Global warming has motivated the world’s majorcountries to actively develop technologies and make policies topromote carbon emission reduction. Focusing on interconnectedmulti-regional power systems, this paper propo...
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Global warming has motivated the world’s majorcountries to actively develop technologies and make policies topromote carbon emission reduction. Focusing on interconnectedmulti-regional power systems, this paper proposes a coordinatedplanning model for interconnected power systems consideringenergy storage system planning and transmission expansion. Amarket-based carbon emission quota trading market that helpsreduce carbon emissions is built and integrated into the coordinated planning model, where entities can purchase extra or sellsurplus carbon emission quotas. Its effects on promoting carbonemission reduction are analyzed. Considering the limitations oninformation exchange between interconnected regional powersystems, the proposed model is decoupled and solved with theanalytical target cascading algorithm. A modified two-region 48-bus system is used to verify the effectiveness of the proposedmodel and solving method.
Zero-carbon energy stations (ZCESs) have a promising prospect in reducing carbon emission, which also results in great impacts on the planning scheme of low-carbon distribution system (DS). In this context, this paper...
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Zero-carbon energy stations (ZCESs) have a promising prospect in reducing carbon emission, which also results in great impacts on the planning scheme of low-carbon distribution system (DS). In this context, this paper carries out the low-carbon DS planning considering the flexible support of ZCES. Firstly, a low carbon DS planning model is established, where the material carbon emission and operational carbon emission are both considered. Then, for achieving the low-carbon goal of DS, the flexible support of ZCES is considered during the low-carbon DS planning process. Especially, ZCES is supplied by zero-carbon renewable energy (e.g., photovoltaics and wind power). Meanwhile, DS and ZCES are regarded as different stakeholders, which is addressed by the analyticaltargetcascading (ATC) algorithm. In addition, a distributionally robust optimization method is proposed to cope with the probability distribution (PD) uncertainty of renewable energy and loads. Moreover, a tractable low-carbon planning model for DS considering the flexible support of ZCES is reformulated based on the duality method. Finally, the proposed planning model is tested on a modified IEEE 33-node and a practical 99-node distribution system with ZCES. Numerical results show that the proposed low-carbon planning model is effective in managing PD uncertainties, and improving the low-carbon and economic performance of DS while the ATC algorithm also exhibits good convergence performance. (c) 2022 Elsevier Ltd. All rights reserved.
Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution net...
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Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution network have interaction. As a bridge connecting the transmission grid (TG) and micro grid (MG), ADN breaks the traditional operation pattern of TG + ADN + MG. Considering the physical connections and shared information among TG, ADN and MG, this paper proposes a decentralized and parallel analyticaltargetcascading (ATC) algorithm for interactive unit commitment (UC) implementation in regional power systems. To explore the synergistic ability of the TG + ADN + MG coping with uncertainties of DER, i.e., wind power, the primary and secondary frequency regulation of TG are implemented to cope with uncertainties. Furthermore, the distributional uncertainty of wind power is well modeled by data driven, which is proposed in our previous work (Zhang et al., 2019) [1]. Both the startup/shutdown variables of the thermal units and the variables in TG + ADN + MG are integrated into the multi-level interactive UC model to optimize simultaneously, thus realizing the optimal goal of the whole network, resources complementary and optimal allocation of power system. An improved 6-bus system is used to test the proposed model, the numerical results show that the proposed decentralized algorithm is a fully parallelized procedure. And it also demonstrates the parallel implementation significantly enhances computations efficiency of the ATC algorithm.
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