Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method

Aghaei, Jamshid; Amjady, Nima; Shayanfar, Heidar Ali

doi:10.1016/j.asoc.2011.02.022

Cited by 150 publications

(70 citation statements)

References 28 publications

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“…Augmented-weighted epsilon-constraint technique is suggested to remedy this deficiency. The details of incorporating lexicographic optimization and augmented-weighted epsilon-constraint technique have been described in our previous paper in the area [37,38]. To avoid tautology in writing, these matters have not been repeated in this paper.…”

Section: Multiobjective Mathematical Programming (Mmp)mentioning

confidence: 99%

“…For a general multi-objective optimization problem of (25) (40) where, the superscript U and SN refer to the value of the objective function in the utopia and pseudo nadir points as shown in (32) and (36), respectively. The constraints of the MMP problem should be also considered in each of these optimization subproblems in addition to the objective function constraints mentioned in (38). By solving each optimization subproblem, one Pareto-optimal solution is obtained in the ε-constraint technique.…”

Section: Multiobjective Mathematical Programming (Mmp)mentioning

confidence: 99%

“…In order to choose the best compromise solution among the obtained Pareto optimal solutions by the ε-constraint method, a fuzzy decision maker is proposed which can softly select the most preferred compromise solution among the Pareto solutions [29,[37][38][39][40][41][42].For this purpose, the fuzzy decision maker calculates a linear membership function for each objective function in each Pareto optimal solution, which measures the relative distance between the value of the objective function in the Pareto optimal solution from its values in the respective utopia and pseudo nadir points. The mathematical formulation of these membership functions for the MMP market clearing problem is as follows:…”

Section: A Fuzzy Decision Makermentioning

confidence: 99%

“…Step 4: The feasible optimization sub-problems in (38) are solved applying the presented MMP solution method to produce the Pareto efficient solution while the infeasible ones are discarded.…”

Section: Multiobjective Mathematical Programming (Mmp)mentioning

confidence: 99%

See 3 more Smart Citations

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Aghaei

Ahmadi

Rabiee

et al. 2015

Applied Soft Computing

Self Cite

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In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-head power discharge characteristics of hydro generating units and spillage of reservoirs. Besides, system uncertainties including the generating units' contingencies and price uncertainty are explicitly considered in the stochastic market clearing scheme. For the stochastic modeling of probable multiobjective optimization scenarios, a lattice Monte Carlo simulation has been adopted to have a better coverage of the system uncertainty spectrum. Consequently, the resulting multiobjective optimization scenarios should concurrently optimize competing objective functions including GENeration COmpany's (GENCO's) profit maximization and thermal units' emission minimization. Accordingly, the ε-constraint method is used to solve the multiobjective optimization problem and generate the Pareto set. Then, a fuzzy satisfying method is employed to choose the most preferred solution among all Pareto optimal solutions. The performance of the presented method is verified in different case studies. The results obtained from ε-constraint method is compared with those reported by weighted sum method, evolutionary programming-based interactive Fuzzy satisfying method, differential evolution, quantumbehaved particle swarm optimization and hybrid multi-objective cultural algorithm, verifying the superiority of the proposed approach. Abstract-In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-head power discharge characteristics of hydro generating units and spillage of reservoirs. Besides, system uncertainties including the generating units' contingencies and price uncertainty are explicitly considered in the stochastic market clearing scheme. For the stochastic modeling of probable multiobjective optimization scenarios, a lattice Monte Carlo simulation has been adopted to have a better coverage of the system uncertainty spectrum. Consequently, the resulting multiobjective optimization scenarios should concurrently optimize competing objective functions including GENeration COmpany's (GENCO's) profit maximization and thermal units' emission minimization. Accordingly, the ε-constraint method is used to solve the multiobjective optimization problem and generate the Pareto set. Then, a fuzzy satisfying method is employed to choose the most preferred solution among all Pareto optimal solutions. The perfo...

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Section: Multiobjective Mathematical Programming (Mmp)mentioning

confidence: 99%

Section: Multiobjective Mathematical Programming (Mmp)mentioning

confidence: 99%

Section: A Fuzzy Decision Makermentioning

confidence: 99%

Section: Multiobjective Mathematical Programming (Mmp)mentioning

confidence: 99%

See 2 more Smart Citations

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Aghaei

Ahmadi

Rabiee

et al. 2015

Applied Soft Computing

Self Cite

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“…He/She will encrypt the data with public key of desktop user. Thus desktop user will access data with its private key [48][49] [50]. …”

Section: Key Management At Centralized Servermentioning

confidence: 99%

Review of Key Management and Distribution Technique for Data Dynamics for Storage Security in Cloud Computing

Kumar¹,

Sheetalani²

2017

IOSR JCE

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Incentive Programs Caused by the Carbon Capture Utilization and Storage Technology Profit's Effect: Optimal Configuration and Energy Planning of Hybrid Microgrid Involving INVELOX Turbine

Jirdehi

Shaterabadi

2020

Energy Tech

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Herein, optimal configuration and microgrid's energy control based on day-ahead planning is proposed. For this purpose, fossil fuel resources are equipped with carbon capture utilization and storage (CCUS) technologies, and INVELOX turbines are proposed in microgrid's planning. The microgrid's overall contamination and cost are considered as objective functions. To encourage the consumers to utilize renewable resources, obtained profit from CCUS is assigned as incentive programs for buying their extra energy. Also, the problem is modeled as a mixed-integer linear programming (MILP), and the epsilon constraint and fuzzy satisfying approach are utilized to tackle and accomplish the best and optimal solution. The outcomes show that overall costs and contamination are

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Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method

Cited by 150 publications

References 28 publications

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Review of Key Management and Distribution Technique for Data Dynamics for Storage Security in Cloud Computing

Incentive Programs Caused by the Carbon Capture Utilization and Storage Technology Profit's Effect: Optimal Configuration and Energy Planning of Hybrid Microgrid Involving INVELOX Turbine

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