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Publicações

Publicações por João Tomé Saraiva

2014

An Evolutionary Particle Swarm Optimization, EPSO, Approach to Optimize the Operation of Hydro Stations in Market Environment

Autores
Pacheco, AS; Saraiva, JT;

Publicação
2014 11TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM)

Abstract
This paper describes the application of Evolutionary Particle Swarm Optimization, EPSO, to the optimization of the short term operation of hydro stations in market environment. The maximization of the revenues of hydro stations, namely pumping stations, is gaining increasing attention by generation companies. However, this is typically a complex problem given the non linear relation between the power, the flow and the head, the temporal coupling between stations in cascade and the increasing number of pumping stations. The EPSO based algorithm displayed a very good performance in terms of the quality of the final operation plan as well as regarding the speed of convergence and the robustness of the algorithm.

2016

Multiyear and Multi-Criteria AC Transmission Expansion Planning Model Considering Reliability and Investment Costs

Autores
Gomes, PV; Silva, JP; Saraiva, JT;

Publicação
2016 13TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM)

Abstract
One of the major concerns in Power Systems is surely related with their reliability. Long-term expansion planning studies traditionally use the well-known deterministic "N-1" contingency criterion. However, this criterion is applied based on worst-case analyses and the obtained plan may originate over-investments. Differently, probabilistic reliability approaches can incorporate different type of uncertainties that affect power systems. In this work, a long term multi-criteria AC Transmission Expansion Planning model was developed considering two objectives - the probabilistic reliability index Expected Energy Not Supplied (EENS) and the investment cost. The Pareto-Front associated with these two objectives was obtained using Genetic Algorithms and the final solution was selected using a fuzzy decision making function. This approach was applied to the IEEE 24 Bus Test System and the results ensure its robustness and efficiency.

2016

Dynamic network tariffs: Are they the most efficient way to match peak consumption and network incremental costs?

Autores
Pires, G; Pinto, RB; Saraiva, JT; Fidalgo, JN; Nunes, JF;

Publicação
IET Conference Publications

Abstract
The purpose of this paper is to present the main results of the ongoing analysis of applying dynamic network access tariffs in Portugal. For the 2015-2017 regulatory period, the Portuguese National Regulatory Authority, ERSE, required the three main Portuguese DSOs to submit, until the end of June 2016, plans for the implementation of network dynamic tariff schemes targeting Medium, High and Extra High Voltage customers, as well as the respective cost-benefit analysis. EDP Distribuição, the main Portuguese DSO, is preparing a report regarding the implementation of pilot projects on a sample of these segments of customers, which are due to be on the field during 2017. These pilots should help electrical energy stakeholders understand how the Electric System can benefit from the use of dynamic tariffs focused on networks, allowing for the quantification of benefits in a more accurate way. The level of demand response that results from price signals is a key issue that both the regulator and EDP Distribuição will quantify. Other important issue to assess in this study is the efficiency of cost recovery under a dynamic tariff scheme. In conclusion, this paper will present some results obtained from the cost-benefit analysis regarding the implementation of a Critical Peak Pricing scheme, as well as the key learnings supporting the introduction of dynamic schemes in the future, not only for EHV, HV and MV customers but also eventually extending it to LV ones.

2015

ELECTRICITY DAY-AHEAD MARKETS: COMPUTATION OF NASH EQUILIBRIA

Autores
Carvalho, M; Pedroso, JP; Saraiva, J;

Publicação
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION

Abstract
In a restructured electricity sector, day-ahead markets can be modeled as a game where some players - the producers - submit their proposals. To analyze the companies' behavior we have used the concept of Nash equilibrium as a solution in these multi-agent interaction problems. In this paper, we present new and crucial adaptations of two well-known mechanisms, the adjustment process and the relaxation algorithm, in order to achieve the goal of computing Nash equilibria. The advantages of these approaches are highlighted and compared with those available in the literature.

2017

Long Term Impacts of RES-E Promotion in the Brazilian Power System

Autores
Pires Coelho, MDP; Saraiva, JT; Pereira, AJC;

Publicação
2017 IEEE MANCHESTER POWERTECH

Abstract
This paper analyzes the impact on market prices of the policies that have been adopted in Brazil to foster electricity from renewable energy sources (RES-E), namely wind power. In recent years the Brazilian Government implemented a series of policies that enabled a strong growth of RES-E. Recently more than 14 GW of wind and solar power were contracted. However, as most of the assets are concentrated in specific regions, these policies will induce price differences among areas of the country. In this scope, this paper describes a System Dynamics based model of the Brazilian generation system to evaluate the impact on prices from the deployment of these new sources. The paper describes simulations using realistic data for the Brazilian power system and the results suggest that the difference of prices in the country tend to increase since the Northeast region of the country concentrates most of the wind parks.

2014

Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices

Autores
Guerreiro, CA; Saraiva, JT; Sousa, JC; Mendes, VT;

Publicação
International Conference on the European Energy Market, EEM

Abstract
With the advent of restructuring, generation companies have to plan the operation of their stations in order to maximize their profits. This is very relevant for companies having a large share of hydro stations, and even more if these stations have pumping capacity. This paper describes a model to plan the operation of a set of hydro stations eventually installed in cascade and admitting that some of them are pumping stations. Once a first set of operation orders is obtained using a Genetic Algorithm, their generation/load values are included in the expected market selling/buying curves and the hourly prices are updated. These prices are then used to refine the operation orders originating an iterative process so that hydro stations are price makers. The paper includes results for a hydro system in order to illustrate the application of the developed approach. © 2014 IEEE.

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