Data-Driven Robust Economic Dispatch for Distribution Network and Multiple Micro-grids Considering Correlativity of Wind and Solar Output

doi:10.12204/j.issn.1000-7229.2021.10.005

Abstract

Abstract:

As renewable energy generations represented by wind and photovoltaic power connect to the distribution network (DN) through multiple micro-grids (MMGs), the uncertainty will bring challenges to the reliability and economy of the operation of the DN and MMGs. In response to this, this paper proposes a data-driven robust dispatch method for DN and MMGs considering correlation between wind and solar output. Firstly, a distributed dispatch method is adopted to establish the dispatch model of the DN and a two-stage dispatch model of the MMGs, with the tie-line power as the coupling parameter of the two. Aiming at the uncertainty of renewable energy output as well as the temporal and spatial correlations, the wind-solar output ellipsoid uncertain set is constructed based on the data-driven algorithm, thereby establishing the two-stage data-driven robust dispatch model of the micro-grid. Finally, an improved column and constraint generation algorithm based on extreme scenarios is proposed to solve the robust dispatch problem of the micro-grid, and the analytical target cascading method is used to solve the overall dispatch problem of DN and MMGs. The simulation results show that the proposed method can capture the spatial-temporal correlation between wind and solar, improve the economy of dispatch while ensuring the robustness of the DN and MMGs dispatch, and has good convergence.

Key words: multiple micro-grids (MMGs), renewable energy, data-driven robust optimization, extreme scenario

CLC Number:

TM73

ZHANG Yuwei, XIAO Jinxing, YANG Jun, XU Bingyan, LI Rui, LI Yonghui. Data-Driven Robust Economic Dispatch for Distribution Network and Multiple Micro-grids Considering Correlativity of Wind and Solar Output[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(10): 40-50.

Figures/Tables 15

Fig.1 Structure of DN and MMGs

Fig.2 The cubic set and the ellipsoid set

Fig.3 Flow chart of the data-driven robust optimization method

Fig.4 Flow chart of dispatch solving based on ATC

Fig.5 Day-ahead dispatching scheme of DN

Fig.6 Day-ahead scheduled output and reserve capacity of MT in MG

Fig.7 The iterative convergence curve of ATC

Table 1

Table 2

Fig.A1 Topology of the test system

Fig.A2 Daily load curve of MMGs and DN

Fig.A3 Extreme scenario of wind power output in data-driven set

Fig.A4 Extreme scenario of photovoltaic power output in data-driven set

Fig.A5 Extreme scenario of wind power output in uncertain interval set

Fig.A6 Extreme scenario of photovoltaic power output in uncertain interval set

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