Abstract

A scientific and effective coordinated control strategy is crucial to the safe and economic operation of a microgrid (MG). With the continuous improvement of the renewable energy source (RES) penetration rate in MG, the randomness and intermittency of its output lead to the increasing regulation pressure of the conventional controllable units, the increase of the operating risk of MG and the difficulty in improving the operational economy. To solve the mentioned problems and take advantage of hybrid energy storage system (HESS), this study proposes a multi-time scale coordinated control scheme of “day-ahead optimization (DAO) + intraday rolling (IDR) + quasi-real-time correction (QRTC) + real-time coordinated control (RTCC).” Considering the shortcomings of existing low prediction accuracy of distributed RES and loads, the soft constraints such as unit commitment scheduling errors and load switching scheduling errors are introduced in the intraday rolling model, allowing the correction of day-ahead unit commitment and load switching schedule. In the quasi-real-time coordinated control, an integrated criterion is introduced to decide the adjustment priority of the distributed generations. In the real-time coordinated control, the HESS adopts an improved first order low pass filtering algorithm to adaptively compensate the second-level unbalanced power. Compared with the traditional coordinated control strategy, the proposed improved model has the advantages of good robustness and fast solving speed and provides some guidance for the intelligent solution for stable and economic operation of stand-alone MG with HESS.

Highlights

  • In recent years, distributed generation (DG) technology has rapidly developed due to its advantage of efficiently consuming energy locally

  • The energy-type ESS (ETESS) power command value determined from rolling optimization can provide criteria for the decision of ETESS quasi-real-time charge/discharge state which is expected to follow the command from rolling optimization

  • Without regularization terms in the day-ahead optimization model, the power shortage percentage without regularization terms in the day-ahead optimization model, the power shortage percentage can can reach as high as 28.3567% and the system operation cost is 62.57% less than the cost when reach as high as 28.3567% and the system operation cost is 62.57% less than the cost when regularization regularization is taken into account

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Summary

Introduction

In recent years, distributed generation (DG) technology has rapidly developed due to its advantage of efficiently consuming energy locally. Reference [15] proposes a coordinated control strategy in day-ahead and intraday aspects, considering battery lifetime degradation cost when optimizes operation cost. Reference [17] proposed an energy management model for MG based on day-ahead and real-time timescale. In [18], a strategy for obtaining optimal scheduling of multiple microgrid systems with power sharing through coordination among microgrids that have no cost function of generation units is proposed An improved multi-time scale coordinated control strategy is proposed for stand-alone MG with HESS. Compared with the traditional coordinated control strategy, the proposed improved model has the advantages of good robustness and fast solving speed and provides some guidance for the intelligent solution for stable and economic operation of stand-alone MG with HESS.

Typical Topology of Stand-Alone Microgrid with Hybrid Energy Storage System
Multi-time Scale Coordinated Control Framework
Decision Variables
Objective Function and Constraints
Intraday Rolling Optimization Based on Model Predictive Control
Model Predictive Control Framework
Objective
Comprehensive Criteria Based Quasi-Real-Time Coordinated Control
Real-Time Correction Control of Hybrid Energy Storage
Case Study
Basic Data
Analysis
Day-ahead
Results of
Analysis of the Necessity of Introducing Quasi-Real-Time
Conclusions
Full Text
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