New distributed energy resources (DER) are rapidly replacing centralized power generation due to their environmental, economic and resiliency benefits. Previous analyses of DER systems have been limited in their ability to account for socio-technical complexities, such as intermittent supply, heterogeneous demand and balance-of-system cost dynamics. Here we develop ReMatch, an interdisciplinary modelling framework, spanning engineering, consumer behaviour and data science, and apply it to 10,000 consumers in California, USA. Our results show that deploying DER would yield nearly a 50% reduction in the levelized cost of electricity (LCOE) over the status quo even after accounting for socio-technical complexities. We abstract a detailed matching of consumers to DER infrastructure from our results and discuss how this matching can facilitate the development of smart and targeted renewable energy policies, programmes and incentives. Our findings point to the large-scale economic and technical feasibility of DER and underscore the pertinent role DER can play in achieving sustainable energy goals.

由于其环境，经济和弹性优势，新的分布式能源（DER）正在迅速取代集中式发电。先前对DER系统的分析在解决社会技术复杂性（例如间歇性供应，异构需求和系统平衡成本动态）方面的能力受到限制。在这里，我们开发了跨学科建模框架ReMatch，涵盖工程，消费者行为和数据科学，并将其应用于美国加利福尼亚州的10,000名消费者。我们的结果表明，即使考虑到社会技术的复杂性，部署DER也会比目前的平准化电力成本（LCOE）降低近50％。我们从结果中抽象出消费者与DER基础设施的详细匹配，并讨论这种匹配如何促进智能和有针对性的可再生能源政策，计划和激励措施的发展。我们的发现指出了DER的大规模经济和技术可行性，并强调了DER在实现可持续能源目标方面可以发挥的相关作用。