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Abstract
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With increasing environmental concerns, limited oil reserves and governmental incentives, installation of photovoltaic (PV) systems have gained substantial momentum in smart electric distribution systems (EDS), which is considered to be a great success. That said, widespread integration of these PV units, comes uncertainty issues that puts the flexibility of the system at stake. In this regard, local district heating systems (DHS) are considered to be an effective tool in enhancing the flexibility of the power system on account of their high thermal inertia. In this study, we propose hybrid robust (RO)- stochastic programming (SP) optimization framework for commitment scheduling of distributed generation units and local DHS considering high penetration of PV units. Furthermore, the impact of flexible thermal and electrical loads on total operational cost and overall flexibility of the system is evaluated. The SP is utilized to deal obscurity of solar radiation, and RO is utilized to handle price uncertainties. The uncertainty management via the electrical storage system is also scrutinized. The results are evaluated by different cases studies implemented on an integrated IEEE 33-bus EDS and an 8-node DHS. Eventually, the mixed integer linear problem is solved with a standard CPLEX solver.
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