A bi-level co-expansion planning of integrated electric and heating system considering demand response

Abstract

With the wide deployment of combined heat and power units, electric boilers, etc., the power system and the heating system are coupled tightly, which necessitates expansion planning in a coordinated manner. Demand response (DR) is considered an effective method for augmenting system flexibility, which would lead to a more beneficial planning strategy in the co-expansion planning strategy. Therefore, we develop a bi-level co-expansion planning model with DR constraints for the integrated electric and heating system to minimize expenses on both investment and operation. The upper level gives the optimal investment strategy of energy facilities, while the lower level is optimal operation problems with DR constraints under the given investment decision. Numerical simulation is employed in the P6H8 system to demonstrate the proposed model.

Balancing the Water-Carbon Trade-Off: Development of a Bi-Level Source-Grid-Load Synergistic Optimization Model for Multi-Regional Electric Power System

“…This is primarily attributed to the absence of prioritization among decision makers [47][48][49]. To address this gap, bi-level programming (BLP) has emerged as a promising solution for hierarchical decision making involving conflicting objectives [50][51][52]. Based on the Stackelberg games concept, BLP facilitates effective decision making by arranging decision makers in a preset hierarchy.…”

“…Based on the Stackelberg games concept, BLP facilitates effective decision making by arranging decision makers in a preset hierarchy. For instance, Du et al (2022) utilized BLP to propose a co-expansion planning model aimed at minimizing the costs associated with investment and operation while incorporating demand response constraints [52]. Furthermore, Lv et al (2021) employed an interval bi-level joint-probabilistic programming approach to formulate a strategic plan for China's long-term energy-water nexus system spanning from 2021 to 2050 [53].…”

A Robust Interval Optimization Method for Combined Heat and Power Dispatch

“…Refs. [6][7][8][9][10] investigated the thermal inertia of buildings and their power load shifting capacity. These studies have focused on optimizing the operational costs and enhancing the wind power consumption capacity of systems by using boilers, heat pumps, and the thermal inertia of buildings.…”