Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage

Power systems optimization is generally subject to the compromise between performance and cost. The 2021 Texas grid outage illustrates the worldwide dangers for the regional-centralized power grid, with comparable advantages to safety and flexibility for the distributed energy system. The storage of...

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Main Authors: Shengyu Tao, Yiqiang Zhang, Meng Yuan, Ruixiang Zhang, Zhongyan Xu, Yaojie Sun
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/14/4154
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author Shengyu Tao
Yiqiang Zhang
Meng Yuan
Ruixiang Zhang
Zhongyan Xu
Yaojie Sun
author_facet Shengyu Tao
Yiqiang Zhang
Meng Yuan
Ruixiang Zhang
Zhongyan Xu
Yaojie Sun
author_sort Shengyu Tao
collection DOAJ
description Power systems optimization is generally subject to the compromise between performance and cost. The 2021 Texas grid outage illustrates the worldwide dangers for the regional-centralized power grid, with comparable advantages to safety and flexibility for the distributed energy system. The storage of household batteries helps balance grid load and increase system stability and flexibility. However, household storage battery is still not widely used today because of its high costs. Currently, research on increasing household battery storage applicability is focused largely on optimizing economic strategies, such as configuration, dispatching and subsidy policies, which rely substantially more on technologies and financial perspectives. Consumers are not ‘rational’ individuals, and non-economic incentives can affect their decisions without raising prices. This paper consequently proposes to encourage users to acquire household battery storage to increase efficiency of power dispatching and economic advantages based on behavioral economics. In this paper, an empirical research builds upon the utility model of behavioral economics incentives and purchase willingness. Moreover, the multi-objective genetic algorithm is utilized to optimize the dispatching of household battery storage by using grid variance and user revenues as optimizing goals. The results of this paper show that the behavioral economics incentive improves intention to buy the household battery energy storage by 10.7% without raising subsidies. By improving the energy dispatching strategy, peak-load shifting performance and user revenues are improved by 4.2% and 10.6%, respectively.
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spelling doaj.art-5acb9c6b598f4cc487a027f42bdcb8b72023-11-22T03:40:54ZengMDPI AGEnergies1996-10732021-07-011414415410.3390/en14144154Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy StorageShengyu Tao0Yiqiang Zhang1Meng Yuan2Ruixiang Zhang3Zhongyan Xu4Yaojie Sun5Department of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200438, ChinaDepartment of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200438, ChinaDepartment of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200438, ChinaDepartment of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200438, ChinaDepartment of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200438, ChinaDepartment of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200438, ChinaPower systems optimization is generally subject to the compromise between performance and cost. The 2021 Texas grid outage illustrates the worldwide dangers for the regional-centralized power grid, with comparable advantages to safety and flexibility for the distributed energy system. The storage of household batteries helps balance grid load and increase system stability and flexibility. However, household storage battery is still not widely used today because of its high costs. Currently, research on increasing household battery storage applicability is focused largely on optimizing economic strategies, such as configuration, dispatching and subsidy policies, which rely substantially more on technologies and financial perspectives. Consumers are not ‘rational’ individuals, and non-economic incentives can affect their decisions without raising prices. This paper consequently proposes to encourage users to acquire household battery storage to increase efficiency of power dispatching and economic advantages based on behavioral economics. In this paper, an empirical research builds upon the utility model of behavioral economics incentives and purchase willingness. Moreover, the multi-objective genetic algorithm is utilized to optimize the dispatching of household battery storage by using grid variance and user revenues as optimizing goals. The results of this paper show that the behavioral economics incentive improves intention to buy the household battery energy storage by 10.7% without raising subsidies. By improving the energy dispatching strategy, peak-load shifting performance and user revenues are improved by 4.2% and 10.6%, respectively.https://www.mdpi.com/1996-1073/14/14/4154household energy storagebehavioral economicsmulti-objective optimizationenergy dispatching strategy
spellingShingle Shengyu Tao
Yiqiang Zhang
Meng Yuan
Ruixiang Zhang
Zhongyan Xu
Yaojie Sun
Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage
Energies
household energy storage
behavioral economics
multi-objective optimization
energy dispatching strategy
title Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage
title_full Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage
title_fullStr Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage
title_full_unstemmed Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage
title_short Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage
title_sort behavioral economics optimized renewable power grid a case study of household energy storage
topic household energy storage
behavioral economics
multi-objective optimization
energy dispatching strategy
url https://www.mdpi.com/1996-1073/14/14/4154
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