Optimisation of demand response in electric power systems, a review

By A. R. Jordehi. Renewable & Sustainable Energy Reviews, 2019

445 citations recorded by the source corpus.

Abstract Demand response programs offer efficient solutions for many power system problems, such as high generation cost, high demand’s peak to average ratio, high emissions, reliability issues and congestion in generation, transmission and distribution systems. Their main function is to assist power systems during peak demand hours and also during contingencies. They are a subcategory of the family of demand side management (DSM) strategies. DR programs are classified into two broad categories; price-based DR programs and incentive-based DR programs. In order to exploit their full potential, DR programs must be implemented optimally. Such a problem, which here is referred to as “DR optimisation problem”, is a hot research topic and has been frequently researched in the literature. This paper aims to review different research works on DR optimisation problems. Based on the conducted review, some directions for future research are proposed.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8a903255ace7e6b12e4868ab2c1ed02ad036bb8b

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In Control and Systems Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review (2020, methodology): “Classical algorithms used for solving DR scheduling problems are linear programming (LP), nonlinear programming (NLP), mixed-integer linear programming (MILP), and mixed-integer nonlinear programming (MINLP), depending on the formulation of the scheduling problem [282].”