Pressing environmental problems, energy supply security issues, and nuclear power safety concerns drive the worldwide interest in renewable energy. The US Clean Energy Challenge calls for a partnership of states and communities to expand solar to 140GW by 2020. Investment in renewables today is in utility-scale solar plants and wind farms, as well as small-scale distributed rooftop photovoltaics (PV). Large solar plants are cheaper than rooftop PV, but this advantage is diminished when considering transmission infrastructure costs. Generous tax credits and net metering subsidies are responsible for much of the dramatic growth of distributed PV. Under net metering, utilities are mandated to buy back excess generation at retail prices. But tax credits are being phased out, and utilities strenuously oppose net metering policies as they allow PV owners to avoid paying for infrastructure costs and pose an existential threat to utility business models. The growth of distributed PV generation may decelerate. This project aims to sustain and accelerate future growth in distributed PV investments by enabling connected communities to share electricity services. The central thesis is that shared PV ownership and operations can spur greater investment in distributed PV with minimal subsidy, without net metering, and with participants fairly paying for infrastructure, reserves and reliability costs. Our research will enable connected communities to efficiently use resources, reduce emissions, and support our collective sustainability goals. It will spur deeper penetration of distributed PV without subsidy, while defining new entrepreneurial opportunities in the sharing economy for electricity services. The project will integrate education and research through new interdisciplinary courses that combine technology, economics, policy, and power systems. This research is broadly applicable to other shared services including electricity storage, building energy management, and transportation networks. Specifically, we will (a) develop the infrastructure necessary for sharing electricity services, (b) analyze investment decisions of households under various tariff and subsidy designs, (c) construct behavioral model that predict consumer response to incentives, and (d) conduct an empirical assessment of sharing grounded in data. In our architectural vision for sharing, agents interact with each other through a cloud based supervisory system. This system manages constraints, accepts supply and demand bids for shared resources, clears the market, and publishes prices. A key element of our architecture is software-define-power-flow to scale sharing to millions of clients under a peer-to-peer matching platform. We will make the business case for sharing in the energy sector using game-theoretic methods and micro-economic tools to analyze investment decisions in a sharing economy for electricity services. Recruiting clients to share their resources is a key research challenge. Here, we will apply modern machine learning methods to identify, model, and target suitable clients. Finally, we will use data analytics methods to make a compelling case for sharing based on city-scale data.