01850nas a2200241   4500000000100000008004100001653002300042653002600065653002800091653002000119653002800139100001600167700001500183700001600198700001700214700002100231245008400252856007200336300001100408490000700419520116800426022001401594       2019                            d10aTIMES energy model10aPower system planning10aRenewable intermittency10aUnit commitment10aOperational constraints1 aAnkita Gaur1 aPartha Das1 aAnjali Jain1 aRohit Bhakar1 aJyotirmay Mathur00aLong-term energy system planning considering short-term operational constraints  uhttps://www.sciencedirect.com/science/article/pii/S2211467X19300768  a1003830 v263 aThe intermittent nature of renewable energy sources (RESs) brings formidable challenges in the operation of power system. Long-term energy system planning models overlook the impact of renewable intermittency on system operations due to the computational burden associated with large model size and long planning horizon. Hence, strategies such as soft-linking multiple models are developed, but they do not assure the convergence and optimality of such incoherent modeling framework. In this context, this paper utilizes unit commitment (UC) extension of TIMES modeling framework to integrate operational constraints directly in a long-term power system planning model. This strategy eliminates the complexity of handling multiple models. Results indicate that incorporation of UC constraints improve the performance of conventional generators in terms of increased capacity utilization, and help to assess flexibility requirements with high RESs. Energy storage provides the balancing and flexibility needs with stringent generator constraints. Sensitivity analysis shows that improved flexibility of thermal generators enables increased renewable penetrations.  a2211-467X