Multiobjective optimization for pricing system security in electricity markets

By Federico E. Milano, Claudio A. Cañizares, M. Invernizzi. 2003

192 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/7a7790ee204e1956f2342e4b87036092c0a89e1e

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In Electrical and Electronic Engineering

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Citations in the corpus

Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security (2009, methodology): “In [ 14 ], a multiobjective approach based on interior point method is used in an optimal powerflow, so that the social benefit and the distance to a maximum loading condition are maximized at the same time.”
Sustainable energy systems: Role of optimization modeling techniques in power generation and supply—A review (2011, methodology): “In order to improve the Loading Margin of the sysem, the current available methods mainly include reactive power anagement [152–154], generation rescheduling [155–158] and oad curtailment [159,160].”
Solving Multi-Objective Economic Dispatch Problem Via Semidefinite Programming (2013, methodology): “The weighted sum method [3], [4] is a well-known technique to reduce a multi-objective optimization problem to a scalar equivalent.”
Probabilistic Optimal Power Flow in Electricity Markets Based on a Two-Point Estimate Method (2006, methodology): “In the context of electricity markets, the Lagrangian multipliers of the power flow equations are of special interest, since they can be directly associated with the system LMPs [16], [17].”
An open source power system analysis toolbox (2005, methodology): “2) VSC-OPF Market Clearing Model: The following optimization problem is used for representing an OPF market clearing model with inclusion of voltage stability constraints, based on what was proposed in [21] and [22]:”
Evenly distributed pareto points in multi-objective optimal power flow (2006, methodology): “Various multi-objective optimization approaches have been utilized, for example, the -constrained method [1], [4], the weighted sum method [2], [3], the goal-attainment method [3], [4], and game theory [5].”