What Do Prosumer Marginal Utility Functions Look Like? Derivation and Analysis

Marginal Utility Functions (MUFs) encapsulate the prosumer willingness to trade energy with other market agents. In large-scale distributed optimization schemes scalability and convergence are crucial, assumption of MUFs is common. this work, instead assuming shape coefficients those functions, a method proposed derive them based on prosumer's procurement problem. We formulate rolling-horizon problem that considers asset characteristics network tariffs, we utilize forecasts capture effects uncertainty. use formulation calculate true MUF. A test case real data used investigate these functions. Our results reveal they present non-linear under certain conditions, cannot be priori derived, their form sensitive variety factors. This indicates should constructed an approach similar one in paper more accurately trade. linearized version which computationally attractive scalable, can determined using least-squares estimator achieves best fit preferences linearity constraint.