MTM2013-48462
Tue, 01/30/2018 - 21:12 — admin
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Julián Cifuentes-Rubiano; Cristina Corchero |
| Journal Title | Journal of Environmental Management |
| Volume | 207 |
| Issue | 1 |
| Pages | 12 |
| Start Page | 432 |
| Journal Date | February 2018 |
| Publisher | Elsevier |
| ISSN Number | 0301-4797 |
| Key Words | research; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emissions reduction; paper |
| Abstract | There are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossil-fueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the medium-term derivative commitments in the optimal generation bidding strategy for the day-ahead electricity market. Two different technologies have been considered: the high-emission technology of thermal coal units and the low-emission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the day-ahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit’s optimal generation bid to the wholesale electricity market such that it maximizes the long-term profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP’s effects on the expected profits and the optimal generation bid. |
| URL | Click Here |
| DOI | 10.1016/j.jenvman.2017.11.010 |
| Preprint | http://hdl.handle.net/2117/114024 |
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Sat, 01/20/2018 - 00:00 — admin
 The paper Stochastic optimal generation bid to electricity markets with emissions risk constraints has been published in the Journal of Environmental Management , Elsevier. This work investigates the influence of the emissions reduction plan and the incorporation of the medium-term derivative commitments in the optimal generation bidding strategy for the day-ahead electricity market. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP's effects on the expected profits and the optimal generation bid. Preprint available at http://hdl.handle.net/2117/114024.
Sat, 12/16/2017 - 00:00 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; J.-Anton Sánchez |
| Conference Name | 4th International Conference on Optimization Methods and Software 2017 |
| Conference Date | 16-21/12/2017 |
| Conference Location | La Havana |
| Type of Work | Invited presentation |
| Key Words | multistage; VSS; wind-BESS VPP; wind power; energy storage; battery; research |
| Abstract | One of the objectives of the FOWGEN project (https://fowgem.upc.edu) was to study the economic feasibility and optimal operation of a wind-BESS Virtual Power Plant (VPP): In [1] an ex-post economic analysis shows the economic viability of a wind-BESS VPP thanks to the optimal operation in day-ahead and ancillary electricity markets; In [2] a new multi-stage stochastic programming model (WBVPP)for the optimal bid of a wind producer both in spot and ancillary services electricity markets is developed.
The work presented here extends the study in [2] with a new methodology to treat the uncertainty, based in forecasting models, and the study of the quality of the stochastic solution.
[1] F-Javier Heredia et al. Economic analysis of battery electric storage systems operating in electricity markets 12th International Conference on the European Energy Market (EEM15), 2015 DOI: 10.1109/EEM.2015.7216739.
[2] F-Javier Heredia et al. On optimal participation in the electricity markets of wind power plants with battery energy storage system. Submitted, under second revision. 2017. |
| URL | Click Here |
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Fri, 07/07/2017 - 10:16 — admin
Thu, 06/01/2017 - 16:26 — admin
 A new multi-stage stochastic programming model for the optimal bid of a wind producer both in spot and
ancillary services electricity markets has been presented inthe conference WindFarms 2017. We analyse the effect of the BESS and the
reserve market to the optimal bidding strategies of the VPP with real data
from the Iberian Electricity Market Operator (OMIE) and wind production data from Gas Natual - Fenosa. The complete presentation can be downloaded from here
Tue, 09/27/2016 - 09:19 — admin
| Publication Type | Tesis de Grau i Màster // BSc and MSc Thesis |
| Year of Publication | 2016 |
| Authors | Maksims Sisovs |
| Director | F.-Javier Heredia |
| Tipus de tesi | MSc Thesis |
| Titulació | "KIC InnoEnergy" Master of Science in Smart Electrical Networks and Systems |
| Centre | Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB) |
| Data defensa | 16/09/2016 |
| Nota // mark | 10 MH (A+ with honours) |
| Key Words | teaching; BEES; battery energy storage systems; electrical vehicle; smart meters; retail energy market; MSc Thesis |
| Abstract | The main focus of this master thesis project is to evaluate the economic, technical and regulatory feasibility of distributed battery energy storage systems (BESS) and the potential opportunity of electricity companies to increase their pro ts through advanced operation in energy services, such as electric energy time-shift, ancillary or electric vehicle incentives in Spanish electricity market. To assess the feasibility, an optimization tool has been developed. This tool simulates energy trading between diff erent market participants with particular features extracted from data analysis and literature. Load consumption pro les had been developed from smart meter real data by applying several data mining techniques. This part had been guided by external collaborating entity Minsait. Electricity market analysis includes the overview of its functionality principles and regulatory side regarding storage adaptation and speci fic service applicability. Market historical prices were used for further electricity trading simulation. A brief technical insight explains current storage situation and tells about high-potential technologies in emerging markets. Benchmark analysis covers several products of battery manufacturers with relevant technical and price information. Spanish electricity market showed low adaptability to distributed BESS solutions: energy arbitrage incomes have resulted being insuficient. Ancillary services, despite promising economic gures, are to a large extent prohibited to be provided by distributed storage. Electric vehicle incentives, though, resulted being of a high interest due to absence of direct investment. |
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Mon, 07/18/2016 - 18:43 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | F.-Javier Heredia; Cristina Corchero; Marlyn D. Cuadrado |
| Conference Name | 28th European Conference on Operational Research |
| Series Title | Conference Handbook |
| Pagination | 322 |
| Conference Date | 3-6/07/2016 |
| Conference Location | Poznan, Poland |
| Type of Work | contributed presentation. |
| Key Words | research; VPP; wind generation; battery energy storage system; stochastic programming; electricity market; optimal bid |
| Abstract | The recent cost reduction and technologic advances in medium to large scale Battery Energy Storage Systems (BESS) makes these devices a real choice alternative for wind producers operating in electricity markets. The association of a wind power farm with a BESS (the so called Virtual Power Plant VPP) provides utilities with a tool to turn the uncertainty wind power production into a dispatchable technology enabled to operate not only in the spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, was forbidden to non-dispatchable technologies. Even more, recent studies have shown that the capital cost investment in BESS can only be recovered through the participation of such a VPP in the ancillary services markets. We present in this study a stochastic programming model to find the optimal participation of a VPP to the day-ahead market and secondary reserve markets (the most relevant ancillary service market) where the uncertainty in wind power generation and markets prices (day-ahead ancillary services) has been considered. A case study with real data from the Iberian Electricity Market is presented. |
| URL | Click Here |
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Thu, 09/03/2015 - 10:25 — admin
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The work On optimal participation in the electricity markets of wind power plants with battery energy storage systems has been published in the journal Computers and Operations Research. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets hile taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian electricity market is presented. Preprint available at http://hdl.handle.net/2117/118479
Last december I was invited to the 4th International Conference on Optimization Methods and Software 2017 that was held in La Havana, to present the study A Multistage Stochastic Programming Model for the Optimal Bid of Wind-BESS Virtual Power Plants to Electricity Markets. This study was developed in collaboration with Marlyn Cuadrado and Josep Anton Sánchez, from my same department in the UPC, and is a partial result of the research project FOWGEM. This study is a follow up of the previous work presented in the WindFarms 2017 Conference extended with a new methodology to treat the uncertainty, based in forecasting models, and the study of the quality of the stochastic solution through the Value of the Stochastic Solution. In the animated graph you can observe how the the probability distribution of several recourse variables (optimal bid, imbalances, charge/discharge and SOC) evolves along five working days.