Comprehensive Control for Microgrid Autonomous Operation With Demand Response

Nisar, Amira; Thomas, Mini S.

doi:10.1109/tsg.2016.2514483

Cited by 82 publications

(45 citation statements)

References 16 publications

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“…The microgrid can execute either in a grid-connected mode or in an islanded mode [17][18][19]. A pilot project of the Mae Sariang microgrid system model, which was created and funded by the United Nations Development Program (UNDP), is reported in [20][21][22][23].…”

Section: The Perspective Of Microgridmentioning

confidence: 99%

Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid

Tephiruk¹,

Kanokbannakorn²,

Kerdphol³

et al. 2018

Sustainability

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Abstract:In this study, the active and reactive power control of a battery energy storage system (BESS) using fuzzy logic control to maintain the voltage and frequency stability of the islanded Mae Sariang microgrid is presented. The main scope of the presented study is to cogitate the effectiveness of the BESS controller in view of fluctuations of frequency/voltage subjected to a disturbance occurring in the islanded microgrid. In the Mae Sariang microgrid system, the electricity is produced from two renewable energy resources (RESs), i.e., hydro and solar PV. The use of these clean energy sources has become a main problem, envisaging the output power uncertainties from RESs. Further, such power uncertainty raises power quality problems and leads to power failure. To overcome such problems, the proposed fuzzy logic control (FLC) approach is applied for the BESS controller to improve the stability of the islanded Mae Sariang microgrid. The proposed FLC is intended to provide the BESS with well-established attributes of dynamical response to disturbance, which is analyzed by a predictive model. The proposed FLC has been investigated and compared with the robust control method, which is analyzed by a mathematical model using the system identification technique. The modeling of the microgrid system with BESS is implemented and verified on the DIgSILENT PowerFactory software. The simulation result illustrates that both of the control approaches allow the dynamic stability of the microgrid and the maintenance of frequency and voltage within acceptable ranges. However, the proposed BESS fuzzy logic control is less prone to uncertainty than the BESS robust control. Furthermore, in the proposed BESS fuzzy logic control, the microgrid frequency and voltage rapidly return to their normal steady-state condition and the size of the BESS is smaller than the BESS robust control.

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Section: The Perspective Of Microgridmentioning

confidence: 99%

Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid

Tephiruk¹,

Kanokbannakorn²,

Kerdphol³

et al. 2018

Sustainability

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“…MG contains various micro sources (MS), load, energy storage (ES) and power electronic devices, which can achieve efficient use of renewable energy and ease the crisis of coal resources decreasing [2]. Plenty of renewable energy is uncontrollable, which needs microgrid to coordinate and manage.…”

Section: Introductionmentioning

confidence: 99%

Optimal Operation of Hybrid AC/DC Microgrid Including PV/WT/ES Considering Battery Charging and Discharging Times Constraint

Zheng¹,

Li²,

Sun³

et al. 2018

dtcse

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Abstract. Distributed generations have obvious features, including flexibility, randomness, intermittence and uncertainty. Energy storage can be equiped with such power supply, which can improve the new energy consumptive rate and ensure the reliability of power supply. The service life of the battery is mainly affected by its discharge depth, charge and discharge times and other factors. In this paper, the battery state of charge constraints, charge and discharge times constraint are taken into account, so as to decrease the battery charging and discharging frequency. Through an actual example, artificial bee colony is used to solve the objective function of the minimum operation cost of hybrid AC/DC microgrid including PV/WT/ES.

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“…Demand response technology can be used to optimize the operation of MG [11,12], frequency and connection line power [13,14], as well as support emergency fault [15,16]. DR can significantly improve the economy, reliability and flexibility of MG system [17]. With the improvement of the electric power market and the widespread application of the communication, the load optimization of the demand response has become the important factor that can not be ignored in the MG's planning and operation.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response

et al. 2016

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Abstract:In order to solve the influence of uncertain photovoltaic power (PV) on the stable operation of microgrid (MG), demand response (DR) and battery energy storage system (BESS) need to be introduced simultaneously into the operation optimal scheduling of PV-based microgrid (PV-MG). Therefore, it is of great significance for commercial investment decisions of PV-MG to consider the influence of DR on BESS optimal sizing. Under the peak-valley time-of-use (TOU) price, this paper builds cross-time DR models based on price elasticity matrix. Furthermore, through the introduction of DR and BESS into PV-MG scheduling optimization, the MG investment and benefit model is proposed. Considering the constraint condition such as co-ordination of supply and demand, electricity price elasticity and energy loss of storage system, the improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimal allocation model of the BESS with the target of maximum PV consumptive rate and annual net profits. The optimization method was applied to a PV-MG in Guangdong. Through the regulation and control effect of demand response and BESS on load distribution, the uncertainties PV power can be suppressed so as to improve the PV system consumptive level, which is of great guiding significance for BESS optimal sizing under this situation.Keywords: time-of-use (TOU) price; multi-period demand response (DR); battery energy storage system (BESS); photovoltaic consumptive rate; investment and benefit model; multi-objective optimization; non-dominated sorting genetic algorithm II (NSGA-II) algorithm

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Comprehensive Control for Microgrid Autonomous Operation With Demand Response

Cited by 82 publications

References 16 publications

Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid

Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid

Optimal Operation of Hybrid AC/DC Microgrid Including PV/WT/ES Considering Battery Charging and Discharging Times Constraint

Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response

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