@article{braga_flor_strategic_2022,
	title = {Strategic observation of power grids for reliable monitoring},
	volume = {138},
	issn = {0142-0615},
	url = {https://www.sciencedirect.com/science/article/pii/S0142061522000060},
	doi = {10.1016/j.ijepes.2022.107959},
	abstract = {In this paper, strategic observation of power grids refers to the optimized placement of measurements necessary to obtain the most likely operating condition of the grid, achieved in real-time monitoring via the state estimation ({SE}) functionality. The measuring system designed for {SE} considers the types, placement at various grid buses, and the total available measurements, which is crucial for reliable monitoring. The objective to be reached is to find the best places to install additional measuring units, in a limited number divided into pre-specified lots, to reduce data criticalities—whose importance is related to impending unobservability and incapacity of {SE} residual analysis to handle bad data. The process of finding an optimized solution for the meter placement problem is typically combinatorial and of considerable size, which makes metaheuristics the realistic option to solve the issue at hand. Metaheuristics are approximate optimization techniques with a pervasive success story in tackling various complex, real-world combinatorial optimization problems. This paper proposes the combined implementation of greedy randomized adaptive search procedure ({GRASP}), variable neighborhood descent ({VND}), and variable neighborhood search ({VNS}) optimization techniques. Numerical results performed on benchmark power grids ({IEEE} 30- and 118-bus) illustrate the application of the proposed approach and evince that high-quality solutions are achieved (validated by the exhaustive search results) in a computing time adequate for power grid operation planning studies.},
	pages = {107959},
	journaltitle = {International Journal of Electrical Power \& Energy Systems},
	shortjournal = {International Journal of Electrical Power \& Energy Systems},
	author = {Braga Flôr, Vinícius B. and Do Coutto Filho, Milton B. and Stachinni de Souza, Julio C. and Satoru Ochi, Luiz},
	urldate = {2024-07-02},
	date = {2022-06-01},
	keywords = {Optimization, State Estimation, Criticalities, {GRASP}, Metaheuristics, {VND}, {VNS}},
	file = {Braga Flôr et al_2022_Strategic observation of power grids for reliable monitoring.pdf:files/2088/Braga Flôr et al_2022_Strategic observation of power grids for reliable monitoring.pdf:application/pdf;ScienceDirect Snapshot:files/1692/S0142061522000060.html:text/html},
}

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The objective to be reached is to find the best places to install additional measuring units, in a limited number divided into pre-specified lots, to reduce data criticalities—whose importance is related to impending unobservability and incapacity of SE residual analysis to handle bad data. The process of finding an optimized solution for the meter placement problem is typically combinatorial and of considerable size, which makes metaheuristics the realistic option to solve the issue at hand. Metaheuristics are approximate optimization techniques with a pervasive success story in tackling various complex, real-world combinatorial optimization problems. This paper proposes the combined implementation of greedy randomized adaptive search procedure (GRASP), variable neighborhood descent (VND), and variable neighborhood search (VNS) optimization techniques. Numerical results performed on benchmark power grids (IEEE 30- and 118-bus) illustrate the application of the proposed approach and evince that high-quality solutions are achieved (validated by the exhaustive search results) in a computing time adequate for power grid operation planning studies.","pages":"107959","journaltitle":"International Journal of Electrical Power & Energy Systems","shortjournal":"International Journal of Electrical Power & Energy Systems","author":[{"propositions":[],"lastnames":["Braga","Flôr"],"firstnames":["Vinícius","B."],"suffixes":[]},{"propositions":[],"lastnames":["Do","Coutto","Filho"],"firstnames":["Milton","B."],"suffixes":[]},{"propositions":["Stachinni","de"],"lastnames":["Souza"],"firstnames":["Julio","C."],"suffixes":[]},{"propositions":[],"lastnames":["Satoru","Ochi"],"firstnames":["Luiz"],"suffixes":[]}],"urldate":"2024-07-02","date":"2022-06-01","keywords":"Optimization, State Estimation, Criticalities, GRASP, Metaheuristics, VND, VNS","file":"Braga Flôr et al_2022_Strategic observation of power grids for reliable monitoring.pdf:files/2088/Braga Flôr et al_2022_Strategic observation of power grids for reliable monitoring.pdf:application/pdf;ScienceDirect Snapshot:files/1692/S0142061522000060.html:text/html","bibtex":"@article{braga_flor_strategic_2022,\n\ttitle = {Strategic observation of power grids for reliable monitoring},\n\tvolume = {138},\n\tissn = {0142-0615},\n\turl = {https://www.sciencedirect.com/science/article/pii/S0142061522000060},\n\tdoi = {10.1016/j.ijepes.2022.107959},\n\tabstract = {In this paper, strategic observation of power grids refers to the optimized placement of measurements necessary to obtain the most likely operating condition of the grid, achieved in real-time monitoring via the state estimation ({SE}) functionality. 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This paper proposes the combined implementation of greedy randomized adaptive search procedure ({GRASP}), variable neighborhood descent ({VND}), and variable neighborhood search ({VNS}) optimization techniques. 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