João Hermínio Ninitas Lagarto
@isel.pt
Área Departamental de Engenharia Eletroténica de Energia e Automação
Instituto Superior de Engenharia de Lisboa
EDUCATION
PhD in Sustainable Energy Systems - Instituto Superior Técnico
RESEARCH INTERESTS
Power systems economics
Electricity markets
Renewable energy
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Jorge Sousa, João Lagarto, Cristina Camus, Carla Viveiros, Filipe Barata, Pedro Silva, Ricardo Alegria, and Orlando Paraíba
Elsevier BV
Mário Silva, João Lagarto, Jorge Sousa, Feliz Mil-Homens, Carla Viveiros, and Filipe Barata
MDPI AG
The remuneration scheme for the electricity produced by Waste-to-Energy (WtE) recovery plants has changed recently in Portugal according to 2020 legislation. The new model, linking the electricity remuneration from WtE plants to the spot electricity prices, is expected to bring greater uncertainty in the waste activity, which is a novelty for the sector. In Portugal, Valorsul is the municipal waste treatment entity responsible for the recovery and treatment of municipal solid waste (MSW) produced in 19 municipalities in the Lisbon area. This paper highlights the impact of the new Portuguese electricity remuneration scheme for electricity from waste on Valorsul’s WtE plant. For this purpose, the new remuneration scheme is modeled and simulated based on electricity spot market price scenarios, which are compared with the base case scenario of the former remuneration scheme. Considering different electricity prices for the electricity produced by the WtE plant, the present study anticipates the consequences of the gate-fee of such regulatory changes. Results show that any price changes in the electricity remuneration scheme are offset by equivalent changes in the waste gate-fee. Consequently, the change in the remuneration of the electricity from the WtE plant is, in fact, neutral for the Valorsul accounts and lower revenues from the electricity generation activity of the WtE will negatively impact the gate-fee prices paid by the waste users.
Jorge Sousa, João Lagarto, Ezequiel Carvalho, and Ana Martins
Elsevier BV
Ana Martins, J. Lagarto, H. Canacsinh, Francisco Reis and Margarida M. G. S. Cardoso
Helio Marques, Jorge Sousa, Cristina Camus, and Joao Lagarto
IEEE
This paper evaluates the financial performance of the solar photovoltaics (PV) projects approved under the Portuguese auction of 2020. A 700 MVA capacity was auctioned through 12 lots, each ranging from 10 MVA to 109 MVA, in the Portuguese regions of Alentejo and Algarve. World record prices were achieved in this auction, namely the lowest bid of 11.14 €/MWh, which raised doubts about the profitability of these investments. The present study identifies the main drivers of the observed bidding prices by simulating the auction process using real solar resource availability and electricity market price scenarios. The model includes the costs of the auction requirements, connection to the grid, substation, and storage (when applicable). In order to understand the auction prices and evaluate the investors profitability, the key financial performance indexes of Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP) were computed for the 12 lots for a 15-year and 25-year period.
Andre Lopes, Jorge Sousa, Cristina Camus, and Joao Lagarto
IEEE
Growing concerns with climate change has prompted governments for action. Portugal put forward ambitious targets through its National Energy and Climate Plan 2030 (PNEC2030) and the Roadmap for Carbon Neutrality 2050 (RNC2050) to reduce CO2 emissions. In this context, the present work analyzes the Portuguese commitments under the 2030 scenarios presented in the PNEC2030 and RNC2050. Simulations of the Portuguese system were carried out using the simulator developed by the ISEL Energy Systems Research Group. This simulator, implemented in GAMS language, performs the unit commitment, economic dispatch, and hydrothermal coordination of the Portuguese power system that minimizes the full operational system costs. Base case results for 2030 showed a 42 GWh renewable energy curtailment. Measures to integrate this excess of renewable energy are presented both with additional storage systems and green hydrogen production.
B. Capitao, J. Lagarto, R. Pereira, P. Almeida, and P.M. Fonte
IEEE
Demand response actions allow to support an adequate domestic load management, considering consumer preferences. In order to develop a hardware tool based on Arduino used to support consumers load management and decisions, an optimization mathematical model is developed and detailed in this paper. In the developed mathematical model, household appliances and electric vehicle are considered as controllable loads. The existence of a storage system based on batteries is considered as well as energy provided by the power grid and solar panel self-generation. The model is implemented using optimization software GAMS (General Algebraic Modeling System) as a Mixed Integer Programming (MIP) problem, where its outputs are used as inputs applied to the hardware used as interface between the optimization mathematical model and controllable loads.
