled to observe the behavior of the present status of the micro-grid, with an increased photovoltaic (PV) generation capacity, by using an optimum battery storage system with a diesel generator of suitable capacity and finally integrating electric vehicles (EVs) to discuss the potential of vehicle to grid (V2G) operation modes. The existing building management system (BMS) of MCAST was interfaced within the micro-grid to introduce the geographic information system (GIS) and Building Information Modeling (BIM) for developing an intelligent 3D model of the micro-grid. The results of the simulation framework for various potential case scenarios were obtained in a MATLAB/Simulink environment to assess the performance of the micro-grid. Previously formulated key performance indices (KPIs) that describe the financial aspects of micro-grid operation and ecological benefits of the investigated micro-grid were evaluated. A sensitivity analysis of these KPIs shows encouraging results with the potential of cost-competitiveness.

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Section: Capital Expenditure (Capex)mentioning

confidence: 99%

Design and Performance Investigation of a Pilot Micro-Grid in the Mediterranean: MCAST Case Study

Jately

Azzopardi

et al. 2021

Energies

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“…For reactive power dispatch, the reactive power load, with the power factor of load set around 0.9, is shared among DERs in proportional to their remaining power capacity defined by (7). Since ESS serves as Vf reference, the reactive power losses in feeders will also be compensated by ESS, which makes its output power a little larger than the reference calculated from proportional power sharing.…”

Section: Daily-scale Test Of Dispatch Functionmentioning

confidence: 99%

“…A universal C-HIL platform for microgrid controller testing is proposed in [6], but only transition function is tested. In [7], an MGCS embedded with dispatch function is validated on a real-time testbed, but the optimization is still run offline. Similarly, dispatch and protection functions are presented in [8], but no comprehensive tests are conducted.…”

Section: Introductionmentioning

confidence: 99%

Design and Real-Time Implementation of a Centralized Microgrid Control System With Rule-Based Dispatch and Seamless Transition Function

Sun

Joós

Ali

et al. 2020

IEEE Trans. on Ind. Applicat.

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With reference to the newly released microgrid standards, design and real-time implementation of a centralized microgrid control system is presented in this article. In the grid-connected mode, the utility grid will provide the voltage and frequency reference at the point of connection. The assets within the microgrid will follow power command references provided by the control system. In the islanded mode, the energy storage system (ESS) can provide the voltage and frequency reference to all other generators. Based on the state-of-charge of the ESS, a rule-based dispatch is proposed, with priority given to diesel generator and then the storage in the middle state of charge range. To alleviate power fluctuations, meet smooth planned islanding requirement, and compensate for the feeder losses ignored in dispatch algorithm, a supplementary slackbus power control based on closed-loop feedback and first-order filter is proposed. The potential of the storage system in firming short-time power fluctuation and providing long-term load shifting capabilities is exploited. An emergency dispatch function for unplanned islanding considering the speed of response limitation of a diesel generator is also proposed. The proposed control strategy is implemented and tested on a controller hardware-in-the-loop test bench. It demonstrates the capability of the control system to reduce load shedding and renewable curtailment, and to implement power management at the point of interconnection. Index Terms-Controller hardware-in-the-loop (C-HIL) test, microgrid control system (MGCS), rule-based dispatch, slackbus power control, smooth transition, state of charge (SoC) management.

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“…Although, it is important to consider the fact that KPIs do have different impact on the overall MG performance. Following, the work of Rangel et al [12] is based upon less metrics and multi-objective functions per case for grid-connected MGs. Through hardware-in-the-loop (HIL) validation, the work focuses only on very specific metrics, such as the levelized cost of energy (LCoE); the total demand curtailed; the total purchased energy; the amount of fuel consumed; as well as power violations.…”

Section: Performance Indicators For Mg Assessmentmentioning

confidence: 99%

Towards a Holistic Microgrid Performance Framework and a Data-Driven Assessment Analysis

et al. 2020

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On becoming a commodity, Microgrids (MGs) have started gaining ground in various sizes (e.g., nanogrids, homegrids, etc.) and forms (e.g., local energy communities) leading an exponential growth in the respective sector. From demanding deployments such as military bases and hospitals, to tertiary and residential buildings and neighborhoods, MG systems exploit renewable and conventional generation assets, combined with various storage capabilities to deliver a completely new set of business opportunities and services in the context of the Smart Grid. As such systems involve economic, environmental and technical aspects, their performance is quite difficult to evaluate, since there are not any standards that cover all of these aspects, especially during operational stages. Towards allowing an holistic definition of a MG performance, for both design and operational stages, this paper first introduces a complete set of Key Performance Indicators to measure holistically the performance of a MG’s life cycle. Following, focusing on the MG’s day-to-day operation, a data-driven assessment is proposed, based on dynamic metrics, custom made reference models, and smart meter data, in order to be able to extract its operational performance. Two different algorithmic implementations (i.e., Dynamic Time Warping and t-distributed Stochastic Neighbor Embedding) are used to support the methodology proposed, while real-life data are used from a small scale MG to provide the desired proof-of-concept. Both algorithms seem to correctly identify days and periods of not optimal operation, hence presenting promising results for MG performance assessment, that could lead to a MG Performance Classification scheme.

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Real-time implementation & evaluation of grid-connected microgrid energy management systems

Cited by 25 publications

References 23 publications

Design and Performance Investigation of a Pilot Micro-Grid in the Mediterranean: MCAST Case Study

Design and Performance Investigation of a Pilot Micro-Grid in the Mediterranean: MCAST Case Study

Design and Real-Time Implementation of a Centralized Microgrid Control System With Rule-Based Dispatch and Seamless Transition Function

Towards a Holistic Microgrid Performance Framework and a Data-Driven Assessment Analysis

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