A stochastic MPEC approach for grid tariff design with demand-side flexibility

Abstract

As the end-users increasingly can provide flexibility to the power system, it is important to consider how this flexibility can be activated as a resource for the grid. Electricity network tariffs is one option that can be used to activate this flexibility. Therefore, by designing efficient grid tariffs, it might be possible to reduce the total costs in the power system by incentivizing a change in consumption patterns. This paper provides a methodology for optimal grid tariff design under decentralized decision-making and uncertainty in demand, power prices, and renewable generation. A bilevel model is formulated to adequately describe the interaction between the end-users and a distribution system operator. In addition, a centralized decision-making model is provided for benchmarking purposes. The bilevel model is reformulated as a mixed-integer linear problem solvable by branch-and-cut techniques. Results based on both deterministic and stochastic settings are presented and discussed. The findings suggest how electricity grid tariffs should be designed to provide an efficient price signal for reducing aggregate network peaks.

The Economics of Demand-side Flexibility in Distribution Grids

“…The UL variables will not be impacted, as the DSO will take a unique decision regarding network investment and curtailment for all the scenarios, taking into account the probability of their occurrence. Such a formulation has been used in Gabriel et al (2013) and Askeland et al (2020).…”

Duck Curve Aware Dynamic Pricing and Battery Scheduling Strategy Using Reinforcement Learning

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