Adaptive Microgrid Price-Making Strategy and Economic Dispatching Method Based on Blockchain Technology

doi:10.12204/j.issn.1000-7229.2021.06.003

Abstract

Abstract:

The ability of single microgrid to deal with the uncertainty of the output of various distributed power sources is limited. Power transaction among multiple microgrids in an area is one of the effective methods to improve the consumption of local renewable energy. However, the traditional centralized transaction platform has the problems of high platform maintenance cost, untimely transfer of funds and opaque transaction information. In this situation, applying the distributed data storage and peer-to-peer transaction technology of blockchain, this paper designs smart contracts for multi-microgrid market transactions to help microgrids make decisions. Under the energy coordination architecture of multi-microgrid trading market, the microgrid firstly adopts adjustable robust optimization to formulate a scheduling plan that considers the uncertainty of renewable energy output. Secondly, the judgmental smart contract is used to judge the market’s trading mode. Then, smart meters are used to make adaptive price and the transaction matching is completed by the distributed transaction smart contract. Finally, the transaction plan determined by the distributed transaction smart contract can be used as the input data of adjustable robust optimization of the single microgrid to explore feasible solutions. At last, a better economic solution is selected as the optimal day-ahead output plan and trading plan for the microgrid under the worst distributed power output scenario. Simulation results indicate the effectiveness of the presented method.

Key words: adjustable robust optimization, blockchain, smart contract, adaptive pricing

CLC Number:

TM73

CHEN Tao, LIU Yang, LI Wenfeng, XU Lixiong, MA Teng. Adaptive Microgrid Price-Making Strategy and Economic Dispatching Method Based on Blockchain Technology[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(6): 17-28.

Figures/Tables 14

Fig.1 Architecture of multi-microgrid energy trading system

Fig.2 Structure of multi-microgrid system

Fig.3 Aggressive model

Fig.4 Flow chart of robust model resolving

Table 1 Operation cost of day-ahead scheduling plan for each microgrid 元

Table 2 Iteration results of each round of each microgrid

Table 3 Cost of each microgrid participating in multi-microgrid transaction 元

Fig.5 Unit output plan of each microgrid participating in multi-microgrid transaction

Fig.6 Matching results of the second round of transactions

Table 4 Optimization results when the adjustable robustness parameter Γ is 0 元

Table 5 Optimization results when the adjustablerobustness parameter Γ is 24 元

Table 6 Power purchase costs of micro-microgrid participating in multi-microgrid transactions or not元

Fig.B1 Load of each microgrid and renewable energy output

Fig.B2 Unit output plan of each microgrid not participating multi-microgrid transaction

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