Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings. (1st March 2020)

• Record Type: Journal Article
• Authors: Li, Yang; Wang, Chunling; Li, Guoqing; Wang, Jinlong; Zhao, Dongbo; Chen, Chen
• Is Part Of: Energy conversion and management. Volume 207(2020)
• Publication Date: 2020-03-01
• Subjects: Renewable curtailment -- Operational flexibility -- Integrated energy system -- Renewable generation -- Thermal inertia -- Thermal-electric decoupling; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2020.112526
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A chance-constrained programming-based scheduling model is proposed for integrated energy systems. A sequence operation theory-based solution approach is developed. The effectiveness of the approach is verified via the modified IEEE 30-bus system. The approach can improve system operational flexibility by leveraging building thermal inertia and auxiliary equipments. Abstract: Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. The simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.