Abstract
This paper evaluates the economic impact of short-term and long-term energy storage capacity on power system operation cost. First, the unit commitment (UC) model with short-term and long-term energy storage comprising a year-round hourly operation simulation is established to minimize the optimal operation cost. By introducing the convex hull of the original feasible region of decision variables, the integer variables in UC model are relaxed as continuous variables, transforming the UC problem as a linear programming (LP). Then, by regarding the power and energy capacities as parameters, the LP is cast as a multiparametric linear programming (mp-LP), where the optimal value function (OVF) is explicitly expressed as a piecewise linear function of the capacity parameters. An approximation method is used to calculate the analytical optimal value function and critical regions. The analytical expression of OVF contains rich sensitivity information. Finally, case studies validate our proposed method and provide visualization results. The sensitivity information of analytical OVF is exploited. As a potential application, the economic evaluation results could be applied in energy storage capacity sizing.
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