Strategic and network-aware bidding policy for electric utilities through the optimal orchestration of a virtual and heterogeneous flexibility assets’ portfolio

Abstract High renewable energy penetration and exploitation of heterogeneous flexibility assets require an effective interaction between efficient energy markets and electricity grid management systems. In this business environment, modern Energy Service Providers (ESPs) need to: i) adopt imperfect market context - aware bidding strategies to maximize their profits, ii) respect the underlying network constraints, and iii) make decisions about the optimal mix of their heterogeneous flexibility (HetFlex) assets as well as their optimal sizing, siting and operation. We propose a model that factorizes all the above and an algorithm that, optimally and in an integrated way, schedules Energy Storage Systems (ESSs) and Demand Side Management (DSM) systems in order to maximize a price maker ESP's profits. We model this problem as a Stackelberg game, expressed as a Mathematical Problem with Equilibrium Constraints (MPEC), which is finally transformed into a tractable mixed integer linear program (MILP). We show that: i) ESP's profits can be considerably increased, by on average 20% compared to the price taker solution, ii) the impact of HetFlex assets’ siting and sizing can be accurately quantified, iii) even if the ESP accounts for a small portion of market's supply or demand capacity (i.e., low market power), significant profit benefits can be obtained, and iv) the network-aware feature leads not only to higher profits, but also to the avoidance of vital distribution network constraints’ violation.