A game-theoretic approach for optimal time-of-use electricity pricing

By Peng Yang, Gongguo Tang, Arye Nehorai. IEEE Transactions on Power Systems, 2013

440 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/e38d0e69b2926690b15764fd28bb0c6c42ae8302

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Mengmeng Yu
2. Seung Ho Hong
3. Nizar Zorba
4. Christos V. Verikoukis
5. John S. Vardakas
6. Renzhi Lu
7. Ozan Erdinc

Citations in the corpus

• A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms (2015, background): “efforts have been made to design an accurate forecasting model [8], [219], [240]–[242].”
• A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach (2016, background): “Previous game theory-based DR studies are categorized by two kinds of models, one is the game between the utility and users aiming to help the utility regulate optimal prices which are later used for inducing users to adjust their energy usages [16], [17], [19]; the other game focuses on inside of t”