Abstract
This paper presents a mixed integer linear programming (MILP) approach to deal with the volatility associated with loads and distributed energy resources (DER) in low observability distribution networks. Distribution networks, characterized by having many buses and few meters, have recently faced massive integration of DER, whose injection increases net load volatility. To better understand how to act under such increased volatility, the accuracy of state estimation (SE) needs to be improved. Our approach improves SE accuracy by providing meter placement solutions that take into account uncertainty as expressed by multiple load and DER profile scenarios, this way mitigating the impact of net load volatility. Solution results are illustrated and discussed for different case studies carried out over a radial 9 bus test feeder.
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