• Media type: E-Article
  • Title: Distributed algorithm without iterations for an integrated energy system
  • Contributor: Tan, Jiaming; Liu, Xinying
  • Published: Frontiers Media SA, 2023
  • Published in: Frontiers in Energy Research, 10 (2023)
  • Language: Not determined
  • DOI: 10.3389/fenrg.2022.1078938
  • ISSN: 2296-598X
  • Keywords: Economics and Econometrics ; Energy Engineering and Power Technology ; Fuel Technology ; Renewable Energy, Sustainability and the Environment
  • Origination:
  • Footnote:
  • Description: <jats:p>Existing energy management methods for integrated energy systems are mostly in distributed communication and computation now, need a large number of iterations, and each time of iteration needs lots of communication and computation. For this reason, on one hand, the iteration may cause energy-delay. On the other hand, iteration will significantly increase the communication and computation burden. The integrated energy systems contain a variety of devices and energy resources (including renewable energy resources), so the communication and computation burden is already very high. If the communication and computation cannot be solved very well, the cost functions of each device need to be much easier to ensure the operation of the system and their systematic error will be much larger. For this reason, the result of optimization will be much worse because of the accuracy of cost functions. The greatest challenge of this issue is to establish an algorithm without iteration. For handling this issue, first, we adopt the theoretical demonstration to prove that if all prices of all devices are the same, the optimization will be realized and the instantaneous price is the one-order derivative. (we assume the relationship between the operating cost and the energy flow of each device as the convex cost functions.) Second, we reshape all cost functions. Third, we change the function to the total of the foregoing functions in the directed annular path and adopt the total function of the hole system to solve the energy price. Last, we use the price to ensure their operating condition. Our theoretical demonstration has already proved the optimization, convergence, the plug and play performance, scalability, and the emergency scheduling performance of the annular partial differential algorithm (APDA).</jats:p>
  • Access State: Open Access