ISEP – GECAD – Comunicações em eventos científicos
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- Decision-Support Tool for the Establishment of Contracts in the Electricity MarketPublication . Azevedo, Filipe; Vale, Zita; Vale, António A.The Pool, in many countries, was adopted for the participants of the electricity market to trade the electrical energy in a basis of each half-hour or one hour of the next day. However, like the traditional markets, the agents of electrical market are now exposed to the volatility of market price. In some countries, to face that problem and to turn the market more liquid, the derivatives markets – futures and options - were introduced to negotiate products with electrical energy as underlying active. In this context, there is a need of decisionsupport tools to assist those agents for the use of derivatives markets with the objective of practicing the hedge. In this paper, we present a decision model that supports producers to establish contracts with the objective to maximize the profit expected utility.
- Hedging Using Futures and Options Contracts in the Electricty MarketPublication . Azevedo, Filipe; Vale, Zita; Vale, António A.Since the 80’s with the experience of Chile, the electric sector has suffered, in many counties, a process of deregulation and liberalization. In almost of the countries, that process originated the appearance of a Pool where the participants of the market trade the electrical energy on a basis of half-hour or one hour of the next day. However, like the traditional markets, the agents of electricity markets are now exposed to the volatility of market price, so far inexistent in those markets. In some countries, to face that problem and to turn the market more liquid have been introduced derivatives markets – futures and options, to negotiate products with underlying active the electrical energy. In this context, there is a need of decision-support tools that allow those agents to use derivatives markets with the objective of practicing the hedge and simultaneously increase their results. In this paper, we present a decision model that supports producers in the establishment of contracts with the objective to maximize the profit expected utility. The paper presents a group of examples of the use of this decision-support system.
- Optimal Contracts Allocation Using Mean Variance Optimization MethodPublication . Azevedo, Filipe; Vale, ZitaThe process of restructuration and liberalization of power systems are a constant all over the world. However, those processes, due to the specific characteristics of the “product” electricity, create uncertainty and new risks that did not exist when power systems were vertically integrated. Those changes origin the necessity of tools that allow the participants of the electricity markets to practice the hedge against the volatility of the System Marginal Price. In that sense, we present in this paper a decision-support application, based on a Mean Variance Optimization Method trying to give a response to the necessities of the electricity markets participants. The results show that the proposed method can be useful to producers and also to others participants of electricity markets like Brokers and Load Serving Entities (LSE).
- Short-term Price Forecast From Risk Management Point of ViewPublication . Azevedo, Filipe; Vale, ZitaThis paper provides a different approach for electricity price forecast from risk management point of view. Making use of neural networks, the methodology presented here has as main concern finding the maximum and the minimum System Marginal Price (SMP) for a specific programming period, with a certain confidence level. To train the neural network, probabilistic information from past years is used. This approach was developed with the objective of integrating a decisionsupport system that uses Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data are presented and discussed in detail.
- Production Support-Support System on Liberalized Market EnvironmentPublication . Azevedo, Filipe; Vale, ZitaThe restructuration and liberalization processes of power systems are a constant all over the world. However, those processes due to the specific characteristics of the product electricity create uncertainty and new risks that doesn t exist when power systems were vertically integrated. Those changes, origin the necessity of tools that allow the participants of the electricity markets to practice the hedge against the volatility of the System Marginal Price. In that sense, we present in this paper a Mean Variance Optimization Method trying to give a response to the necessities of the electricity markets participants. This optimization method was applied on an example presented in this paper. We conclude that, the Optimization Method presented in this paper, could be useful to producers and also to others participants.
- A Clustering Neural Network Model Applied to Electricity Price Range ForecastPublication . Azevedo, Filipe; Vale, Zita; Oliveira, P. B. MouraWith electricity markets birth, electricity price volatility becomes one of the major concerns for their participants and in particular, for the producers. Whether or not to hedge, what type of portfolio is ade-quate, and how to manage that portfolio are important considerations for electricity market agents. To achieve that, load and electricity price forecast have a high impor-tance. This paper provides an approach applied to price range forecast. Making use of artificial neural networks (ANN), the methodology presented here has as main con-cern finding the maximum and the minimum System Mar-ginal Price (SMP) for a specific programming period, with a certain confidence level. To train the neural networks, probabilistic information from past years is used. To in-crease accuracy and turning ANN training more efficient, a K-Means clustering method is previously applied. Re-sults from real data are presented and discussed in detail.
- Forecasting Electricity Prices with Historical Statistical Information using Neural Networks and Clustering TechniquesPublication . Azevedo, Filipe; Vale, ZitaFactors such as uncertainty associated to fuel prices, energy demand and generation availability, are on the basis of the agents major concerns in electricity markets. Facing that reality, price forecasting has an increasing impact in agents’ activity. The success on bidding strategies or on price negotiation for bilateral contracts is directly dependent on the accuracy of the price forecast. However, taking decisions based only on a single forecasted value is not a good practice in risk management. The work presented in this paper makes use of artificial neural networks to find the market price for a given period, with a certain confidence level. Historical information was used to train the neural networks and the number of neural networks used is dependent of the number of clusters found on that data. K-Means clustering method is used to find clusters. A study case with real data is presented and discussed in detail.
- MASCEM improvement for agent based coalitionsPublication . Praça, Isabel; Andrade, André; Morais, H.; Ramos, Carlos; Vale, ZitaThis paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.
- A congestion management and transmission price simulator for competitive electricity marketsPublication . Ferreira, Judite; Vale, Zita; Cardoso, JoséIn a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.
- Natural Gas location design and operationPublication . Nogueira, Teresa; Vale, Zita; Ramos, Carlos; Cardoso, JoséA major determinant of the level of effective natural gas supply is the ease to feed customers, minimizing system total costs. The aim of this work is the study of the right number of Gas Supply Units – GSUs - and their optimal location in a gas network. This paper suggests a GSU location heuristic, based on Lagrangean relaxation techniques. The heuristic is tested on the Iberian natural gas network, a system modelized with 65 demand nodes, linked by physical and virtual pipelines. Lagrangean heuristic results along with the allocation of loads to gas sources are presented, using a 2015 forecast gas demand scenario.