Multi-objective evolutionary algorithm in tables for placement of SCADA and PMU considering the concept of Pareto Frontier

Vigliassi, Marcos Paulo; Massignan, Julio A. D.; Delbem, Alexandre Cláudio Botazzo; London, João Bosco Augusto

doi:10.1016/j.ijepes.2018.10.026

Cited by 22 publications

(14 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By letting F(x) = 0, F(y) = 0, F(z) = 0, i.e., letting the rate of strategy change be zero, we can obtain the equilibrium points of this dynamic system, which are (0,0,0), (0,0,1), (0,1,0), (1,0,0), (1,1,0), (1,0,1), (0,1,1), and (1,1,1), respectively. These eight equilibrium points constitute the boundary of the domain of this evolutionary game, and the stability of these equilibrium points in this evolutionary system can be obtained by local stability analysis of the Jacobian matrix [57][58][59].…”

Section: Stability Analysis Of the Evolutionary Gamementioning

confidence: 99%

Does Whistleblowing Work for Air Pollution Control in China? A Study Based on Three-party Evolutionary Game Model under Incomplete Information

Yang

2019

Sustainability

View full text Add to dashboard Cite

During China's air pollution campaign, whistleblowing has become an important way for the central government to discover local environmental issues. The three parties involved in whistleblowing are: the central government environmental protection departments, the local government officials, and the whistleblowers. Based on these players, this paper has constructed an Evolutionary Game Model under incomplete information and introduced the expected return as well as replicator dynamics equations of various game agents based on analysis of the game agents, assumptions, and payoff functions of the model in order to study the strategic dynamic trend and stability of the evolutionary game model. Furthermore, this paper has conducted simulation experiments on the evolution of game agents' behaviors by combining the constraints and replicator dynamics equations. The conclusions are: the central environmental protection departments are able to effectively improve the environmental awareness of local government officials by measures such as strengthening punishment on local governments that do not pay attention to pollution issues and lowering the cost of whistleblowing, thus nurturing a good governance and virtuous circle among the central environmental protection departments, local government officials, and whistleblowers. Based on the study above, this paper has provided policy recommendations in the conclusion.

show abstract

Section: Stability Analysis Of the Evolutionary Gamementioning

confidence: 99%

Does Whistleblowing Work for Air Pollution Control in China? A Study Based on Three-party Evolutionary Game Model under Incomplete Information

Yang

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…By analyzing the data in Table 3, it can be seen that the difference of the placement schemes between the two models lies in the locations of the PMUs. For example, 29 PMUs are needed in both models under case 2, and the majority of PMUs are placed at the same location, namely, bus 1, 3,9,12,20,22,24,27,29,30,32,33,35,39,47,51,53,55,57; meanwhile, the rest few PMUs are placed at a different location, namely, bus 4,6,11,15,19,36,41,44,46,49 in multi-objective model and bus 5,7,14,18,38,40,42,43,45,50 in single-objective model. Obviously, the sum of adjacent buses of bus 4,6,11,15,19,36,41,44,46,49 is larger than bus 5,7,14,18,38,40,42,43,45,50. Thus, compared to single-objective models, parts of PMUs in multi-objective models are placed at the buses with more adjacent buses.…”

Section: Numerical Studymentioning

confidence: 99%

“…Apparently, the developed placement model can provide solutions with higher reliability. ,11,12,15,19,20,22,24,26,28,29,30,31, 32,33,35,36,37,38,41,45,46,47,50,51,53,54,56,57 Multi-objective 29 0.00180 1,3,4,6,9,11,12,15,19,20,22,24,27,29,30,32,33,35,36,39,41,44,46,47,49,51,53,55,57 Single-objective 29 0.00298 1,3,5,7,9,12,14,18,20,22,24,27,29,30,32,33,35,38,39,40,42,43,45,47,…”

Section: Numerical Studymentioning

confidence: 99%

“…The redundancy here was formulated as average possibility of observability including random component outages, and full possibility formula was applied to calculate the average possibility of observability in the case of single line outage. Finally, the model was employed to the IEEE-57 bus system, and the results verified that the developed model could provide a placement scheme with higher reliability.Sustainability 2019, 11, 7097 2 of 12 bee colony (ABC) algorithm, modified binary cuckoo optimization algorithm (MBCOA), weighted method, multi-objective evolutionary algorithm-based, were adopted to solve the multi-objective model in [11][12][13][14][15], respectively. In addition, to obtain the final solution from the Pareto front quickly and accurately, the fuzzy satisfying approach was applied in [16,17] and sparse neighborhood surroundings in [18].…”

mentioning

confidence: 99%

See 1 more Smart Citation

A Probabilistic Multi-Objective Model for Phasor Measurement Units Placement in the Presence of Line Outage

