Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode

Marzband, Mousa; Ghadimi, Majid; Sumper, Andreas; Domínguez‐García, José Luis

doi:10.1016/j.apenergy.2014.04.056

Cited by 214 publications

(126 citation statements)

References 34 publications

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“…The day-ahead scheduling is employed to address the long-term influence, and the real-time scheduling is applied to address the short-term influence. Both the day-ahead and the real-time scheduling have drawn much attention in recent years [16,17]. The approaches of model predictive control (MPC), fuzzy logic control (FLC) [18], dynamic programming [19] and mixed-integer nonlinear programming (MINLP) [20] have been used to perform real-time scheduling.…”

Section: Introductionmentioning

confidence: 99%

Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

et al. 2015

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Abstract:Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC) method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long-and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.

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Section: Introductionmentioning

confidence: 99%

Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

et al. 2015

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“…Since it is likely to have shortage or excess in power generation anytime during the daily operation of an islanded H-MG, the energy management system (EMS) design should consider this specification. It is also desired for the EMS design to adapt and compensate itself in real-time to any changes in the types and capacity of the generation and storage assets quickly, without any modification in the EMS, in addition, maximizing the operational efficiency (equivalently minimizing the cost of operation), minimizing the emission [5], maximizing the lifetime of assets [6][7][8][9], increasing the reliability of inter-operatability [10,11] or a combination of the above for a multi-objective type EMS [12][13][14][15]. The proposed supervisory controllers for the safe and optimal H-MGs operation are categorized as: central energy management system (CEMS) and distributed energy management system (DEMS), where certain advantages and drawbacks have been comparatively reviewed in [12,16].…”

Section: Introductionmentioning

confidence: 99%

A real-time evaluation of energy management systems for smart hybrid home Microgrids

Marzband

Ghazimirsaeid

Uppal

et al. 2017

Electric Power Systems Research

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131

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Real-time energy management within the concepts of home Microgrids (H-MG) systems is crucial for H-MG operational reliability and safe functionality, regardless of simultaneously emanated variations in generation and load demand transients. In this paper, an experimental design and validation of a real-time mutli-period artificial bee colony (MABC) topology type central energy management system (CEMS) for H-MGs in islanding mode is proposed to maximize operational efficiency and minimize operational cost of the H-MG with full degree of freedom in automatically adapt the management problem under variations in the generation and storage resources in real-time as well, suitable for different size and types of generation resources and storage devices with plug-and-play structure, is presented. A self-adapting CEMS offers a control box capability of adapting and optimally operating with any H-MGs structure and integrated types of generation and storage technologies, using a two-way communication between each asset, being a unique inherent feature. This CEMS framework utilizes feature like day-ahead scheduling (DAS) integrated with real-time scheduling (RTS) units, and local energy market (LEM) structure based on Single Side Auction (SSA) to regulate the price of energy in real-time. The proposed system operates based on the data parameterization such as: the available power from renewable energy resources, the amount of non-responsive load demand, and the wholesale offers from generation units and time-wise scheduling for a range of integrated generation and demand units. Experimental validation shows the effectiveness of our proposed EMS with minimum cost margins and plugand-play capabilitities for a H-MG in real-time islanding mode that can be envisioned for hybrid multi-functional smart grid supply chain energy systems with a revolutionary architectures. The better performance of the proposed algorithm is shown in comparison with the mixed integer non-linear programming (MINLP) algorithm, and its effectiveness is experimentally validated over a microgrid test bed. The obtained results show convergence speed increase and the remarkable improvement of efficiency and accuracy under different condition.

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“…The former has a large storage capacity and short life cycle, while the latter has a large power density, fast response and long life cycle. In recent years, energy-type energy storage devices have been commonly used in standalone microgrids including renewable energy generation [6][7][8][9][10], but the face the challenge of large fluctuation in charge-discharge power, and even the challenge of frequent switching between charge-discharge status. This will accelerate the life loss of energy-type energy storage systems which are sensitive to the charge-discharge process, and severely degrade their performance.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Analysis of a Hybrid Energy Storage System in a Small-Scale Standalone Microgrid for Remote Area Power Supply (RAPS)

Xie

Yang

2015

Energies

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Abstract:The analysis and application of hybrid energy storage systems (HESSs) in small-scale standalone microgrids for remote area power supply (RAPS) has received extensive attention. This application mode has its own characteristics which must be considered but have not been considered in the existing research. To reflect the common satisfaction of load demands and maximize the utilization of renewable energy in a standalone microgrid, a new index named effective rate of energy storage system (ESS) is proposed. To reflect the true work state of supercapacitor ESS (SC-ESS), the second-level data of field measurements is used in calculation and analysis. To further enhance the operational performance of the HESS, a coordinated control strategy based on state cooperation is adopted. To get a more reasonable and more credible HESS optimization model, the comparison of existing models and proposed model with different considerations on cost and life is provided. In addition, a comparative analysis of technical and economic characteristics improvements is presented for different ESS application schemes in practical projects.

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Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode

Cited by 214 publications

References 34 publications

Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

A real-time evaluation of energy management systems for smart hybrid home Microgrids

Optimization and Analysis of a Hybrid Energy Storage System in a Small-Scale Standalone Microgrid for Remote Area Power Supply (RAPS)

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