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Browsing ISE - Artigos em revistas internacionais by Author "Algarvio, Hugo"
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- Agent-based model of citizen energy communities used to negotiate bilateral contracts in electricity marketsPublication . Algarvio, HugoABSTRACT: The worldwide targets for carbon-neutral societies increased the penetration of distributed generation and storage. Smart cities now play a key role in achieving these targets by considering the alliances of their demand and supply assets as local citizen energy communities. These communities need to have enough weight to trade electricity in wholesale markets. Trading of electricity can be done in spot markets or by bilateral contracts involving customers and suppliers. This paper is devoted to bilateral contracting, which is modeled as a negotiation process involving an iterative exchange of offers and counter-offers. This article focuses on local citizen energy communities. Specifically, it presents team and single-agent negotiation models, where each member has its sets of strategies and tactics and also its decision model. Community agents are equipped with intra-team strategies and decision protocols. To evaluate the benefits of CECs, models of both coalition formation and management have been adapted. This paper also describes a case study on forward bilateral contracts, involving a retailer agent and three different types of citizen energy communities. The results demonstrate the benefits of CECs during the negotiation of private bilateral contracts of electricity. Furthermore, they also demonstrate that in the case of using a representative strategy, the selection of the mediator may be critical for achieving a good deal.
- Agent-based retail competition and portfolio optimization in liberalized electricity markets: A study involving real-world consumersPublication . Algarvio, Hugo; Lopes, FernandoABSTRACT: The liberalization of energy markets brought full competition to the electric power industry. In the wholesale sector, producers and retailers submit bids to day-ahead markets, where prices are uncertain, or alternatively, they sign bilateral contracts to hedge against pool price volatility. In the retail sector, retailers compete to sign bilateral contracts with end-use customers. Typically, such contracts are subject to a high-risk premium—that is, retailers request a high premium to consumers to cover their potential risk of trading energy in wholesale markets. Accordingly, consumers pay a price for energy typically higher than the wholesale market price. This article addresses the optimization of the portfolios of retailers, which are composed of end-use customers. To this end, it makes use of a risk-return optimization model based on the Markowitz theory. The article presents a simulation-based study conducted with the help of the MATREM system, involving 6 retailer agents, with different risk preferences, and 312 real-world consumers. The retailers select a pricing strategy and compute a tariff to offer to target consumers, optimize their portfolio of consumers using data from the Iberian market, sign bilateral contracts with consumers, and compute their target return during contract duration. The results support the conclusion that retail markets are more favourable to risk-seeking retailers, since substantial variations in return lead to small variations in risk. However, for a given target return, risk-averse retailers consider lower risk portfolios, meaning that they may obtain higher returns in both favourable and unfavourable situations.
- Automated Bilateral Trading of Energy by Alliances in Multi-Agent Electricity MarketsPublication . Algarvio, HugoABSTRACT: In liberalized markets, consumers can choose their electricity suppliers or be part of an energy community. The problem with communities is that they may not have enough weight to trade in markets, which can be overcome by forming coalitions. Electricity is traded in spot markets or through bilateral contracts involving consumers and suppliers. This paper is devoted to bilateral contracting, modeled as a negotiation process involving an iterative exchange of offers and counter-offers. It focuses on coalitions of energy communities. Specifically, it presents team and single-agent negotiation models, where each consumer has strategies, tactics, and decision models. Coalition agents are equipped with intra-team strategies and decision protocols. It also describes a study of bilateral contracts involving a seller agent and a coalition of energy communities. By allying into a coalition, members of energy communities reduced their average costs for electricity by between 2% (large consumers) and 64% (small consumers) according to their consumption. Their levelized cost reduction was 19%. The results demonstrate the power of coalitions when negotiating bilateral contracts and the benefit of a low-consumption members alliance with larger players.
