Energy management of hybrid electric and thermal energy system

• Main Author: Hao, Xi
• Other Authors: Wang Peng
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/161501
• Institution: Nanyang Technological University

Energy management in hybrid electric and thermal system has gained great attention in recent years. The hybrid energy system is a carrier for integrating different types of energy resources such as electricity and natural gas, aiming at more efficient and economical use of thermal and electricity resources. Coordination of electricity and thermal is crucial to save energy, reduce energy prices and achieve global emission targets. Against this background, the formation of a reliable and efficient operation scheme considering the relaxation of heating and cooling demand and the response characteristics of users is a problem that needs to be solved in the current development of integrated energy systems. Due to the importance of this subject, this paper propose an optimal operation scheme for the hybrid electric and thermal system considering user demand response and the stochastic nature of PV and load, in order to increase the operational efficiency and user flexibility in energy use. A two-stage optimization model is built in this paper. At the first stage, the 1-hour operation of CHP, ESS and air-condition consumption are optimized to minimize the operational cost. At the second stage, the 15-minutes operation of air condition and CHP are optimized to minimize the consumer’s dissatisfaction on cooling and heat services. The proposed model is solved by invoking the solver GUROBI in the PYTHON environment, and the simulation results are compared and analyzed under different conditions to verify the reasonableness and effectiveness of the energy management in this paper. Keywords: Hybrid electric and thermal system; Optimal operation scheme; Two-stage optimization model; Demand response; GUROBI