Enhanced Lagrange relaxation for the optimal unit commitment of identical generating units

Nikolaidis, Pavlos; Poullikkas, Andreas

doi:10.1049/iet-gtd.2020.0410

Cited by 17 publications

(11 citation statements)

References 27 publications

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“…The novel four stage solution methodology for mixed generation UCP 103 Various optimization methods including classical, heuristics, meta-heuristics, and hybrid have been reported to be applied to solve the complex UCP problem in renewable integrated environment. 124,125 In industrial practice, however, use of Mixed Integer Linear Programming (MILP) is taking over the classical Lagrangian Relaxation (LR) method due to its proven advantages. 126 CPLEX, CBC, and FICO Xpress etc are some of the commercial software available for solving MILP-based UCP formulations.…”

Section: Solution Methodologies and Test Bedsmentioning

confidence: 99%

Unit commitment problem in renewable integrated environment with storage: A review

Tiwari

Dwivedi

Dave

et al. 2021

Int Trans Electr Energ Syst

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Section: Solution Methodologies and Test Bedsmentioning

confidence: 99%

Unit commitment problem in renewable integrated environment with storage: A review

Tiwari

Dwivedi

Dave

et al. 2021

Int Trans Electr Energ Syst

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“…In addition, it occurs advantageous in convergence times in contrast to heuristic and meta-heuristic alternatives which must deal with the burden of exploration/exploitation trade-offs [29]. Compared to mathematical techniques which commonly rely on dual optimization, the priority-list approach does not suffer from the identical heat-rate sensitivity; this forms a great advantage in autonomous systems which consist of several identical generating units in terms of heat-rate coefficients and start-up costs [4].…”

Section: Enhanced Priority-list Schemes Formulationmentioning

confidence: 99%

“…Current efforts aiming to shift towards de-carbonization give rise to remarkable challenges for power systems and their operators [4]. The depletion of fossil-fuel reserves, global warming and associated extreme weather conditions have motivated European Union (EU) to expand the share of intermittent renewable energy sources (RES) for electricity production.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast to conventional systems that can be carefully timed to be dispatched and contribute to generation, renewable sources are strictly correlated to imperfectly predictable and uncontrollable weather conditions. In this regard, unit commitment becomes one of the highest priority optimization problem by which the adequacy of a power system can be evaluated and planned-ahead to offer a large profitable return [8]. The added volatility in net load caused by the increasing penetration of renewable generation have motivated the study of alternative approaches that account for the necessary flexibility, without affecting the stable operation of conventional power plants.…”

Section: Introductionmentioning

confidence: 99%

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Increasing the Photovoltaic Hosting Capacity in Autonomous Grids and Microgrids via Enhanced Priority-List Schemes and Storage

Nikolaidis

Poullikkas

2021

Green Energy Sustain

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European Union has seen a rapid increase in renewable energy sources during the last decade. The variability and uncertainty caused by the increased penetrations of renewable generation must be properly considered in day-ahead unit commitment to retain the stable operation of conventional power plants. In this work, we present an enhanced method to determine the hosting capacity of photovoltaic energy in an autonomous grid. Based on optimal unit commitment schedules derived from priority list-schemes, we examine the potential of increasing the hosting capacity performing annual simulations for different scenarios in the presence of electricity storage. According to the obtained results, the application of storage eliminates the reliability expenses of load shedding and spinning reserve deficits. Hence, the actual hosting capacity is appropriately retrieved based on the renewable generation curtailment during each case study. However, sustainable solutions are achieved at higher penetration levels, reaching a near of 20% with respect to photovoltaic systems. The proposed solution could be efficiently utilized to determine the photovoltaic hosting capacity of microgrids in islanded or interconnected mode.

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“…The probability rate, for each GA's optimization variable (weights of LP), of being mutated was 1%. Generating random directions that are adaptive with respect to the last successful generation, the algorithm selects those directions for the weights and step length that satisfy the pre-determined bounds and linear constraints [37].…”

Section: Proposed Genetic Algorithm Modelmentioning

confidence: 99%

A Hybrid Optimization Approach for Autonomy Enhancement of Nearly-Zero-Energy Buildings Based on Battery Performance and Artificial Neural Networks

et al. 2020

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Reducing the primary energy consumption in buildings and simultaneously increasing self-consumption from renewable energy sources in nearly-zero-energy buildings, as per the 2010/31/EU directive, is crucial nowadays. This work solved the problem of nearly zeroing the net grid electrical energy in buildings in real time. This target was achieved using linear programming (LP)—a convex optimization technique leading to global solutions—to optimally decide the daily charging or discharging (dispatch) of the energy storage in an adaptive manner, in real time, and hence control and minimize both the import and export grid energies. LP was assisted by equally powerful methods, such as artificial neural networks (ANN) for forecasting the building’s load demand and photovoltaic (PV) on a 24 hour basis, and genetic algorithm (GA)—a heuristic optimization technique—for driving the optimum dispatch. Moreover, to address the non-linear nature of the battery and model the energy dispatch in a more realistic manner, the proven freeware system advisor model (SAM) of National Renewable Energy Laboratory (NREL) was integrated with the proposed approach to give the final dispatch. Assessing the case of a building, the results showed that the annual hourly profile of the import and export energies was smoothed and flattened, as compared to the cases without storage and/or using a conventional controller. With the proposed approach, the annual aggregated grid usage was reduced by 53% and the building’s annual energy needs were covered by the renewable energy system at a rate of 60%. It was therefore concluded that the proposed hybrid methodology can provide a tool to maximize the autonomy of nearly-zero-energy buildings and bring them a step closer to implementation.

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Enhanced Lagrange relaxation for the optimal unit commitment of identical generating units

Cited by 17 publications

References 27 publications

Unit commitment problem in renewable integrated environment with storage: A review

Unit commitment problem in renewable integrated environment with storage: A review

Increasing the Photovoltaic Hosting Capacity in Autonomous Grids and Microgrids via Enhanced Priority-List Schemes and Storage

A Hybrid Optimization Approach for Autonomy Enhancement of Nearly-Zero-Energy Buildings Based on Battery Performance and Artificial Neural Networks

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