The social factors shaping community microgrid operation

Can residents in a community microgrid enjoy greater electricity quotas during blackouts by paying more? A new FRS study shows U.S. residents support market-based mechanisms even in life-and-death situations.

06.08.2024

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When extreme weather events result in power blackouts, the critical electricity needs of a community can continue to be met by utilising localised energy resources. The collective setup of these resources is referred to as a microgrid. Dr Gurupraanesh Raman, Yang Yang, and Prof. Jimmy Chih-Hsien Peng external page carried out a survey to study the preferences of 1021 U.S. residents on how the finite energy stored in a community microgrid should be rationed amongst various participating households during prolonged blackouts.

Fig 1 — Fig.1: Framework of the web-based survey. The survey elicit respondent perceptions on the fairness of a differentiated service scheme for energy rationing in a community microgrid, and their willingness to sell stored energy during a blackout.

Particularly, a differentiated service paradigm—where certain consumers can pay more to avail of higher energy quotas—received support from over 91.8% of respondents, despite the zero-sum nature of such rationing. We also report that respondents were receptive to selling between 42–53% of their stored energy to the microgrid should they own personal backup devices—what we call willingness-to-sell—balancing self-preservation and monetary compensation. Studying the factors influencing the responses on the fairness of differentiated service (for consumers) and willingness-to-sell (for storage owners), we identify for policymakers and businesses that an energy-as-a-service model is socially acceptable for community microgrids.

Fig.2: Survey responses pertaining to a differentiated service paradigm for community microgrids. a Histogram showing the preference of respondents on the fairness of differentiated service, quota-based usage, and whether usage quotas should be strictly enforced during a blackout. Here, the responses are on a Likert scale from 0 to 10, where a larger number indicates stronger support. b Responses on the payment plan perceived to be the most fair for availing of backup service from the community microgrid, where the choices differ in the fixed cost per year (USD($)/year) and variable cost ($/blackout day (BD)). c Density plots showing the probability distribution of the additional amount of money that respondents are willing to pay per year towards providing backup for economically weaker residents in the community. Responses are grouped according to the responses from (b), where values above $1000 are capped at $1000.

Fig 3 — Fig.3: Survey responses on willingness-to-sell (WTS). a How willing the respondents are to participate in a contract where they sell energy to the microgrid from personal storage in exchange for a payment. Here, the responses are on a Likert scale from 0 to 10, where a larger number indicates higher willingness. b Correlation between the respondents' willingness to participate in a selling contract with their support for differentiated service. Here, the solid line is the result of a linear regression, with the shaded area representing the prediction interval with 95% confidence. The size of the circles represents the number of respondents. c Preferences on the nature of payment for selling energy to the microgrid. d–f Heat map of the WTS for an anticipated 2-day blackout versus a 7-day blackout for the three cohorts. Here, the solid line is the result of a linear regression, and the coordinates indicate the mean WTS.

_{Image: Rolls-Royce MTU Microgrid Validation Center by external page mtu solutions on Flickr Creative Commons}

Raman, G., Yang, Y. & Peng, J.CH. The social factors shaping community microgrid operation. Nat Commun 15, 6451 (2024). external page https://doi.org/10.1038/s41467-024-50736-9