Polytechnic Institute of Porto

www.ipp.pt
Porto, Portugal

The Polytechnic Institute of Porto , also referred to as Porto Polytechnic for naming and branding purposes, is a higher learning Portuguese institution composed of diverse polytechnic schools based in Porto. The Porto Polytechnic developed as a metropolitan institution with schools in Porto, Matosinhos, Póvoa de Varzim2004 the Polytechnic had 15,000 students, a third of them in its major college, the ISEP. It also had about 1000 teachers. 7000 students competed to enter in that year and 2000 entered.The polytechnic is officially known as Instituto Politécnico do Porto or "Polytechnic Institute of Porto", but it decided to drop the "institute" name from the brand in order "to reinforce the institutional reference and to be easily known" said Vitor Santos, the president of the Polytechnic and former director of ISEP. Wikipedia.

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Faria P.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto | Baptista J.,Sudan University of Science and Technology
Energy Conversion and Management | Year: 2015

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods. © 2015 Elsevier Ltd. All rights reserved.

Document Keywords (matching the query): distributed generation resources, distributed generation, energy resources, distributed power generation, distributed energy resources.


Sousa T.,Polytechnic Institute of Porto | Morais H.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto | Faria P.,Polytechnic Institute of Porto | Soares J.,Polytechnic Institute of Porto
IEEE Transactions on Smart Grid | Year: 2012

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G users' profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources. © 2011 IEEE.

Document Keywords (matching the query): distributed generation, energy resources, distributed resources, distributed power generation, energy resource management, intelligent energies.


Faria P.,Polytechnic Institute of Porto | Soares T.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto | Morais H.,Technical University of Denmark
Renewable Energy | Year: 2014

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets.The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers. © 2014 Elsevier Ltd.

Document Keywords (matching the query): distributed generation.


Morais H.,Technical University of Denmark | Morais H.,Polytechnic Institute of Porto | Sousa T.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto | Faria P.,Polytechnic Institute of Porto
Energy Conversion and Management | Year: 2014

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management. © 2014 Elsevier Ltd. All rights reserved.

Document Keywords (matching the query): distributed generation, distributed generation units, renewable energy source, distributed power generation, distributed energy resources, renewable energy resources.


Vale Z.,Polytechnic Institute of Porto | Morais H.,Polytechnic Institute of Porto | Faria P.,Polytechnic Institute of Porto | Ramos C.,Polytechnic Institute of Porto
Renewable Energy | Year: 2013

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness).This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis.The paper includes a case study using a 114 bus distribution network and load demand based on real data. © 2012 Elsevier Ltd.

Document Keywords (matching the query): distributed generation, energy resources, distributed power generation, distributed energy resources, energy resource.


Soares J.,Polytechnic Institute of Porto | Morais H.,Polytechnic Institute of Porto | Sousa T.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto | Faria P.,Polytechnic Institute of Porto
IEEE Transactions on Smart Grid | Year: 2013

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs in the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Other important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method. © 2012 IEEE.

Document Keywords (matching the query): energy resource management, distributed power generation, energy resources, distributed resources, energy resource managements.


Faria P.,Polytechnic Institute of Porto | Soares J.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto | Morais H.,Polytechnic Institute of Porto | Sousa T.,Polytechnic Institute of Porto
IEEE Transactions on Smart Grid | Year: 2013

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. © 2013 IEEE.

Document Keywords (matching the query): distributed energy resource, energy resource management, energy resources, distributed power generation, energy resource managements.


Silva M.,Polytechnic Institute of Porto | Morais H.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto
Energy Conversion and Management | Year: 2012

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD®, is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD®. © 2012 Elsevier Ltd. All rights reserved.

Document Keywords (matching the query): energy resources, distributed power generation, distributed energy resources.


Sousa T.,Polytechnic Institute of Porto | Morais H.,Polytechnic Institute of Porto | Soares J.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto
Applied Energy | Year: 2012

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints.The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model.A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method. © 2012 Elsevier Ltd.

Document Keywords (matching the query): distributed generation, energy resources, energy use, energy planning, distributed power generation, energy resource, energy resource management, energy market, energy flux.


Morais H.,Technical University of Denmark | Morais H.,Polytechnic Institute of Porto | Faria P.,Polytechnic Institute of Porto | Vale Z.,Polytechnic Institute of Porto
International Journal of Electrical Power and Energy Systems | Year: 2014

Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper proposes a methodology to support VPPs in the DR programs' management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific programs in the LMP values supports the manager decision concerning the DR use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 33-bus network with intensive use of DG. © 2014 Elsevier Ltd. All rights reserved.

Document Keywords (matching the query): distributed generation, energy resources, distributed power generation.

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