Optimal operation modeling and synergetic dispatch of source-load-storage for high renewable energy penetration

ABSTRACT

With the increase in clean energy penetration, its power curtailment during operation is made increasingly evident. In this circumstance, it is imperative to address the conflict between inflexible combined heat and power (CHP) units and variable wind and solar power. With regard to the district energy system with high penetration renewable energy, a new source-load-storage synergetic optimization operation dispatch mode is explored in this paper. It demonstrates such characteristics as the full consumption of clean energy, the CHP units with lower power output and better capability of deep peak regulation, and the small installed capacity of electric energy storage (EES) devices. Besides, this model is capable to balance heat and power demands at any time throughout the day with a variety of different energy sources, including CHP, wind, photovoltaic (PV), electrical boilers (EBs), EES, and thermal energy storage (TES) devices. Moreover, with the competitive swarm optimization (CSO) algorithm applied to solve this model, the convergence performance is improved and the computation time is reduced compared to other heuristic algorithms. Relative to the other three simulation results, the single cost of simulation result can be reduced by as much as 29.3%-34.0% at most by applying the model proposed in this paper. Moreover, this model is verified as feasible.

KEYWORDS:

• Optimal operation modeling
• synergetic dispatch
• source-load-storage
• high renewable energy penetration
• CSO

Nomenclature

Table

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (61433004), the Fundamental Research Funds for the Central Universities (N160402003), and State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (LAPS17013).

Notes on contributors

Qi Tang

Qi Tang received the B.S. degree from Northeastern University, Shenyang, China, in 2018, where she is currently pursuing the master's degree. Her current research interests include coordinated optimal operation of district energy system.

Fengnan Zhang

Fengnan Zhang received the B.S. degree from North China Electric Power University, Beijing, China, in 2018. Now she is currently pursuing the master's degree in Northeastern University, Shenyang, China.