Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel

Hao Xiao; Wei Pei; Zuomin Dong; Li Kong

doi:10.17775/CSEEJPES.2017.01260

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Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel

更新时间：2025-12-18

- Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel
- CSEE Journal of Power and Energy Systems Vol. 4, Issue 2, Pages: 155-167(2018)
- 作者机构：
  
  1. Institute of Electrical Engineering Chinese Academy of Sciences,, Beijing, CN,Beijing
  2. University of Victoria,,, CA,Victoria,BC
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2017.01260
  CLC：
- Published：2018
- 稿件说明：
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Hao Xiao, Wei Pei, Zuomin Dong, et al. Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel[J]. CSEE Journal of Power and Energy Systems, 2018, 4(2): 155-167.
DOI：

Hao Xiao, Wei Pei, Zuomin Dong, et al. Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel[J]. CSEE Journal of Power and Energy Systems, 2018, 4(2): 155-167. DOI： 10.17775/CSEEJPES.2017.01260.

摘要

Abstract

The optimal planning and design of an integrated energy system (IES) is of great significance to facilitate distributed renewable energy (DRE) technology and improve the overall energy efficiency of the energy system. With the increased penetration of distributed generation (DG)

the power supply and load sides of an IES present more increased levels of uncertainties. Demand response (DR) and the energy storage system (ESS) serve as important means to shift energy supply and use across time to counter the indeterminate variations. However

the current IES planning methods are unable to effectively deal with the uncertainties of DREs and loads

and to optimize the operations of DG-DR-ESS due to the enormous possible combinations. In this paper

a new method for the optimal planning and design of an integrated energy system has been introduced and verified. The new method consists of three integrated elements. First

the method of the probability scenario has been used to model the uncertainties of the DREs and loads so as to better characterize the impact of uncertainty on the planning and design of the IES. Secondly

the optimal operation of the IES under different probability scenarios is ensured using the second-order cone optimization for quick solutions due to the simplicity of this sub-problem

serving as the bottom-level optimization. Thirdly

the optimal planning and design of IES through optimal sizing of the power generating components and ESS are performed using a special meta-model based global optimization method due to the complex

black-box

and computation intensive nature of this top-level optimization in a nested

bi-level global optimization problem. The combined approach takes full account of the interrelated operations of DG-DR-ESS under different design configurations to support a better optimal planning and design of the IES. The simulation has been carried out on an IES system modified from the IEEE 33-node distribution system. The simulation results show that the proposed method and model are effective.

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