Energy management system for enhanced resiliency of microgrids during islanded operation

Balasubramaniam, Karthikeyan; Saraf, Parimal; Hadidi, Ramtin; Makram, Elham B.

doi:10.1016/j.epsr.2016.04.006

Cited by 116 publications

(77 citation statements)

References 14 publications

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“…In Equation (8), u g,t is a binary variable and it shows the commitment status of gth CDG at time interval t. If CDG is committed to operate at time t, this binary variable takes the value of 1 and 0 otherwise. Power generation limits of gth CDG are given by Equation (8). Equation (9) shows the start-up indicator (y g,t ) for gth CDG and Equation (10) shows the shutdown indicator (z g,t ).…”

Section: Constraints For Controllable Generatorsmentioning

confidence: 99%

“…If the event is cleared, the EMS will switch back to normal/resilient operation mode depending on its input values. Generally, a scheduling horizon of 1 day is considered for scheduling of microgrids [6,8,21]. Therefore, in this study also, simulations are conducted for one day.…”

Section: Scheduling Horizonsmentioning

confidence: 99%

“…The initial solution is revised via resiliency cuts to obtain zero mismatch. The decision between the feeding of lesser critical loads and storage of energy for future dispatches is considered by [8]. The objective of the research is to minimize the load-shedding amount following a disruption event.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids

2017

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Abstract:The resiliency of power systems can be enhanced during emergency situations by using microgrids, due to their capability to supply local loads. However, precise prediction of disturbance events is very difficult rather the occurrence probability can be expressed as, high, medium, or low, etc. Therefore, a fuzzy logic-based battery energy storage system (BESS) operation controller is proposed in this study. In addition to BESS state-of-charge and market price signals, event occurrence probability is taken as crisp input for the BESS operation controller. After assessing the membership levels of all the three inputs, BESS operation controller decides the operation mode (subservient or resilient) of BESS units. In subservient mode, BESS is fully controlled by an energy management system (EMS) while in the case of resilient mode, the EMS follows the commands of the BESS operation controller for scheduling BESS units. Therefore, the proposed hybrid microgrid model can operate in normal, resilient, and emergency modes with the respective objective functions and scheduling horizons. Due to the consideration of resilient mode, load curtailment can be reduced during emergency operation periods. Numerical simulations have demonstrated the effectiveness of the proposed strategy for enhancing the resiliency of hybrid microgrids.

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Section: Constraints For Controllable Generatorsmentioning

confidence: 99%

Section: Scheduling Horizonsmentioning

confidence: 99%

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Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids

2017

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“…While smart grids are known as the future of power systems, home Microgrids (H-MGs) are known as the vital technology to deliver the functional blocks of smart grid on a local scale [1,2]. Although the idea of H-MGs seems to be similar to the various areas of operation in the traditional power system, they are different in which they have to be fully capable of autonomous operation in islanded mode [3,4].…”

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

132

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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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“…According to the party that initiates the demand reduction action, market-driven actions or renewable based microgrids considering operation cost is presented in [20,21] and the study in [22,23] proposed a stochastic non-linear approach for energy optimization management. Recently, the model predictive control (MPC) strategy has drawn considerable attention of power system researchers due to several potential benefits [24,25]: (1) it considers future behavior of the system, receding horizon strategy, which can be attractive for systems with uncertainties; (2) by providing a feedback mechanism, the system can be more robust against uncertain parameters; and (3) it can easily meet the power system constraints.…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

et al. 2018

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Due to the recent developments in the practical implementation of remotely controlled switches (RCSs) in the smart distribution system infrastructure, distribution system operators face operational challenges in the hourly reconfigurable environment. This paper develops a stochastic Model Predictive Control (MPC) framework for operational scheduling of distribution systems with dynamic and adaptive hourly reconfiguration. The effect of coordinated integration of energy storage systems and demand response programs through hourly reconfiguration on the total costs (including cost of total loss, switching cost, cost of bilateral contract with power generation owners and responsive loads, and cost of exchanging power with the wholesale market) is investigated. A novel Switching Index (SI) based on the RCS ages and critical points in the network along with the maximum number of switching actions is introduced. Due to nonlinear nature of the problem and several existing binary variables, it is basically considered as a Mixed Integer Non-Linear Programming (MINLP) problem, which is transformed into a Mixed Integer Linear Programming (MILP) problem. The satisfactory performance of the proposed model is demonstrated through its application on a modified IEEE 33-bus distribution system.

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Energy management system for enhanced resiliency of microgrids during islanded operation

Cited by 116 publications

References 14 publications

Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids

Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids

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

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

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