Optimal Operation Strategy Based on Central Decoupling and Evolutionary Game for Multiple Agricultural Integrated Energy Systems

doi:10.12204/j.issn.1000-7229.2022.02.004

Abstract

Abstract:

There are concentrated energy demands and a variety of sources and loads in agricultural parks. When the multiple agricultural parks are dispersedly accessed to rural distribution network and lack of reasonable operation methods, it is bound to have a negative impact on the safety of rural distribution network and the benefit of agricultural parks. In view of the above problems, an optimal operation method based on central decoupling and evolutionary game for multiple agricultural integrated energy system (AIES) is proposed. Firstly, the AIES architecture with electricity-gas-heat and model of the demand response are constructed. Secondly, the rural distribution network is decoupled from the AIES by central decoupling. A two-layer game model including rural network layer and multi-park layer is established. The voltage safety margin and the energy cost are considered in the rural distribution network layer. The satisfaction of crop energy supply and economic benefit are considered in the agricultural park layer. Thirdly, the evolutionary game based on multi-objective particle swarm optimization is proposed. The problem of strong rationality and difficulty in achieving Nash equilibrium in a complex game with multiple parks and goals are solved. Finally, the feasibility and effectiveness of the method are verified by simulation examples. The optimal operation of multiple AIES is achieved.

Key words: central decoupling, evolutionary game, rural distribution network, agricultural integrated energy system (AIES), particle swarm optimization

CLC Number:

TM73

BIAN Hui, CHEN Lina, MA Fanlin, ZHANG Xin, JIANG Jinpeng. Optimal Operation Strategy Based on Central Decoupling and Evolutionary Game for Multiple Agricultural Integrated Energy Systems[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(2): 26-36.

Figures/Tables 12

Fig.1 Schematic diagram of AIES bidirectional coupling energy system

Fig.2 Flow chart of evolutionary game

Fig.3 Topology of rural network

Fig.4 AIES typical daily load and environmental conditions

Fig.5 Comparative analysis of MOPSO optimization process

Fig.6 Comparative analysis of evolutionary game and classic game algorithm

Fig.7 Power exchange between grid and AIES

Fig.8 Electric power stacking in AIES2 park

Fig.9 Flexible load and G2P power in AIES3 park

Table 1 Comparison of daily indicators of park demand-side response

Table 2 Comparison of daily operating targets under each scheme

Table 3 Comparison of daily control indicators under various control plans

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