Open AccessResearch on Control Strategy of Electric Heating Load Cluster
Author(s) -
Xingxiang Zhang,
Dezhi Li,
Bo Lü,
Ying Zhou,
Qing Li,
Shupeng Li,
Feixiang Gong
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/768/6/062007
Subject(s) - renewable energy , grid , intermittent energy source , wind power , electric power , load shifting , computer science , distributed generation , power (physics) , automotive engineering , electrical engineering , engineering , electricity , physics , geometry , mathematics , quantum mechanics
At present, due to the rapid development of the economy and the unceasing enthusiasm of the modernization process, human beings are increasingly dependent on electric energy. The development of renewable energy and energy efficiency have become the consensus in the energy field. The randomness of in the future solar power generation, wind power and other intermittent and new energy sources in the power grid continue to rise, which is bound to occupy an increasingly important position power energy structure. The active regulation capability of the “power supply side” in a high-ratio renewable energy grid is degraded. To ensure safe and efficient operation of the grid, it is imperative to develop the regulation capability on the load side. This paper establishes a cluster aggregation model, clusters the electric heating load through scientific and rational grouping, makes the electric heating load form a load group for unified regulation, formulates an appropriate cluster optimization control strategy, and makes full use of the cluster electric heating control potential to achieve peak clipping. Fill the valley, effectively improve the regulation capacity of the grid.