E. Carvalho, J. Sousa and João L. Lagarto
In this work the electric vehicle (EV) specific CO2 emissions resulting from the EV integration on thePortuguese power system are analyzed, considering a large set of scenarios combining the system renewablecapacity versus EV share, under a night charge scenario. For this purpose, a unit commitment and economicdispatch (UCED) is applied to the power units scheduling. The optimization procedure is implemented inGeneral Algebraic Modeling System (GAMS) and performs the dispatch of the thermal and hydro units,in order to minimize the operation costs. The model is applied to an entire year of operation in a hourlybasis using a marginal methodology. According to the results obtained, for the scenarios considered, the EVspecific CO2 emissions range from 57 g CO2/km, for high wind capacity and low EV penetration, to 129g CO2/km, for low wind capacity and low EV penetration. From the results, it can be concluded that, withthe current wind capacity of the Portuguese system, the impact of the EV in terms of CO2 emissions is notbeneficial when compared to the 95 g CO2/km target, for penetrations lower than 1 million vehicles. Resultsalso show that EVs can be integrated in an environmental beneficial way, if increasing EV penetrations arecombined with an increase in the installed wind capacity.
Ana Martins, Joao Lagarto, and Margarida G.M.S. Cardoso
IEEE
The creation of the internal market of electricity has long been a goal of the European Union, for which it has established common rules through the directive 2009/72/EC. In this context, the analysis of electricity markets operation of the different countries that will form the internal market is of the utmost importance.In this work, we use clustering techniques to analyze 26 time series of day-ahead electricity prices from European markets between 2015 and 2018 in order to identify different price patterns. The cluster technique proposed uses a combination of three dissimilarity measures for time series: Euclidean, Pearson correlation based and periodogram based.Results show that there is a clear distinction between Northern markets, especially Nord Pool, and Southern markets, MIBEL and Italy. Moreover, results also show that despite some market prices presenting similar behaviors, a full integrated European electricity market is yet to be accomplished.
Filipe Fernandes, Jorge A. M. Sousa, Joao Santana, and Joao Lagarto
IEEE
The increasing integration of wind power in the Portuguese energy market has been raising some challenges in terms of operation and planning of the generation portfolio and of power system management, with ancillary services playing a major role in system stability. A generation company (GENCO) aiming at maximizing its profits has to deal with bids to several available markets, among which are the Day-ahead Market (DAM) and the Secondary Reserve Market (SRM). This paper presents a scheduling solution of a price-maker GENCO whose portfolio comprises a pumped-storage hydro (PSH) unit with variable pumping capacity, acting simultaneously in the DAM and SRM. The results were obtained for four different scenarios, where the PSH may or may not possess variable pumping capacity and compares the PSH behavior in one or both markets simultaneously. The model was implemented in General Algebraic Modeling System (GAMS) as a Mixed Integer Programming (MIP) using CPLEX solver.
Joao Vicente, Ana Martins, Joao Lagarto, and Jorge A. M. Sousa
IEEE
With the globalization of the world economy, the relationships between commodities, financial and other markets are relevant. Although the electricity market is a more recent kind of market, it is still related with other markets, such as, commodities markets (natural gas, coal, oil), and carbon emissions markets. In this work, we propose to study the interconnections between the day-ahead Iberian electricity market (MIBEL) and the commodities markets, as well as, the carbon emissions markets between 2010 and 2016. To achieve this purpose, we use the Diebold-Yilmaz framework, which proposes measures of the interdependence of returns and volatilities through variance decomposition of forecasted error variances in a generalized vector autoregressive model. Results show that the markets that had a higher influence in MIBEL in the analyzed period were the TTF and Zeebrugge natural gas markets and the markets that MIBEL most influenced were the Coal (API2) and CER market.
