Multi-energy coordinated optimization for both supply and demand sides of energy internet system

Abstract

The energy Internet based industrial revolution will become the key technical means to promote the transformation and development of China's energy industry. To solve the problem of the randomness of supply and demand in current power system, the theory of synergetic controllability of both supply and demand sides was put forward in this paper. The synergetic optimization model has been established based on the complementary supply network of the electricity and the thermal energy by taking the environmental cost of investment and operation as the optimal objective. The teaching-learning based optimization algorithm (TLBO) was used to solve this multi-objective nonlinear programming model. The test system proves that the proposed model can realize the bilateral collaborative optimization of supply and demand. It shows strong performance and proposes a new idea to solve these energy Internet problems.