  This paper proposes a method to design network-aware flexibility requests for
local flexibility markets. These markets are becoming increasingly important
for distribution system operators (DSOs) to ensure grid safety while minimizing
costs and public opposition to new network investments. Despite extended recent
literature on local flexibility markets, little attention has been paid to
quantifying the flexibility required at each location, considering physical
network constraints (e.g. line and voltage limits). The method introduced uses
a chance-constrained optimization model and a LinDistFlow approximation to
consider both physical network constraints and uncertainty caused by renewable
production or demand fluctuations. Unlike other methods, it avoids sharing
sensitive grid data with the market operator. We compare our approach against a
stochastic market-clearing mechanism which serves as a benchmark, and we derive
analytical conditions for the performance of our method to determine
flexibility requests. We show on two case studies that our method outperforms
the stochastic market-clearing benchmark in terms of computation time while
achieving comparable social welfare and costs for the DSOs. One of the case
studies is conducted on an actual German distribution grid, showing that the
proposed method can scale well to real-sized networks.
