PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 1, 2022IEEE Access45 citationsOpen Access

Decentralized Power Management of DC Microgrid Based on Adaptive Droop Control With Constant Voltage Regulation

AHAl Faris HabibullahKKKyeong‐Hwa Kim

Key Points

Key points are not available for this paper at this time.

Abstract

An adaptive droop control with constant voltage regulation is proposed for the power and voltage management of a DC microgrid (DCMG) with multiple power sources, such as a utility grid (UG), a distributed generator (DG), an energy storage system (ESS), and an electric vehicle (EV). In the proposed scheme, the droop characteristics for the UG, ESS, and EV are adaptively changed according to electricity price conditions and state-of-charge (SOC) levels in order to optimize the DCMG operation flexibility as well as electricity cost. The proposed control method not only ensures the power-sharing of DCMG reliably without the use of a communication link, but also regulates the DC bus voltage stably at the nominal value. To achieve this, the proposed scheme consists of primary control and secondary control. The primary control is used to achieve power-sharing in the decentralized DCMG, while the secondary control is used to overcome the disadvantage of conventional droop control, i.e., to remove DC bus voltage deviations. Decentralized power management is also presented to enhance the DCMG system reliability in the presence of uncertainties such as DG generation power, the ESS and EV SOC levels, the grid and EV availabilities, the load demand, and electricity price conditions. The effectiveness of the proposed scheme is demonstrated in a comprehensive simulation and experiment under various conditions. The test results clearly confirm the control flexibility and overall performance of the proposed control scheme for decentralized DCMG system.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Habibullah et al. (2022) studied this question.

synapsesocial.com/papers/6a2a8a4d1a02efbeec82dc9fhttps://doi.org/10.1109/access.2022.3228703
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Dynamic Reconfiguration of Multiobjective Distribution Networks Considering DG and EVs Based on a Novel LDBAS Algorithm2020 · 48 citations
  2. 2Optimal Sizing of PV and BESS for a Smart Household Considering Different Price Mechanisms2018 · 192 citations
  3. 3Resilience-Oriented Multistage Scheduling for Power Grids Considering Nonanticipativity Under Tropical Cyclones2022 · 54 citations
  4. 4Hierarchical Control of Droop-Controlled AC and DC Microgrids—A General Approach Toward Standardization2010 · 5,020 citations
  5. 5Centralized Control for Optimizing Microgrids Operation2008 · 900 citations