A cooperative control for the reserve management of isolated microgrids

Cagnano, Alessia; Bugliari, A. Caldarulo; Tuglie, E. De

doi:10.1016/j.apenergy.2018.02.142

Cited by 52 publications

(21 citation statements)

References 41 publications

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“…The safe, reliable operation of the campus MG is of utmost importance, which could be successfully achieved with the reserve margins of the ESS. SOC have a significant influence on the reserve power of the ESSs [44]. Thus, an additional 5% reserve margin was taken into account in the first stage scheduling, considering that the maximum and minimum SOC levels were set to be 20% and 80%, respectively.…”

Section: Implementation Resultsmentioning

confidence: 99%

Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid

Jeong

Shin

et al. 2019

Energies

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Optimal operation scheduling of energy storage systems (ESSs) has been considered as an effective way to cope with uncertainties arising in modern grid operation such as the inherent intermittency of the renewable energy sources (RESs) and load variations. This paper proposes a scheduling algorithm where ESS power inputs are optimally determined to minimize the microgrid (MG) operation cost. The proposed algorithm consists of two stages. In the first stage, hourly schedules during a day are optimized one day in advance with the objective of minimizing the operating cost. In the second stage, the optimal schedule obtained from the first stage is repeatedly updated every 5 min during the day of operation to compensate for the uncertainties in load demand and RES output power. The ESS model is developed considering operating efficiencies and then incorporated in mixed integer linear programming (MILP). Penalty functions are also considered to acquire feasible optimal solutions even under large forecasting errors in RES generation and load variation. The proposed algorithm is verified in a campus MG, implemented using ESSs and photovoltaic (PV) arrays. The field test results are obtained using open-source software and then compared with those acquired using commercial software.

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Section: Implementation Resultsmentioning

confidence: 99%

Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid

Jeong

Shin

et al. 2019

Energies

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“…According to (20), the transfer function of the disturbance is given by G(s) = b T (sI − J) −1 b. Figure 8 shows a Bode diagram of G(s) when L 1 = 2, 3, 4, 5, and 6 mH.…”

Section: Transfer Function Of the Disturbancementioning

confidence: 99%

“…According to (20), the transfer function of the disturbance is given by 10 ,10     rad/s, the magnitude of the transfer function ranges from −20 dB to −80 dB. Therefore, the system has a strong ability to mitigate disturbances.…”

Section: Transfer Function Of the Disturbancementioning

confidence: 99%

“…Usually, the main control objectives of a DC microgrid include maintaining stability [4][5][6][7][8][9], minimizing cost [10][11][12], sharing power and regulating voltage [13]. For these objectives, there are mainly three control methods: decentralized control [10,12,[14][15][16][17], distributed control [18][19][20][21][22][23][24][25][26] and centralized control [11,27].…”

Section: Introductionmentioning

confidence: 99%

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Stabilization Method Considering Disturbance Mitigation for DC Microgrids with Constant Power Loads

Liang

Liu

2019

Energies

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In this paper, the stability of direct current (DC) microgrids with a constant power load (CPL) and a non-ideal source is investigated. The CPL’s negative impedance will destabilize the system, and disturbances in the non-ideal source will degrade the load voltage quality. In this study, we aim to: (1) overcome the instability of the CPL; (2) mitigate disturbances from the non-ideal source; (3) prevent the discontinuous harmonic current of high-frequency switching regulator from interfering with the source. Then, a stabilization method based on active damping which can achieve the above three objectives simultaneously is proposed. To obtain the stability conditions, the small-signal model of the system near the high-voltage equilibrium is established. Then, stability conditions are derived by eigenvalue analysis, and the domain of attraction near equilibrium is also obtained using the quadratic Lyapunov function. For the second objective, the key is to choose the optimal parameters to achieve disturbance attenuation. For the third objective, the active damper can separate the source from the switching regulator, which can prevent the discontinuous harmonic current. Moreover, the proposed method can be extended to multiple cases, and simulation results verify the effectiveness of the proposed method.

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“…It should be pointed out that the MGCC sends the PQ references to slave DGs to generate real power in order to avoid overloading inverters and to ensure that load changes are properly controlled. In the context of isolated microgrids, paper [4] developed a coordinated control strategy for managing the active power reserve.…”

Section: Introductionmentioning

confidence: 99%

Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation

et al. 2018

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In a radial distribution network integrated with distributed generation (DG), frequency and voltage instability could occur due to grid disconnection, which would result in an islanded network. This paper proposes an optimal load shedding scheme to balance the electricity demand and the generated power of DGs. The integration of the Firefly Algorithm and Particle Swarm Optimization (FAPSO) is proposed for the application of the planned load shedding and under frequency load shedding (UFLS) scheme. In planning mode, the hybrid optimization maximizes the amount of load remaining and improves the voltage profile of load buses within allowable limits. Moreover, the hybrid optimization can be used in UFLS scheme to identify the optimal combination of loads that need to be shed from a network in operation mode. In order to assess the capabilities of the hybrid optimization, the IEEE 33-bus radial distribution system and part of the Malaysian distribution network with different types of DGs were used. The response of the proposed optimization method in planning and operation were compared with other optimization techniques. The simulation results confirmed the effectiveness of the proposed hybrid optimization in planning mode and demonstrated that the proposed UFLS scheme is quick enough to restore the system frequency without overshooting in less execution time.

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A cooperative control for the reserve management of isolated microgrids

Cited by 52 publications

References 41 publications

Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid

Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid

Stabilization Method Considering Disturbance Mitigation for DC Microgrids with Constant Power Loads

Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation

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