Optimal Scheduling of Distributed Generation System for Kitchen Waste Treatment Plant Based on Model Predictive Control

LI Anle; YI Zhigang; PENG Xing

doi:10.3969/j.issn.1008-0198.2022.04.015

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Optimal Scheduling of Distributed Generation System for Kitchen Waste Treatment Plant Based on Model Predictive Control

更新时间：2025-06-11

- Optimal Scheduling of Distributed Generation System for Kitchen Waste Treatment Plant Based on Model Predictive Control
- Vol. 42, Issue 4, Pages: 75-80(2022)
- 作者机构：
  
  湖南仁和环境股份有限公司,湖南,长沙,410005
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1008-0198.2022.04.015
  CLC： TM714
- Published：2022
- 稿件说明：
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李安乐, 易志刚, 彭星. 基于模型预测控制的厨余垃圾处理厂分布式发电系统优化调度[J]. 湖南电力, 2022, 42(4): 75-80.

LI Anle, YI Zhigang, PENG Xing. Optimal Scheduling of Distributed Generation System for Kitchen Waste Treatment Plant Based on Model Predictive Control[J]. 2022, 42(4): 75-80.
李安乐, 易志刚, 彭星. 基于模型预测控制的厨余垃圾处理厂分布式发电系统优化调度[J]. 湖南电力, 2022, 42(4): 75-80. DOI： 10.3969/j.issn.1008-0198.2022.04.015.

LI Anle, YI Zhigang, PENG Xing. Optimal Scheduling of Distributed Generation System for Kitchen Waste Treatment Plant Based on Model Predictive Control[J]. 2022, 42(4): 75-80. DOI： 10.3969/j.issn.1008-0198.2022.04.015.

摘要

在厨余垃圾处理厂中

为了充分利用分布式光伏发电系统

满足厂用电需求

减少电网用电量的同时降低对电网的冲击

提出基于模型预测控制的分布式发电系统优化调度策略。首先

对分布式光伏发电系统出力进行日前预测

结合厂用电计算出对主网用电量的需求计划。然后

基于模型预测控制对储能系统出力进行滚动优化调度

通过合理调整储能系统出力来平抑分布式光伏发电系统出力预测误差。最后

以某厨余垃圾处理厂实际算例进行验证

并对其经济效益与环境效益进行测算

结果表明所提策略具有较高的环境和经济效益。

Abstract

To make full use of the distributed power generation system in the food waste treatment plant

meet the plant power demand

and reduce the power consumption of the grid while reducing the impact on the grid

the optimal dispatching strategy of the distributed power generation system based on model prediction control is proposed. Firstly

the power output of distributed power generation system is day-ahead predicted

and the load demand plan for upper grid power is calculated by combining with plant power consumption. Then

the output of energy storage system is optimally dispatched on a rolling basis based on model prediction control

and the prediction error of distributed power generation system is suppressed by reasonably adjusting the power output of energy storage system. Finally

the actual example of a waste treatment plant is verified

and its economic and environmental benefits are measured. The results show that the proposed strategy has high environmental and economic benefits.

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references

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