Hydrothermal self-scheduling problem in a day-ahead electricity market

Bisanovic, Smajo; Hajro, Mensur; Dlakic, Muris

doi:10.1016/j.epsr.2008.02.002

Cited by 59 publications

(35 citation statements)

References 18 publications

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“…The water discharge limits are similar to those presented in [23]; however, in the proposed stochastic multiobjective HTSS model the spillage effect is also considered [2]. Also, the initial value of the reservoir, water balance [2], [23], and operating services [16] are considered in the proposed HTSS problem.…”

Section: The Other Constraints Of Hydro Unitsmentioning

confidence: 79%

“…The other constraints of the proposed HTSS problem, as addressed in [2,34], are: time varying start-up cost function, Minimum Up-Time (MUT) and Minimum Down-Time (MDT), and Logical status of commitment. Also, the fuel limit constraints are taken from [7,16].…”

Section: E Other Constrains Of Thermal Unitsmentioning

confidence: 99%

“…Also, the initial value of the reservoir, water balance [2], [23], and operating services [16] are considered in the proposed HTSS problem.…”

Section: The Other Constraints Of Hydro Unitsmentioning

confidence: 99%

“…GENeration COmpanies (GENCOs) uses Price-Based Unit Commitment (PBUC) to maximize their profit but they are not concerning about providing the system load [1]. The UC and PBUC are respectively termed as the Hydro-Thermal Scheduling (HTS) and Hydro-Thermal Self Scheduling (HTSS) [2] for the system with the hydro and thermal units. Different solution methods of the HTSS problem are comprehensively classified into heuristic and analytical methods in [3].…”

Section: Introductionmentioning

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

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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: The Other Constraints Of Hydro Unitsmentioning

confidence: 79%

Section: E Other Constrains Of Thermal Unitsmentioning

confidence: 99%

“…Also, the initial value of the reservoir, water balance [2], [23], and operating services [16] are considered in the proposed HTSS problem.…”

Section: The Other Constraints Of Hydro Unitsmentioning

confidence: 99%

Section: Introductionmentioning

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

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“…Addition to the mentioned constraints, the other constraints of hydro units such as initial and final volume [17], Water balance [37] and operating services [38] are considered in the problem. Details of these constraints are given in mentioned references.…”

Section: C4 the Other Constraints Of Hydro Unitsmentioning

confidence: 99%

MIP-Based Stochastic Security-Constrained Daily Hydrothermal Generation Scheduling

Aghaei

Karami

Muttaqi

et al. 2015

IEEE Systems Journal

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This paper presents the application of a mixedinteger programming (MIP) approach for solving stochastic security-constrained daily hydrothermal generation scheduling (SCDHGS). Power system uncertainties including generating units and branch contingencies and load uncertainty are explicitly considered in the stochastic programming of SCDHGS. The roulette wheel mechanism and lattice Monte Carlo simulation (LMCS) are first employed for random scenario generation wherein the stochastic SCDHGS procedure is converted into its respective deterministic equivalents (scenarios). Then, the generating units are scheduled through MIP over the set of deterministic scenarios for the purpose of minimizing the cost of supplying energy and ancillary services over the optimization horizon (24 h) while satisfying all the operating and network security constraints. To amore realistic modeling of the DHGS problem, in the proposed MIP formulation, the nonlinear valve loading effect, cost, and emission function are modeled in linear form, and prohibited operating zones (POZs) of thermal units are considered. Furthermore, a dynamic ramp rate of thermal units is used, and for the hydro plants, the multiperformance curve with spillage and time delay between reservoirs is considered. To assess the efficiency and powerful performance of the aforementioned method, a typical case study based on the standard IEEE-118 bus system is investigated, and the results are compared to each other in different test systems.

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Smart self-scheduling of Gencos with thermal and energy storage units under price uncertainty

Soroudi

2013

Int. Trans. Electr. Energ. Syst.

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SUMMARY This paper provides a self‐scheduling tool for price taker Gencos. This methodology is based on Robust Optimization (RO) to deal with the uncertainties of market price values in the day‐ahead electricity pool market. The Genco is assumed to be the entity who decides about the operating schedules of its thermal units and Compressed Air Energy Storage units. The benefits of Genco brought by smart grid technology and energy storage systems are investigated in this work. The applicability of the proposed method is analyzed through different scenarios. Copyright © 2013 John Wiley & Sons, Ltd.

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Hydrothermal self-scheduling problem in a day-ahead electricity market

Cited by 59 publications

References 18 publications

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

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

MIP-Based Stochastic Security-Constrained Daily Hydrothermal Generation Scheduling

Smart self-scheduling of Gencos with thermal and energy storage units under price uncertainty

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