Impact of CCGT Start-Up Flexibility and Cycling Costs Toward Renewables Integration

Hermans, Mathias; Bruninx, Kenneth; Delarue, Erik

doi:10.1109/tste.2018.2791679

Cited by 27 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most relevant to our research are those studies which investigate the operation of conventional power stations under VRE penetration, which has generally been assessed by grid simulation using dispatch models [2,4,5,9e11,23e29]. Simulation studies on cycling have been conducted on a range of power systems including the U.S. Western Interconnection [27], European interconnections [4,28], ERCOT [11], Ireland [10,11,23], GB [2], the Netherlands [24], Germany [5,9,25], Finland [11,30], Spain [29] and California [26]. The GB power system has been studied in simulation in [6], which makes predictions for ramping, part-loading and startups to 2020 under four scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ramping, measured by rate of change in production, is found to increase by around 50% in [9], while in [10] the number of hours of severe ramping (defined as a change in load of over 50% in under 1 h) per year increases sharply from < 10 to approximately 30 per CCGT between 30% and 40% VRE penetration. Other simulation studies at different penetrations predict total startups to increase: by roughly double from 10% to 40% penetration for a test system based on the Spanish grid [29] and by approximately 6 times from 0% to 27% for Ireland [23].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Estimating the impact of variable renewable energy on base-load cycling in the GB power system

Mars

O’Sullivan

Keppo

2020

Energy

View full text Add to dashboard Cite

Between 2009 and 2017 the share of wind and solar energy sources in the GB electricity generation mix increased from 2.5% to 17%. Due to the variable nature of these renewable sources, large thermal power stations designed for constant base-load operation have been required to operate more flexibly to compensate for fluctuations in renewable generation. This flexible operation results in increased thermal stress and reduced efficiency causing increased operation, maintenance and fuel costs for these assets. In this paper we present the results of what is, to the best of our knowledge, the first empirical study on the impact of renewables generation on startups, ramping and part-loading (collectively, 'cycling') of baseload generators. We develop regression models using half-hourly generation data from 2009 to 2017 that capture the impact of increased renewable penetration while taking into account confounding factors including seasonality and demand. We find that with 2009-levels of renewable generation, cycling in 2017 would have been less severe, with 20% fewer startups. We also present estimates for cycling under National Grid Future Energy Scenarios to 2030 with implications for investment in generation assets. Additionally, the dataset derived in this research is made available and comprises the first open-access dataset on cycling.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Estimating the impact of variable renewable energy on base-load cycling in the GB power system

Mars

O’Sullivan

Keppo

2020

Energy

View full text Add to dashboard Cite

show abstract

“…Their integration has increased the cycling costs of thermal generators [4]. This has led to an overall increase in maintenance cost of thermal generators [5]. To lower the variability and uncertainty of RES integration, both robust and stochastic optimisation framework are used for optimal scheduling of RES and thermal generators [6].…”

Section: Introductionmentioning

confidence: 99%

“…The penalty cost is represented by γ, which is the cost imposed for not achieving the RES obligation requirement and π ω is the probability of each scenario. The generator cost function is a quadratic equation as shown in (5) where the units for the cost coefficients are $/M W h 2 , $/M W h, and $/h and the generator spinning reserve cost is a linear function as shown in (6).…”

mentioning

confidence: 99%

Multi-objective stochastic economic dispatch with maximal renewable penetration under renewable obligation

et al. 2020

View full text Add to dashboard Cite

“…Investigation of lengths for the rolling horizon was done by [19] to find the optimal use of power plant flexibility considering the start-up and maintenance related problems of CCGT power plants.…”

Section: Introductionmentioning

confidence: 99%

Effect of Different Interval Lengths in a Rolling Horizon MILP Unit Commitment with Non-Linear Control Model for a Small Energy System

2019

View full text Add to dashboard Cite

In this paper, a fixed electricity producer park of both a short- and long-term renewable energy storage (e.g., battery, power to gas to power) and a conventional power plant is combined with an increasing amount of installed volatile renewable power. For the sake of simplicity, the grid is designed as a single copper plate with island restrictions and constant demand of 1000 MW; the volatile input is deducted from scaled 15-min input data of German grid operators. A mixed integer linear programming model is implemented to generate an optimised unit commitment (UCO) for various scenarios and configurations using CPLEX® as the problem solver. The resulting unit commitment is input into a non-linear control model (NLC), which tries to match the plan of the UCO as closely as possible. Using the approach of a rolling horizon the result of the NLC is fed back to the interval of the next optimisation run. The problem’s objective is set to minimise CO2 emissions of the whole electricity producer park. Different interval lengths are tested with perfect foresight. The results gained with different interval lengths are compared to each other and to a simple heuristic approach. As non-linear control model a characteristic line model is used. The results show that the influence of the interval length is rather small, which leads to the conclusion that realistic forecast lengths of two days can be used to achieve not only a sufficient quality of solutions, but shorter computational times as well.

show abstract

Impact of CCGT Start-Up Flexibility and Cycling Costs Toward Renewables Integration

Cited by 27 publications

References 10 publications

Estimating the impact of variable renewable energy on base-load cycling in the GB power system

Estimating the impact of variable renewable energy on base-load cycling in the GB power system

Multi-objective stochastic economic dispatch with maximal renewable penetration under renewable obligation

Effect of Different Interval Lengths in a Rolling Horizon MILP Unit Commitment with Non-Linear Control Model for a Small Energy System

Contact Info

Product

Resources

About