  Continuous integration of renewable energy sources into power networks is
causing a paradigm shift in energy generation and distribution with regards to
trading and control; the intermittent nature of renewable sources affects
pricing of energy sold or purchased; the networks are subject to operational
constraints, voltage limits at each node, rated capacities for the power
electronic devices, current bounds for distribution lines. These economic and
technical constraints coupled with intermittent renewable injection may pose a
threat to system stability and performance. We propose a novel holistic
approach to energy trading composed of a distributed predictive control
framework to handle physical interactions, i,e., voltage constraints and power
dispatch, together with a negotiation framework to determine pricing policies
for energy transactions. We study the effect of forecasting generation and
consumption on the overall network's performance and market behaviours. We
provide a rigorous convergence analysis for both the negotiation framework and
the distributed control. Lastly, we assess the impact of forecasting in the
proposed system with the aid of testing scenarios.
