IDEAS home Printed from https://ideas.repec.org/f/plu234.html
   My authors  Follow this author

Carlo Lucheroni

Personal Details

First Name:Carlo
Middle Name:
Last Name:Lucheroni
Suffix:
RePEc Short-ID:plu234

Affiliation

Universita' di Camerino (University of Camerino)

http://www.unicam.it
Italy, Camerino (MC)

Research output

as
Jump to: Articles

Articles

  1. Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
  2. Carlo Lucheroni & Carlo Mari, 2018. "Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach," Energies, MDPI, vol. 11(3), pages 1-21, March.
  3. Lucheroni, Carlo & Mari, Carlo, 2017. "CO2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis," Applied Energy, Elsevier, vol. 190(C), pages 278-290.
  4. Carlo Lucheroni, 2012. "A hybrid SETARX model for spikes in tight electricity markets," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(1), pages 13-49.
  5. Carlo Lucheroni, 2010. "Stochastic models of resonating markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(1), pages 77-88, June.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.

    Cited by:

    1. Anderson Mitterhofer Iung & Fernando Luiz Cyrino Oliveira & André Luís Marques Marcato, 2023. "A Review on Modeling Variable Renewable Energy: Complementarity and Spatial–Temporal Dependence," Energies, MDPI, vol. 16(3), pages 1-24, January.
    2. Li, Jinghua & Zhou, Jiasheng & Chen, Bo, 2020. "Review of wind power scenario generation methods for optimal operation of renewable energy systems," Applied Energy, Elsevier, vol. 280(C).
    3. Jafarzadeh Ghoushchi, Saeid & Manjili, Sobhan & Mardani, Abbas & Saraji, Mahyar Kamali, 2021. "An extended new approach for forecasting short-term wind power using modified fuzzy wavelet neural network: A case study in wind power plant," Energy, Elsevier, vol. 223(C).
    4. Zhang, Wenyu & Zhang, Lifang & Wang, Jianzhou & Niu, Xinsong, 2020. "Hybrid system based on a multi-objective optimization and kernel approximation for multi-scale wind speed forecasting," Applied Energy, Elsevier, vol. 277(C).
    5. Zhao, Xinyu & Bai, Mingliang & Yang, Xusheng & Liu, Jinfu & Yu, Daren & Chang, Juntao, 2021. "Short-term probabilistic predictions of wind multi-parameter based on one-dimensional convolutional neural network with attention mechanism and multivariate copula distribution estimation," Energy, Elsevier, vol. 234(C).
    6. Lan, Hai & Zhang, Chi & Hong, Ying-Yi & He, Yin & Wen, Shuli, 2019. "Day-ahead spatiotemporal solar irradiation forecasting using frequency-based hybrid principal component analysis and neural network," Applied Energy, Elsevier, vol. 247(C), pages 389-402.
    7. Yang, Hongming & Liang, Rui & Yuan, Yuan & Chen, Bowen & Xiang, Sheng & Liu, Junpeng & Zhao, Huan & Ackom, Emmanuel, 2022. "Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data," Applied Energy, Elsevier, vol. 313(C).
    8. Belqasem Aljafari & Subramanian Vasantharaj & Vairavasundaram Indragandhi & Rhanganath Vaibhav, 2022. "Optimization of DC, AC, and Hybrid AC/DC Microgrid-Based IoT Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-30, September.
    9. Zhang, Yi & Cheng, Chuntian & Cao, Rui & Li, Gang & Shen, Jianjian & Wu, Xinyu, 2021. "Multivariate probabilistic forecasting and its performance’s impacts on long-term dispatch of hydro-wind hybrid systems," Applied Energy, Elsevier, vol. 283(C).
    10. Carlo Lucheroni & Carlo Mari, 2021. "Internal hedging of intermittent renewable power generation and optimal portfolio selection," Annals of Operations Research, Springer, vol. 299(1), pages 873-893, April.
    11. Kleiman, Rachel M. & Characklis, Gregory W. & Kern, Jordan D. & Gerlach, Robin, 2021. "Characterizing weather-related biophysical and financial risks in algal biofuel production," Applied Energy, Elsevier, vol. 294(C).

  2. Carlo Lucheroni & Carlo Mari, 2018. "Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach," Energies, MDPI, vol. 11(3), pages 1-21, March.

    Cited by:

    1. Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
    2. Carlo Mari, 2020. "Stochastic NPV Based vs Stochastic LCOE Based Power Portfolio Selection Under Uncertainty," Energies, MDPI, vol. 13(14), pages 1-18, July.
    3. Sung-Hyun Hwang & Mun-Kyeom Kim & Ho-Sung Ryu, 2019. "Real Levelized Cost of Energy with Indirect Costs and Market Value of Variable Renewables: A Study of the Korean Power Market," Energies, MDPI, vol. 12(13), pages 1-18, June.
    4. Carlo Mari, 2018. "CO 2 Price Volatility Effects on Optimal Power System Portfolios," Energies, MDPI, vol. 11(7), pages 1-18, July.
    5. Carlo Lucheroni & Carlo Mari, 2021. "Internal hedging of intermittent renewable power generation and optimal portfolio selection," Annals of Operations Research, Springer, vol. 299(1), pages 873-893, April.

