Optimum Droop Parameter Settings of Islanded Microgrids With Renewable Energy Resources

Abdelaziz, Morad; Farag, Hany E. Z.; El-Saadany, Ehab F.

doi:10.1109/tste.2013.2293201

Cited by 98 publications

(57 citation statements)

References 31 publications

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“…Therefore, the active power allocation is designed first. To achieve the precise allocation of active power, we assume that the DG can communicate with the neighbors through diagraph G. Because the active power of a DG changes along with the loads, the synergetic control without leaders is adopted to design the auxiliary variable in Equation (11). The auxiliary control variable considering time-delays in communication is discussed in [27].…”

Section: Active Power Controlmentioning

confidence: 99%

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Adaptive Droop Control for Microgrids Based on the Synergetic Control of Multi-Agent Systems

Yu¹,

Ai²,

He³

et al. 2016

Energies

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Abstract:In this paper, a distributed synergetic control based on multi-agent systems is proposed to solve the problems of frequency and voltage errors, system stability and power sharing accuracy in the traditional droop control of microgrids. Starting with power flow equations, we build the secondary-order dynamic model of DG, which consists of three parts: (1) active power allocation; (2) active power-frequency; and (3) reactive power-voltage droop control. Considering time-delays in communication networks, a leaderless synergetic control algorithm is proposed to allocate the active power in inverse proportion to the droop coefficient, and the synergetic control with a virtual leader is proposed to control the system frequency and voltage to keep at the expected value. Besides, the direct Lyapunov method is introduced to verify the globally asymptotical stability. Moreover, the impacts of communication disturbance are also discussed from the aspects of control precision and system stability. Finally, based on a test microgrid, numerous cases are designed as illustration, and the simulation results validate the proposed method.

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Section: Active Power Controlmentioning

confidence: 99%

“…Proper controls with centralized or decentralized structures are necessary to maintain operations stable and economically efficient. Among them, distributed control is the most desirable option because the communication network in centralized control is complex and spans a large geographical area [3,[5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Droop Control for Microgrids Based on the Synergetic Control of Multi-Agent Systems

Yu¹,

Ai²,

He³

et al. 2016

Energies

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show abstract

“…One of these factors is the grid topology, as it was recognized by Abdelaziz et al [7]- [9], who in a series of recent papers succeeded in developing tools for analyzing the optimal performance of the microgrid. These authors recognized the advantages and opportunities of adapting a load power flow algorithm to the core of their approaches.…”

Section: Introductionmentioning

confidence: 99%

Direct Backward/Forward Sweep Algorithm for Solving Load Power Flows in AC Droop-Regulated Microgrids

Díaz

Gómez‐Aleixandre

Coto

2016

IEEE Trans. Smart Grid

126

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Abstract-We propose an algorithm capable of solving the load power flow problem in ac droop-regulated microgrids. Based on radial distribution networks, these systems lack a slack bus for facilitating the computation by means of conventional methods. Rather than having the stiff bus that provides a voltage reference and supplies the necessary power, the voltage and power regulation must be shared among the distributed resources as a function of their frequency and voltage droop functions. The proposed algorithm is based on the well-known backward/forward sweep algorithm, conventionally employed to solve grid-connected radial load power flows, with the interesting property that they are derivative-free. We have expanded the algorithm to cope with the lack of slack bus. In this paper, we show the theoretical foundation and provide some tests with ex-post computations to investigate the coherence of the results.Index Terms-Backward/forward sweep (BFS), droop, load power flow, microgrids.

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“…The inverter-interfaced DGs have much smaller inertia than a synchronous generator in traditional ac grid and the RES are intermittent, which makes the frequency of an islanded MG at the risk of instability. The droop control methods, which increase virtual inertia of inverter-interfaced DGs by mimicking the governor of a synchronous generator, are widely used as the primary control [2,[4][5][6][7] of an MG. The variability of renewable power sources are compensated by droop-controlled DGs or super capacitor storage systems.…”

Section: Introductionmentioning

confidence: 99%

Agent‐based distributed and economic automatic generation control for droop‐controlled AC microgrids

Zang

Zeng

et al. 2016

IET Generation, Transmission & Distribution

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Microgrids (MGs) are presented as a cornerstone of smart grid, which can integrate renewable energy sources environmentally, friendly, and reliably. Hierarchical control strategies, i.e. primary droop control, second automatic generation control (AGC), and tertiary economic dispatch (ED), are widely used to control and optimise an MG. However, the gap between large time-scale ED and small time-scale AGC may decrease the economical efficiency of an MG. To address this problem, this study proposes a distributed economic AGC (EAGC) algorithm. The algorithm is fully distributed, as each distributed generator is assigned with an agent and the agents only require the local measurements and communication with its neighbours. Compared with centralised algorithms, the distributed control algorithm is easy to fulfil the plug-and-play requirements and reduces costs to modify the architecture of an MG. Furthermore, the proposed EAGC algorithm is suitable for all possible operation modes of an MG, i.e. islanded mode, grid-connected mode, and transition mode. To improve the robustness against agent loss or communication link fault, the topology of agents' communication network is designed to satisfy the N − 1 rule. The effectiveness of the proposed algorithm is demonstrated through the simulation tests which involve plenty of case studies.

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Optimum Droop Parameter Settings of Islanded Microgrids With Renewable Energy Resources

Cited by 98 publications

References 31 publications

Adaptive Droop Control for Microgrids Based on the Synergetic Control of Multi-Agent Systems

Adaptive Droop Control for Microgrids Based on the Synergetic Control of Multi-Agent Systems

Direct Backward/Forward Sweep Algorithm for Solving Load Power Flows in AC Droop-Regulated Microgrids

Agent‐based distributed and economic automatic generation control for droop‐controlled AC microgrids

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