Huang

Liu

et al. 2019

Sustainability

View full text Add to dashboard Cite

Optimal phasor measurement units (PMU) placement was developed to determine the number and locations of PMUs on the premise of full observability of the whole network. In order to enhance reliability under contingencies, redundancy should also be considered beside the number of PMUs in optimal phasor measurement units placement problem. Thus, in this paper, a multi-objective model was established to consider the two conflicting components simultaneously, solved by ε-constraint method and the fuzzy satisfying approach. The redundancy here was formulated as average possibility of observability including random component outages, and full possibility formula was applied to calculate the average possibility of observability in the case of single line outage. Finally, the model was employed to the IEEE-57 bus system, and the results verified that the developed model could provide a placement scheme with higher reliability.Sustainability 2019, 11, 7097 2 of 12 bee colony (ABC) algorithm, modified binary cuckoo optimization algorithm (MBCOA), weighted method, multi-objective evolutionary algorithm-based, were adopted to solve the multi-objective model in [11][12][13][14][15], respectively. In addition, to obtain the final solution from the Pareto front quickly and accurately, the fuzzy satisfying approach was applied in [16,17] and sparse neighborhood surroundings in [18]. Furthermore, the accuracy of state estimation was taken into consideration, subject to the constraint of supervisory control and data acquisition (SCADA) measurement data in [19] and the uncertainties of power system conditions in [20].Literatures aforementioned analyzed the system observability from a deterministic view, including two contrary states, i.e., observable or unobservable. However, it was investigated in a probabilistic manner in [21][22][23][24]. In [21], to obtain a PMU placement scheme with unobservable probability resulted from 1st-order and 2nd-order failures of PMUs and line less than the pre-defined threshold, the unobservable probability was calculated iteratively by increasing PMU numbers gradually on the basis of initial PMU placement scheme, until the requirements were met. A multi-objective model was proposed, simultaneously minimizing the PMU cost and unobservable probability under PMU or line failures in [22]. However, random component outages were not taken into consideration in [21] and [22]. In [23], a probabilistic manner was adopted to differentiate the multiple solutions and showed significant priority comparing to measurement redundancy. A solution with maximum observable probability considering random component outages was selected as the final optimal scheme. In addition, when considering multistage PMU placement, the observable probability was regarded as the objective to optimize at each stage [24].In this paper, firstly, APO of all buses in the network was calculated under two different cases, i.e., with and without consideration of single line outages. It is noticeable to consider the effect of single line outag...

show abstract

“…In [14], information theory was used to formulate the PMU placement in terms of mutual information, which was then optimized by means of a greedy algorithm in order to reduce the number of PMU units while guaranteeing complete system observability. In [15,16], respectively, variable neighborhood search heuristic and genetic algorithms were applied for optimizing PMU placement considering minimum observability constraints. In [17], a multi-objective differential evolution algorithm was used to optimize placement cost and measurement reliability.…”

Section: Related Workmentioning

confidence: 99%

Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation

et al. 2019

View full text Add to dashboard Cite

In this work, we address the problem of allocating optical links for connecting automatic circuit breakers in a utility power grid. We consider the application of multi-objective optimization for improving costs and power network reliability. To this end, we propose a novel heuristic for attributing reliability values to the optical links, which makes the optimization converge to network topologies in which nodes with higher power outage indexes receive greater communication resources. We combine our heuristic with a genetic algorithm in order to solve the optimization problem. In order to validate the proposed method, simulations are carried out with real data from the local utility. The obtained results validate the allocation heuristic and show that the proposed algorithm outperforms gradient descent optimization in terms of the provided Pareto front.

show abstract

Multi-objective evolutionary algorithm in tables for placement of SCADA and PMU considering the concept of Pareto Frontier

Cited by 22 publications

References 22 publications

Does Whistleblowing Work for Air Pollution Control in China? A Study Based on Three-party Evolutionary Game Model under Incomplete Information

Does Whistleblowing Work for Air Pollution Control in China? A Study Based on Three-party Evolutionary Game Model under Incomplete Information

A Probabilistic Multi-Objective Model for Phasor Measurement Units Placement in the Presence of Line Outage

Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation

Contact Info

Product

Resources

About