scholarly journals A Three-Stage Coordinated Optimization Scheduling Strategy for a CCHP Microgrid Energy Management System

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 245
Author(s):  
Yan Xu ◽  
Zhao Luo ◽  
Zhendong Zhu ◽  
Zhiyuan Zhang ◽  
Jinghui Qin ◽  
...  
Keyword(s):  
Energy Management ◽  
Management System ◽  
High Efficiency ◽  
Load Forecasting ◽  
Energy Management System ◽  
Scheduling Strategy ◽  
Coordinated Optimization ◽  
Scheduling Plan ◽  
Microgrid Energy Management ◽  
Optimization Scheduling

With renewable generation resources and multiple load demands increasing, the combined cooling, heating, and power (CCHP) microgrid energy management system has attracted much attention due to its high efficiency and low emissions. In order to realize the integration of substation resources and solve the problems of inaccurate, random, volatile and intermittent load forecasting, we propose a three-stage coordinated optimization scheduling strategy for a CCHP microgrid. The strategy contains three stages: a day-ahead economic scheduling stage, an intraday rolling optimization stage, and a real-time adjustment stage. Forecasting data with different accuracy at different time scales were used to carry out multilevel coordination and gradually improve the scheduling plan. A case study was used to verify that the proposed scheduling strategy can mitigate and eliminate the load forecasting error of renewable energy (for power balance and scheduling economy).

scholarly journals Microgrid Energy Management System for Residential Microgrid Using an Ensemble Forecasting Strategy and Grey Wolf Optimization

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8489
Author(s):  
Usman Bashir Tayab ◽  
Junwei Lu ◽  
Seyedfoad Taghizadeh ◽  
Ahmed Sayed M. Metwally ◽  
Muhammad Kashif
Keyword(s):  
Energy Management ◽  
Management System ◽  
Ensemble Forecasting ◽  
Small Scale ◽  
Energy Management System ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Scheduling Strategy ◽  
Load Demand ◽  
Microgrid Energy Management

Microgrid (MG) is a small-scale grid that consists of multiple distributed energy resources and load demand. The microgrid energy management system (M-EMS) is the decision-making centre of the MG. An M-EMS is composed of four modules which are known as forecasting, scheduling, data acquisition, and human-machine interface. However, the forecasting and scheduling modules are considered the major modules from among the four of them. Therefore, this paper proposed an advanced microgrid energy management system (M-EMS) for grid-connected residential microgrid (MG) based on an ensemble forecasting strategy and grey wolf optimization (GWO) based scheduling strategy. In the forecasting module of M-EMS, the ensemble forecasting strategy is proposed to perform the short-term forecasting of PV power and load demand. The GWO based scheduling strategy has been proposed in scheduling module of M-EMS to minimize the operating cost of grid-connected residential MG. A small-scale experiment is conducted using Raspberry Pi 3 B+ via the python programming language to validate the effectiveness of the proposed M-EMS and real-time historical data of PV power, load demand, and weather is adopted as inputs. The performance of the proposed forecasting strategy is compared with ensemble forecasting strategy-1, particle swarm optimization based artificial neural network, and back-propagation neural network. The experimental results highlight that the proposed forecasting strategy outperforms the other strategies and achieved the lowest average value of normalized root mean square error of day-ahead prediction of PV power and load demand for the chosen day. Similarly, the performance of GWO based scheduling strategy of M-EMS is analyzed and compared for three different scenarios. Finally, the experimental results prove the outstanding performance of the proposed scheduling strategy.

Design of Microgrid Energy Management System Based on LabVIEW

2014 ◽  
Vol 960-961 ◽  
pp. 1562-1566 ◽  
Author(s):  
Teng Yu Ge ◽  
Bu Han Zhang ◽  
Jun Li Wu ◽  
Bing Jie Jin ◽  
Shuang Zhao ◽  
...  
Keyword(s):  
Energy Management ◽  
Management System ◽  
Point Of View ◽  
System Structure ◽  
Energy Management System ◽  
Short Term ◽  
Optimization Management ◽  
Term Energy ◽  
Microgrid Energy Management

Microgrid can be applied in different locations, relative to traditional power technology. It can improve the reliability of users of electricity and power system operation. Distributed power in microgrid needs real-time and multi-objective optimization management. This paper discusses functions and structure of microgrid energy management system(MGEMS) when connected with the main grid. Problems in long-term and short-term energy management of microgrid are discussed. From the point of view of the software platform, the system structure of MGEMS software are proposed. On this basis, this paper discusses the way to construct modules of MGEMS and their functions.

Microgrid Energy Management System based ANN of the Two-Step Structure

2021 ◽  
Author(s):  
Tae-Gyu Kim ◽  
Hoon Lee ◽  
Chang-Gyun An ◽  
Kyung-Min Kang ◽  
Junsin Yi ◽  
...  
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Management System ◽  
Step Structure ◽  
Microgrid Energy Management
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