- Bilateral Contracting and Price-Based Demand Response in Multi-Agent Electricity Markets: A Study on Time-of-Use TariffsPublication . Algarvio, Hugo; Lopes, FernandoABSTRACT: Electrical energy can be traded in liberalized organized markets or by negotiating private bilateral contracts. Competitive markets are central systems where market players can purchase and sell electrical energy. Bilateral contracting consists typically in a private negotiation of power over several months or years between two parties. Price-based demand response considers the active participation of consumers in electricity markets. Consumers adopt demand response programs when responding to market prices or tariffs, as they change over time. Those tariffs can be proposed by retailers by considering their load shape goals, influencing consumers to change their behavior. Consumers may adopt strategies from two different groups, namely by curtailing energy at times of high prices (e.g., peak and intermediate periods) and rescheduling energy away from those times to other times (shifting). This article considers bilateral contracting in electricity markets with demand response. It investigates how curtailment and shifting affect the energy quantity and energy cost of consumers that adopt a time-of-use tariff involving three block periods (i.e., base, intermediate and peak periods). The results indicate that consumers respond to changes in energy price according to their consumption flexibility, while retailers do not always change energy price in response to consumers' efforts to change their consumption patterns. On average, by considering a 5% consumption reduction in the intermediate and peak periods by a consumer agent, a retailer agent reduces the energy price only by 1.5%.
- Changing the day-ahead gate closure to wind power integration: a simulation-based studyPublication . Algarvio, Hugo; Couto, António; Lopes, Fernando; Estanqueiro, AnaABSTRACT: Currently, in most European electricity markets, power bids are based on forecasts performed 12 to 36 hours ahead. Actual wind power forecast systems still lead to large errors, which may strongly impact electricity market outcomes. Accordingly, this article analyzes the impact of the wind power forecast uncertainty and the change of the day-ahead market gate closure on both the market-clearing prices and the outcomes of the balancing market. To this end, it presents a simulation-based study conducted with the help of an agent-based tool, called MATREM. The results support the following conclusion: a change in the gate closure to a time closer to real-time operation is beneficial to market participants and the energy system generally.
- Decarbonization of electricity systems in Europe: market design challengesPublication . Strbac, Goran; Papadaskalopoulos, Dimitrios; Chrysanthopoulos, Nikolaos; Estanqueiro, Ana; Algarvio, Hugo; Lopes, Fernando; Vries, Laurens de; Morales-España, Germán; Sijm, Jos; Hernandez-Serna, Ricardo; Kiviluoma, Juha; Helistö, NiinaABSTRACT: Driven by climate change concerns, Europe has taken significant initiatives toward the decarbonization of its energy system. The European Commission (EC) has set targets for 2030 to achieve at least 40% reduction in greenhouse gas emissions with respect to the 1990 baseline level and cover at least 32% of the total energy consumption in the European Union (EU) through renewable energy sources, predominantly wind and solar generation. However, these technologies are inherently characterized by high variability, limited predictability and controllability, and lack of inertia, significantly increasing the balancing requirements of the system with respect to historical levels. The flexibility burden is currently carried by flexible fossil-fueled conventional generators (mainly gas), which are required to produce significantly less energy (as low operating cost and CO2-free renewable and nuclear generation are prioritized in the merit order) and operate part loaded with frequent startup and shut-down cycles, with devastating effects on their cost efficiency.
- Dynamic Line Rating Models and Their Potential for a Cost-Effective Transition to Carbon-Neutral Power SystemsPublication . Estanqueiro, Ana; Algarvio, Hugo; Couto, António; Michiorri, Andrea; Salas, Sergio; Pudjianto, Danny; Hagglund, Per; Dobschinski, Jan; Bolgaryn, Roman; Kanefendt, Thomas; Gentle, Jake; Alam, S. M. Shafiul; Priest, Zachary M.; Abboud, Alexander W.ABSTRACT: Most transmission system operators (TSOs) currently use seasonally steady-state models considering limiting weather conditions that serve as reference to compute the transmission capacity of overhead power lines. The use of dynamic line rating (DLR) models can avoid the construction of new lines, market splitting, false congestions, and the degradation of lines in a cost-effective way. DLR can also be used in the long run in grid extension and new power capacity planning. In the short run, it should be used to help operate power systems with congested lines. The operation of the power systems is planned to have the market trading into account; thus, it computes transactions hours ahead of real-time operation, using power flow forecasts affected by large errors. In the near future, within a "smart grid" environment, in real-time operation conditions, TSOs should be able to rapidly compute the capacity rating of overhead lines using DLR models and the most reliable weather information, forecasts, and line measurements, avoiding the current steady-state approach that, in many circumstances, assumes ampacities above the thermal limits of the lines. This work presents a review of the line rating methodologies in several European countries and the United States. Furthermore, it presents the results of pilot projects and studies considering the application of DLR in overhead power lines, obtaining significant reductions in the congestion of internal networks and cross-border transmission lines.
