Optimal dispatching of an energy system with integrated compressed air energy storage and demand response
- 1. College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083 (China)
- 2. Dept. of Biological Engineering, Utah State University, Logan, UT (United States)
- 3. Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb (Croatia)
Description
Highlights: • A rolling optimization planning framework and model of an IES considering CAES and sliding time window is proposed. • Integrated demand response (DR) is introduced into IES model. • The comparison of five different energy system configuration schemes verifies the validity and superiority of the model. • The operation characteristics of electricity-thermal joint storage and joint supply of CAES can improve the economy of IES. • A stochastic optimization model of IES is constructed based on Monte Carlo simulation. The integrated energy system is considered to be an important way to avoid energy supply risks by virtue of advantages in meeting diversified energy demand and improving energy utilization efficiency. Energy storage enables microgrid operators to respond to variability or loss of generation sources. In view of the difficulty of battery to fully improve the energy utilization efficiency and solve the problems of clean energy power large-scale consumption, and the difficulty of single demand response to significantly improve the operational reliability and economy of the integrated energy system, a rolling optimization planning framework and model of an integrated energy system considering compressed air energy storage and sliding time window-based electric and heating integrated response demand is proposed, which can obtain both optimal resource configuration and energy management strategy. The planning problem is to coordinate the output of various dispatching resources on the basis of satisfying the constraints, so as to minimize the total cost. Taking into account the uncertainty of wind power and photovoltaic output and the unplanned outage risk of the unit, a stochastic optimization model is constructed based on the probability density function of the risk variable, and finally the cost probability distribution is obtained. The results verify the universality of the planning model. The comparison of five different energy system configuration schemes and multiple time window length schemes verifies the validity and superiority of the model. The simulation results show that the integrated energy system scheme proposed by this planning model has better economy than the scheme without compressed air energy storage, and the operating cost decreases by 11.9% and the total cost decreases by 4.5%. In addition, the results show that through the introduction of demand response, the operating economy and flexibility of the integrated energy system are improved, and as the sliding window length increases, the total cost gradually decreases.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.energy.2021.121232Additional details
Identifiers
- DOI
- 10.1016/j.energy.2021.121232;
- PII
- S0360544221014808;
Publishing Information
- Journal Title
- Energy (Oxford)
- Journal Volume
- 234
- Journal Page Range
- vp.
- ISSN
- 0360-5442
- CODEN
- ENEYDS
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 53108399
- Subject category
- S14: SOLAR ENERGY; S42: ENGINEERING;
- Descriptors DEI
- COMPRESSED AIR ENERGY STORAGE; COMPUTERIZED SIMULATION; ENERGY CONSUMPTION; ENERGY DEMAND; ENERGY EFFICIENCY; ENERGY MANAGEMENT; ENERGY SYSTEMS; FLEXIBILITY; HEATING; MONTE CARLO METHOD; OPTIMIZATION; PHOTOVOLTAIC EFFECT; PROBABILITY DENSITY FUNCTIONS; SOLAR CELLS; STOCHASTIC PROCESSES; WIND POWER
- Descriptors DEC
- CALCULATION METHODS; DEMAND; DIRECT ENERGY CONVERTERS; EFFICIENCY; ENERGY SOURCES; ENERGY STORAGE; EQUIPMENT; FUNCTIONS; MANAGEMENT; MECHANICAL PROPERTIES; PHOTOELECTRIC CELLS; PHOTOELECTRIC EFFECT; PHOTOVOLTAIC CELLS; POWER; RENEWABLE ENERGY SOURCES; SIMULATION; SOLAR EQUIPMENT; STORAGE; TENSILE PROPERTIES
Optional Information
- Copyright
- Copyright (c) 2021 Elsevier Ltd. All rights reserved.