H. Algarvio, F. Lopes, J. Sousa, and J. Lagarto
Elsevier BV
Abstract The major electricity market models include: pools, bilateral contracts and hybrid models. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants can enter into bilateral contracts to hedge against pool price volatility. In bilateral contracts, market participants can set the terms and conditions of agreements independent of the market operator. The hybrid model combines features of both pools and bilateral contracts. This paper is devoted to risk management and the optimization of the portfolios of retailers operating in liberalized electricity markets. It introduces a model for optimizing portfolios composed by end-use consumers using the Markowitz theory. It also presents an overview of a multi-agent system for electricity markets. The system simulates the behavior of various markets entities, including generating companies, retailers and consumers. The final part of the paper presents three case studies on portfolio optimization involving risk management: a retailer (a software agent) optimizes its portfolio by taking into account the attitude towards risk and the offer of a 3-rate tariff to five different types of consumers: industrial, large and small commercial, residential and street lightning. The results show that the retailer, by being more realistic in choosing consumers to its portfolio, can offer more competitive tariffs to key consumers and keep the portfolio optimal and stable in relation to the risk–return ratio.
Daniel Freitas, Ana Martins, and Joao Lagarto
IEEE
In the current operation of electricity markets, market price and quantity present a distinct pattern between peak and off-peak hours. This pattern tends to repeat over a 24-hour time cycle. The purpose of this study is to analyze the maximum values of day-ahead market prices, considering the time of day when the maximum values are reached and the respective quantity traded. The cyclical nature of these variables allows the use of circular statistical methods that can be used to analyze any kind of data that are cyclic in nature, like time-of-day data measured on a 24h-clock. This study applies this methodology in analyzing the maximum day-ahead market prices in the Iberian electricity market (MIBEL) between 2012 and 2014 enabling the analysis over the years and between seasons. Results show that circular statistics methods enable to bring important insights into the characterization of electricity market price behavior.
Joao Lagarto, Filipe Fernandes, Jorge A. M. Sousa, and Joao Santana
IEEE
The increasing integration of renewables in the energy markets has been raising some challenges to generating companies (GENCOs), in terms of operation and planning of their generation portfolios. A GENCO aiming at maximizing its profits has to deal with offers to several available markets, among which are the Day-ahead Market (DAM) and the Secondary Reserve Market (SRM). This paper presents a scheduling solution of a price-maker GENCO whose portfolio includes a pumped-storage hydro unit, acting simultaneously in the DAM and SRM. The results were obtained for six different scenarios, where the portfolio may include a thermal generation unit and compares the GENCO behavior in both markets either as a price-taker or as a price-maker. The results put in evidence the portfolio effect when the GENCO takes into account its influence on price, which is seen in the price-maker scenarios, whereas the scheduling remains unchanged under the price-taker behavior.
Joao Lagarto, Filipe Fernandes, Jorge A. M. Sousa, Joao Santana, and Berto Martins
IEEE
Ancillary services play a major role in power systems security and stability. The transmission systems operators contract some of these services at minimum cost in competitive markets. This is the case of the secondary reserve market (SRM). Besides the day-ahead market (DAM) generating companies, aiming at maximize their profits, can increase their revenues by selling available capacity in the SRM. This paper presents the solution of a price-taker generating company, owning a pumped-storage hydro (PSH) unit, acting in DAM and SRM. The results were obtained for three case studies: the generating company acts only in the DAM; the generating company acts in both markets with a fixed pumping capacity of the PSH unit; the generating company acts in both markets with a variable pumping capacity of the PSH unit. Results show that higher profits are obtained when acting in both markets with a variable pumping capacity of the PSH unit.
Hugo Algarvio, Fernando Lopes, Jorge A.M. Sousa, and Joao Lagarto
IEEE
Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit.
Hugo Algarvio, Fernando Lopes, Jorge A.M. Sousa, and Joao Lagarto
IEEE
The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit.
João Lagarto, Jorge A.M. Sousa, Álvaro Martins, and Paulo Ferrão
Elsevier BV
In the last years the electricity industry has faced a restructuring process. Among the aims of this process was the increase in competition, especially in the generation activity where firms would have an incentive to become more efficient. However, the competitive behavior of generating firms might jeopardize the expected benefits of the electricity industry liberalization. The present paper proposes a conjectural variations model to study the competitive behavior of generating firms acting in liberalized electricity markets. The model computes a parameter that represents the degree of competition of each generating firm in each trading period. In this regard, the proposed model provides a powerful methodology for regulatory and competition authorities to monitor the competitive behavior of generating firms.
