Optimal coordinated wind-hydro bidding strategies in day-ahead markets

Nieta, Agustín A. Sánchez de la; Contreras, Javier; Muñoz, José I.

doi:10.1109/tpwrs.2012.2225852

Cited by 117 publications

(54 citation statements)

References 17 publications

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“…In this paper, the parasitic power is assumed constant. Constraints (14) and (15) impose that the electric power from the SF and TES depends on the efficiencies h 1 and h 3 associated with the thermal power of the SF, q FE c;k , and the storage power, q SE c;k , respectively. Constraints (16) set the bounds Q PB c and Q PB c for the sum of the power from the SF and TES.…”

Section: General Milp Approachmentioning

confidence: 99%

“…In Refs. [14,15], a modelling for wind power and pumped-storage hydro power plants shows advantages of not only minimizing curtailments and energy imbalances, but also an enhancement on the dispatchability relatively to the standalone wind power plants. Harmonization schemes between wind power and concentrating solar power (CSP) plants are important for the Southern Iberian Peninsula [16], due to favourable wind resources and solar irradiation levels near load centres.…”

Section: Introductionmentioning

confidence: 99%

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Bilevel approach to wind-CSP day-ahead scheduling with spinning reserve under controllable degree of trust

et al. 2016

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a b s t r a c tThis paper proposes a day-ahead schedule harmonization between wind power plants and concentrating solar thermal power plants having thermal energy storage. The negative correlation between wind power and solar power is computed and an artificial neural network method estimates the power. The schedule is carried out by a bilevel mathematical programming approach. The upper-level determines energy and spinning reserve schedule by the maximization of profit subject to all lower-level problems. Lower-level problems minimize the post-contingency power output. A controllable degree of trust on the schedule is introduced based on n e K security criterion for worst-case contingency. The approach uses duality theory and problem approximations for a conversion into an equivalent mixed-integer linear programming problem. A case study is presented to illustrate the effectiveness of the approach for power producers not only with transmission constraints, but also valuing safekeeping on the day-ahead schedule to ensure a degree trust on the satisfaction of compromises within electricity markets.

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Section: General Milp Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bilevel approach to wind-CSP day-ahead scheduling with spinning reserve under controllable degree of trust

et al. 2016

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“…Thus, how to effectively quantify the risk of ESI is still an urgent problem to be solved. Value-at-risk (VaR) and conditional value-at-risk (CVaR), as well-known risk measures, have been widely used in various energy management problems for different entities in the electricity market such as retailers [9], producers [10][11][12], distribution companies [13], and in generation operation planning [14], optimal power flow [15] as well as coordinated energy trading problems [16,17]. improve the forecasting accuracy, uncertain energy consumption fashion in local-area still poses an enormous dilemma regarding the appropriate implementation of prediction algorithms.…”

Section: Introductionmentioning

confidence: 99%

Operating Strategy for Local-Area Energy Systems Integration Considering Uncertainty of Supply-Side and Demand-Side under Conditional Value-At-Risk Assessment

Shi

Wang²,

et al. 2017

Sustainability

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Abstract:To alleviate environmental pollution and improve the energy usage efficiency of terminals, energy systems integration (ESI) has become an important paradigm in the energy structure evolution. Power, gas and heat systems are becoming tightly interlinked with each other in ESI. The dispatching strategy of local-area ESI has significant impact on its operation. In this paper, a local-area ESI operational scheduling model based on conditional value-at-risk (CVaR) is proposed to minimize expected operational cost, which considers the uncertainty of energy supply-side and demand-side as well as multi-energy network constraints, including electrical network, thermal network and gas network. The risk cost is analyzed comprehensively under the condition of under-or overestimated cost. On this basis, a hybrid method combining particle swarm optimization with interior point algorithm is executed to compute the optimal solutions of two-stage multi-period mixed-integer convex model. Finally, a case study is performed on ESI to demonstrate the effectiveness of the proposed method.

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“…Also, schemes based on the coordination of wind and hydro power, specially pumped-storage hydro power plants [8,9], unveiled an improvement on minimization of curtailment, energy imbalance and dispatchability. Furthermore, electrical vehicles connection to the power grid are expected to be used as controllable loads and a convenient operation with suitable market design may help accommodate more wind power [10].…”

Section: Introductionmentioning

confidence: 99%

Wind-CSP short-term coordination by MILP approach

Pousinho

Silva

Mendes

et al. 2014

3rd Renewable Power Generation Conference (RPG 2014)

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This paper is on the maximization of total profit in a dayahead market for a price-taker producer needing a short-term scheduling for wind power plants coordination with concentrated solar power plants, having thermal energy storage systems. The optimization approach proposed for the maximization of profit is a mixed-integer linear programming problem. The approach considers not only transmission grid constraints, but also technical operating constraints on both wind and concentrated solar power plants. Then, an improved short-term scheduling coordination is provided due to the more accurate modelling presented in this paper. Computer simulation results based on data for the Iberian wind and concentrated solar power plants illustrate the coordination benefits and show the effectiveness of the approach.

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Optimal coordinated wind-hydro bidding strategies in day-ahead markets

Cited by 117 publications

References 17 publications

Bilevel approach to wind-CSP day-ahead scheduling with spinning reserve under controllable degree of trust

Bilevel approach to wind-CSP day-ahead scheduling with spinning reserve under controllable degree of trust

Operating Strategy for Local-Area Energy Systems Integration Considering Uncertainty of Supply-Side and Demand-Side under Conditional Value-At-Risk Assessment

Wind-CSP short-term coordination by MILP approach

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