Optimal use of incentive and price based demand response to reduce costs and price volatility

By Ailin Asadinejad, Kevin Tomsovic. 2017

163 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/f184741e34d622e59f1e3703071b5a556daaedd7

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. Renzhi Lu
2. Seung Ho Hong
3. Eslam Al Hassan
4. Azah Mohamed
5. Maytham S. Ahmed
6. Hussain Shareef
7. Mengmeng Yu

In Renewable Energy, Sustainability and the Environment

1. Seung Ho Hong

Citations in the corpus

• Review on Home Energy Management System Considering Demand Responses, Smart Technologies, and Intelligent Controllers (2018, background): “Pricebased programs provide different electricity tariff prices and utilize a signal to help consumers obtain improved power [43], [44].”
• Incentive-based demand response for smart grid with reinforcement learning and deep neural network (2019, background): “About 93% of the peak load reductions from existing DR resources in the US is achieved via incentive-based DR programs [12].”