Modeling Distribution Options and Constraints for Smart Power Systems with Massive Renewables Penetration

The drive toward sustainable development will be facilitated by the transition to smart cities relying on the interface and co-optimization of the cyber and physical layers modeling the Electricity Cyber Physical System (CPS). Increasing penetration of intermittent and volatile renewable energy sources connected at the transmission (e.g. wind farms) or the distribution networks (e.g. roof top PV panels) will impose new operational requirements. Fortunately, the advent of grid friendly Flexible loads and Distributed Energy Resources (DERs) including variable speed drive powered CHP microgenerators, heat pumps, and electric vehicles, provide opportunities to optimize power systems and improve operational and investment efficiencies. Indeed, DERs may have a profound impact on the resilience of network infrastructures. This paper proposes distributed decision making driven by spatiotemporal marginal-cost-based prices (DLMPs) discovered in market clearing processes enabled by the massive use of communication and computation technology. In particular, it develops a linear programming market clearing framework that models distribution network characteristics, load and DER preferences and capabilities, and AC power flow relationships. Real and reactive power as well as secondary reserve DLMPs are derived. Network as well as participant charges/revenues are evaluated. A case study of an urban This research is supported by the Qatar National Research Fund under Grant Agreement no 6-1035-5–126. Preprint submitted to Applied Energy August 25, 2015 distribution network in Europe is carried out and provides numerical results that illustrate the proposed electricity DLMP framework.