This dataset provides replication materials for the paper "Network Structure Matters: How Coordination and Cooperation Mechanisms Drive Solar-Battery Co-adoption" published in Environmental Research Letters. The study examines how renewable energy governance network structures influence residential solar-battery co-adoption across eight U.S. states (Arizona, California, Connecticut, Florida, Minnesota, Oregon, Pennsylvania, and Texas) from 1998–2018. Using hyperlink network analysis to measure coordination (degree centrality) and cooperation (clustering coefficients) among renewable energy stakeholders, we find that networks with higher levels of both mechanisms are significantly associated with higher co-adoption rates. Contents: code.do – Main Stata code for data preprocessing and logistic regression analysis tts_lbnl_public_data_file_10-dec-2019_0.zip – Tracking the Sun dataset (Lawrence Berkeley National Laboratory) containing solar-battery installation records and user guide actors_and_networks.zip – Network adjacency matrices and UCINET output files for eight state-level renewable energy governance networks 2024data.zip – Updated adoption data through 2023 for Figure 2 network.zip – Processed network variables for regression analysis policy.zip – Policy incentives and regulatory data from DSIRE sbir.zip – Small Business Innovation Research awards data (innovation proxy) yale_survey.zip – Environmental awareness data from Yale Climate Opinion Maps co-adoption-by-county-new.zip – County-level data for co-adoption maps (Figure 2) Demographic data (zipped by variable): age, edu, housing_unit, median_home_value, median_income – County-level socioeconomic data from U.S. Census Bureau (2010–2019) battery.zip – Battery innovation and technology data Funding: National Science Foundation award #2125775