- Effects of regulating the European Internal Market on the integration of variable renewable energyPublication . Algarvio, Hugo; Lopes, Fernando; Couto, António; Santana, João; Estanqueiro, AnaABSTRACT: The new proposal for regulating the European Internal Market for Electricity (EIME) can motivate the harmonization of the various National markets. The process of harmonizing the day-ahead markets (DAMs) is at an advanced stage, with an efficiency in the use of interconnectors of 86%. However, the harmonization of both intraday (IDMs) and balancing markets (BMs) is still in its infancy, with an efficiency in the use of interconnectors of 50 and 19%, respectively. The new proposal brings new targets to DAMs, and European countries should make efforts to comply with them. The same is true for IDMs and BMs, but involving more ambitious targets, requiring higher efforts to be accomplished. Both the analysis of the various National markets (according to their compliance with the new proposal for regulating the EIME) and the advantages of the new proposal for key market participants (particularly, consumers, variable renewable generation, and conventional generation) are presented. The analysis indicates that the proposal contributes to a potential increase of the general welfare of market participants. However, some aspects of the proposal can negatively affect the revenue obtained from the National markets, notably for variable renewable generation and conventional generation. This article is categorized under: Wind Power > Systems and Infrastructure Energy Policy and Planning > Economics and Policy Energy Systems Analysis > Economics and Policy Energy and Development > Economics and Policy
- Least-cost non-RES thermal power plants mix in power systems with majority penetrations of renewable energyPublication . Algarvio, HugoABSTRACT: The ambitious targets of the European Union (EU) for a greater penetration of renewable energy sources (RES) in all areas of activity have led to power systems with growing levels of variable RES (VRES) all over the EU. Considering these targets, the EU countries presented their National Energy and Climate Plans (NECP) with their expected capacity until 2030. The NECPs considered a relevant increase in the VRES capacity and in some cases a decrease in the capacity of dispatchable power plants. VRES have near-zero marginal costs and increase the volatility of the net-load due to the stochastic profile of their production. These characteristics increase the need to maintain fast-response dispatchable power plants to guarantee the security of supply and also decrease market prices. Thus, governments promote externalities, as capacity mechanisms and other incentives to these players, guaranteeing their economic sustainability. This study presents the optimization of the non-RES thermal capacity of the Iberian power system by 2030, considering the least-cost algorithm. Considering a cooperative scenario between Portugal and Spain, it is possible to reduce the system costs by 17.40%, the curtailments quantity by 21.93%, the number of market-splitting hours by 43.26% and the dioxide carbon emissions by 4.76%.
- A Machine Learning Model for Procurement of Secondary Reserve Capacity in Power Systems with Significant vRES PenetrationsPublication . dos Santos, Joao; Algarvio, HugoABSTRACT: The growing investment in variable renewable energy sources is changing how electricity markets operate. In Europe, players rely on forecasts to participate in day-ahead markets closing between 12 and 37 h ahead of real-time operation. Usually, transmission system operators use a symmetrical procurement of up and down secondary power reserves based on the expected demand. This work uses machine learning techniques that dynamically compute it using the day-ahead programmed and expected dispatches of variable renewable energy sources, demand, and other technologies. Specifically, the methodology incorporates neural networks, such as Long Short-Term Memory (LSTM) or Convolutional neural network (CNN) models, to improve forecasting accuracy by capturing temporal dependencies and nonlinear patterns in the data. This study uses operational open data from the Spanish operator from 2014 to 2023 for training. Benchmark and test data are from the year 2024. Different machine learning architectures have been tested, but a Fully Connected Neural Network (FCNN) has the best results. The proposed methodology improves the usage of the up and down secondary reserved power by almost 22% and 11%, respectively.
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