  3. Lucheroni, Carlo & Mari, Carlo, 2017. "CO2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis," Applied Energy, Elsevier, vol. 190(C), pages 278-290.

    Cited by:

    1. Aquila, Giancarlo & Coelho, Eden de Oliveira Pinto & Bonatto, Benedito Donizeti & Pamplona, Edson de Oliveira & Nakamura, Wilson Toshiro, 2021. "Perspective of uncertainty and risk from the CVaR-LCOE approach: An analysis of the case of PV microgeneration in Minas Gerais, Brazil," Energy, Elsevier, vol. 226(C).
    2. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2019. "Assessing Renewable Energy Sources for Electricity (RES-E) Potential Using a CAPM-Analogous Multi-Stage Model," Energies, MDPI, vol. 12(19), pages 1-20, September.
    3. Huthaifa Sameeh Alqaralleh & Ahmad Al-Saraireh & Alessandra Canepa, 2021. "Energy Market Risk Management under Uncertainty: A VaR Based on Wavelet Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 130-137.
    4. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2018. "Pollutant versus non-pollutant generation technologies: a CML-analogous analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(1), pages 199-212, December.
    5. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Antelo, Susana Iglesias & Soares, Isabel, 2017. "Energy planning and modern portfolio theory: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 636-651.
    6. Tran, Thomas T.D. & Smith, Amanda D., 2018. "Incorporating performance-based global sensitivity and uncertainty analysis into LCOE calculations for emerging renewable energy technologies," Applied Energy, Elsevier, vol. 216(C), pages 157-171.
    7. Carlo Mari, 2020. "Stochastic NPV Based vs Stochastic LCOE Based Power Portfolio Selection Under Uncertainty," Energies, MDPI, vol. 13(14), pages 1-18, July.
    8. Tazi, Nacef & Safaei, Fatemeh & Hnaien, Faicel, 2022. "Assessment of the levelized cost of energy using a stochastic model," Energy, Elsevier, vol. 238(PB).
    9. Shen, Wei & Chen, Xi & Qiu, Jing & Hayward, Jennifier A & Sayeef, Saad & Osman, Peter & Meng, Ke & Dong, Zhao Yang, 2020. "A comprehensive review of variable renewable energy levelized cost of electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    10. Zhang, Shuang & Zhao, Tao & Xie, Bai-Chen, 2018. "What is the optimal power generation mix of China? An empirical analysis using portfolio theory," Applied Energy, Elsevier, vol. 229(C), pages 522-536.
    11. Carlo Mari, 2018. "CO 2 Price Volatility Effects on Optimal Power System Portfolios," Energies, MDPI, vol. 11(7), pages 1-18, July.
    12. Aquila, Giancarlo & Nakamura, Wilson Toshiro & Junior, Paulo Rotella & Souza Rocha, Luiz Celio & de Oliveira Pamplona, Edson, 2021. "Perspectives under uncertainties and risk in wind farms investments based on Omega-LCOE approach: An analysis in São Paulo state, Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    13. Maria del Carmen Gomez-Rios & Dora Carmen Galvez-Cruz, 2021. "Simulation of Levelized Costs of Electricity Considering Externalities," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-23, Octubre -.
    14. Carlo Lucheroni & Carlo Mari, 2021. "Internal hedging of intermittent renewable power generation and optimal portfolio selection," Annals of Operations Research, Springer, vol. 299(1), pages 873-893, April.
    15. Gong, Xu & Shi, Rong & Xu, Jun & Lin, Boqiang, 2021. "Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective," Applied Energy, Elsevier, vol. 285(C).
    16. Carlo Lucheroni & Carlo Mari, 2018. "Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach," Energies, MDPI, vol. 11(3), pages 1-21, March.

  4. Carlo Lucheroni, 2012. "A hybrid SETARX model for spikes in tight electricity markets," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(1), pages 13-49.

    Cited by:

    1. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    2. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    3. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    4. Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
    5. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

  5. Carlo Lucheroni, 2010. "Stochastic models of resonating markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(1), pages 77-88, June.

    Cited by:

    1. Carlo Lucheroni, 2012. "A hybrid SETARX model for spikes in tight electricity markets," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(1), pages 13-49.
    2. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models or electricity spot prices," MPRA Paper 20546, University Library of Munich, Germany.
    3. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Carlo Lucheroni should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.