Joao Pereira, Ruben Aires Ferreira, Jorge A. M. Sousa, Joao Lagarto, and Ana Martins
IEEE
Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.
Ricardo Faria, Jorge Sousa, Ana Martins, and Joao Lagarto
IEEE
The Iberian Electricity Market (MIBEL) emerges in the context of the integration and cooperation between the Portuguese and Spanish electricity markets, in response to the European Union incentive for regional electricity markets creation. The present study, focus on the modeling and forecasting of the hourly competitive strategies of the electricity producers in the MIBEL. For this analysis, the studied variable was the MIBEL's conjectural variation, which estimates the level of competitiveness of the electricity producers on the day-ahead electricity market. The methodology adopted for forecasting was time series analysis, using ARIMA and exponential smoothing models. The results obtained show that the estimated models that best suit the hourly MIBEL conjectural variation forecast were mainly of the ARIMA seasonal type with daily seasonality, followed by ARIMA non-seasonal type models. It was also observed, that the selected models were mainly estimated with a time series of 5 working days.
Joao Bolas, Jorge Sousa, Ana Martins, and Joao Lagarto
IEEE
In recent years, the power sector has undergone a restructuring process in many economies in the world. This movement towards liberalization led to the establishment of electricity markets that promote the competitiveness of the production and trading segments of the power sector. In these markets, the agents have to deal with frequent electricity price changes leading to different strategies in their daily bidding behavior. There are a set of variables that can have an impact in the electricity price definition, such as: fuel prices, CO2 emissions prices, electricity production and demand. This paper proposes to analyze structural changes in the Iberian electricity market price between two periods of time: 2007/2008 and 2010/2011. For this purpose, three quantitative analysis methods were used: correlation, causality and Principal Components. Results suggest that the electricity price had a structural change between the analyzed periods, in particular the increasing importance of special regime production.
Joao Lagarto, Jorge de Sousa, Alvaro Martins, and Paulo Ferrao
IEEE
Price forecast is a matter of concern for all participants in electricity markets, from suppliers to consumers through policy makers, which are interested in the accurate forecast of day-ahead electricity prices either for better decisions making or for an improved evaluation of the effectiveness of market rules and structure. This paper describes a methodology to forecast market prices in an electricity market using an ARIMA model applied to the conjectural variations of the firms acting in an electricity market. This methodology is applied to the Iberian electricity market to forecast market prices in the 24 hours of a working day. The methodology was then compared with two other methodologies, one called naïve and the other a direct forecast of market prices using also an ARIMA model. Results show that the conjectural variations price forecast performs better than the naïve and that it performs slightly better than the direct price forecast.
Joao Lagarto, Jorge de Sousa, and Alvaro Martins
IEEE
Electricity market prices can be influenced by many drivers, such as fuel costs, CO2 emission prices, hydro and other renewable production and strategic behavior of firms that participate in the market. One of the aims of the liberalization process of the electricity industry was to bring electricity prices more in line with costs. Therefore, the influence that the strategic behavior of firms might have in market prices is a concern. This paper analyzes the strategic behavior of three medium size firms acting in the Iberian electricity market (IBELM) in the first year after its implementation, that is, from July 2007 to June 2008. This strategic behavior is analyzed by computing an hourly competitive parameter which is obtained from a conjectural variation model. Then the evolution of the monthly average of this conjectural variation parameter is studied. Results showed that some of the analyzed firms did not reflect in market prices the increase in fuel costs and in CO2 emission prices that occurred in the first six months of 2008.
Joao Lagarto, Jorge de Sousa, and Alvaro Martins
IEEE
The integration of the Portuguese and Spanish electricity markets came into force on the July 2007 with the creation of the Iberian Electricity Market (IBELM).
J. Yan, J. Sousa, and J. Lagarto
IEEE
This paper presents a comparative study on market behaviors in a proposed South African electricity market using two market simulation software, in order to evaluate different market structures and competition models. The results show that the design of market structure is essential to ensure proper competition. Market structure plays an important role on the determination of market clearing price and production. The more concentrated the market will result in higher market price. Overall profits in the market also vary with the change of market structure and competition models.