Benefit Evaluation of Energy Storage in Multi-energy Collaborative Optimization of Regional Energy Internet

doi:10.12204/j.issn.1000-7229.2021.05.006

Abstract

Abstract:

The energy Internet is regarded as the development form of smart grid in the future by realizing horizontal multi-energy complementation and vertical high coordination of "source-grid-load-storage" to achieve efficient energy utilization. In order to evaluate the benefits of multi-energy storage configuration in regional energy Internet (REI) multi-energy collaborative optimization, the architecture of regional energy Internet is analyzed firstly, and then on the basis of the multi-energy storage model, multi-energy coupling device model and energy router (ER) model, a multi-energy coupling energy storage system model is constructed. Then, the benefit evaluation model of energy storage is proposed from three aspects of peak-valley difference benefit, environmental benefit and energy-loss reduction benefit, and the corresponding evaluation indices are given. Finally, a commercial REI with electricity, gas and heat load is taken as an example to calculate the energy storage benefit, and different capacity and different types of energy consumption are analyzed and the effectiveness of the proposed index is verified. The results provide guidance for the allocation of energy storage in REI and the establishment of relevant market mechanism.

Key words: combined heating and power, energy storage, regional energy Internet (REI), benefit evaluation

CLC Number:

TM73

FANG Chen, ZHANG Yu, LIAO Wang, SHI Shanshan, LIU Dong. Benefit Evaluation of Energy Storage in Multi-energy Collaborative Optimization of Regional Energy Internet[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(5): 48-56.

Figures/Tables 11

Fig.1 Energy structure of regional energy Internet

Fig.2 Energy conversion diagram of extended ER

Fig.3 Benefit evaluation results under different scenarios

Fig.4 Comparison of contribution degree in different scenarios

Table 1 Comparison of benefit rates in different scenarios

Fig.5 Influence of energy storage capacity ratio on contribution degree

Fig.6 Influence of energy storage capacity on benefit rate

Fig.7 Influence of energy storage capacity ratio on benefit rate

Table A1 Main parameters of equipment

Fig.A1 Load and prediction output of photovoltaic and wind power

Fig.A2 Curve of energy prices

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