Optimal criterion and global/sub-optimal control schemes of decentralized economical dispatch for AC microgrid

Liu, Zhangjie; Su, Mei; Sun, Yao; Li, Lang; Han, Hua; Zhang, Xin; Zheng, Minghui

doi:10.1016/j.ijepes.2018.06.045

Cited by 31 publications

(24 citation statements)

References 11 publications

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“…Wind power generation is one of the fastest-increasing types of renewable energy generation [12][13][14][15]. Due to the intermittent and variable nature of wind power, wind power prediction [16] is of great importance for the safety [17,18], stability [19,20], and economic efficiency [21,22] of power grids. Wind power prediction (WPP) models can provide useful information about the upcoming wind power generation profile [12].…”

Section: Introductionmentioning

confidence: 99%

Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform

et al. 2019

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A wind power short-term forecasting method based on discrete wavelet transform and long short-term memory networks (DWT_LSTM) is proposed. The LSTM network is designed to effectively exhibit the dynamic behavior of the wind power time series. The discrete wavelet transform is introduced to decompose the non-stationary wind power time series into several components which have more stationarity and are easier to predict. Each component is dug by an independent LSTM. The forecasting results of the wind power are obtained by synthesizing the prediction values of all components. The prediction accuracy has been improved by the proposed method, which is validated by the MAE (mean absolute error), MAPE (mean absolute percentage error), and RMSE (root mean square error) of experimental results of three wind farms as the benchmarks. Wind power forecasting based on the proposed method provides an alternative way to improve the security and stability of the electric power network with the high penetration of wind power.

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Section: Introductionmentioning

confidence: 99%

Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform

et al. 2019

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“…In the absence of a central grid connection in many of the un(der)-electrified off-grid regions where SHS are currently deployed, the best way to achieve tier 4 or tier 5 level of electricity access is via a microgrid. In the past, rural microgrids in literature have encompassed different categorizations: centralized [16] and decentralized microgrids [17]; grid-connected [18] and islanded (or off-grid) [19]; AC [20], DC [21] and hybrid [22]; Renewable energy-based [23] and hybrid energy-based (with diesel) [24]. However, given the falling PV prices, solar-based solutions like pico-solar products and SHS have already seen a very high rate of proliferation and acceptance.…”

Section: Rural Microgridsmentioning

confidence: 99%

Quantifying the Benefits of a Solar Home System-Based DC Microgrid for Rural Electrification

et al. 2019

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Off-grid solar home systems (SHSs) currently constitute a major source of providing basic electricity needs in un(der)-electrified regions of the world, with around 73 million households having benefited from off-grid solar solutions by 2017. However, in and of itself, state-of-the-art SHSs can only provide electricity access with adequate power supply availability up to tier 2, and to some extent, tier 3 levels of the Multi-tier Framework (MTF) for measuring household electricity access. When considering system metrics of loss of load probability (LLP) and battery size, meeting the electricity needs of tiers 4 and 5 is untenable through SHSs alone. Alternatively, a bottom-up microgrid composed of interconnected SHSs is proposed. Such an approach can enable the so-called climb up the rural electrification ladder. The impact of the microgrid size on the system metrics like LLP and energy deficit is evaluated. Finally, it is found that the interconnected SHS-based microgrid can provide more than 40% and 30% gains in battery sizing for the same LLP level as compared to the standalone SHSs sizes for tiers 4 and 5 of the MTF, respectively, thus quantifying the definite gains of an SHS-based microgrid over standalone SHSs. This study paves the way for visualizing SHS-based rural DC microgrids that can not only enable electricity access to the higher tiers of the MTF with lower battery storage needs but also make use of existing SHS infrastructure, thus enabling a technologically easy climb up the rural electrification ladder.

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“…In this section, the small-signal stability of the PV-storage MG will be investigated by root locus technique. [37][38][39][40]…”

Section: Stability Analysismentioning

confidence: 99%

A series-parallel PV-storage independent microgrid and its decentralized control

Liu

Yuan

et al. 2018

Int Trans Electr Energ Syst

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Summary This paper presents a series‐parallel photovoltaic (PV)‐storage independent microgrid (MG), where low‐voltage distributed generation units could be connected to power grid conveniently. Moreover, it provides a promising way to form medium voltage MG. For this proposed structure, a decentralized control is proposed. The PV units are controlled by a maximum power point tracking (MPPT)‐based droop control, where MPPT of the PV units is achieved. Storage units are regulated via a “droop” controller dependent its reactive power polarity and take the responsibility of keeping the power supply‐demand balance of the MG. Since all these controllers make decisions only based on their local information, the proposed control is reliable and cost‐effective. Moreover, the small‐signal stability of the system is proved. And simulation results are presented to verify the effectiveness.

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Optimal criterion and global/sub-optimal control schemes of decentralized economical dispatch for AC microgrid

Cited by 31 publications

References 11 publications

Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform

Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform

Quantifying the Benefits of a Solar Home System-Based DC Microgrid for Rural Electrification

A series-parallel PV-storage independent microgrid and its decentralized control

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