Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Publications

Publications by José Pedro Iria

2015

The STABALID project: Risk analysis of stationary Li-ion batteries for power system applications

Authors
Soares, FJ; Carvalho, L; Costa, IC; Iria, JP; Bodet, JM; Jacinto, G; Lecocq, A; Roessner, J; Caillard, B; Salvi, O;

Publication
RELIABILITY ENGINEERING & SYSTEM SAFETY

Abstract
This work presents a risk analysis performed to stationary Li-ion batteries within the framework of the STABALID project. The risk analysis had as main objective analysing the variety of hazards and dangerous situations that might be experienced by the battery during its life cycle and providing useful information on how to prevent or manage those undesired events. The first task of the risk analysis was the identification of all the hazards (or risks) that may arise during the battery life cycle. Afterwards, the hazards identified were mapped in the different stages of the battery life cycle and two analyses were performed for each stage: an internal problem analysis and an external peril analysis. For both, the dangerous phenomena and the undesirable events resulting from each hazard was evaluated in terms of probability of occurrence and severity. Then, a risk assessment was carried out according to a predefined risk matrix and a preliminary set of risk mitigation measures were proposed to reduce their probability of occurrence and/or their severity level. The results obtained show that it is possible to reduce the probability of occurrence/severity of all the risks associated to the battery life cycle to acceptable or tolerable levels.

2019

Trading Small Prosumers Flexibility in the Energy and Tertiary Reserve Markets

Authors
Iria, JP; Soares, FJ; Matos, MA;

Publication
IEEE TRANSACTIONS ON SMART GRID

Abstract
This paper addresses the participation of an aggregator of small prosumersin the energy and tertiary reserve markets. A two-stage stochastic optimization model is proposed to exploit the load and generation flexibility of the prosumers. The aim is to define energy and tertiary reserve bids to minimize the net cost of the aggregator buying and selling energy in the day-ahead and real-time markets, as well as to maximize the revenue of selling tertiary reserve during the real-time stage. Scenario-based stochastic programming is used to deal with the uncertainties of photovoltaic power generation, electricity demand, outdoor temperature, end-users' behavior, and preferences. A case study of 1000 small prosumers from MIBEL is used to compare the proposed strategy to two other strategies. The numerical results show that the proposed strategy reduces the bidding net cost of the aggregator by 48% when compared to an inflexible strategy typically used by retailers.

2017

Using Choreographies to Support the Gamification Process on the Development of an Application to Reduce Electricity Costs

Authors
Cassola, F; Iria, J; Paredes, H; Morgado, L; Coelho, A; Soares, F;

Publication
GAMES AND LEARNING ALLIANCE, GALA 2017

Abstract
Building automation systems contribute to reduce electricity costs by managing distributed energy resources in an efficient way. However, a large share of consumption cannot be optimized through automation alone, since it mainly depends on human interactions. Gamification can be used as one form of changing users’ behaviours [1], but its implementation does require assumptions on the behaviour patterns that need to be identified, encouraged, or discouraged. To tackle this problem, we propose a framework that joins building automation solutions with gamification techniques to enable behavioural demand response.

2017

Trading Small Prosumers Flexibility in the Day-ahead Energy Market

Authors
Iria, JP; Soares, FJ; Matos, MA;

Publication
2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING

Abstract
This paper addresses the bidding problem faced by an aggregator of small prosumers, when participating in the day ahead energy market. A two-stage stochastic optimization model is proposed to support the aggregator in the definition of optimal and robust demand and supply bids. Stochastic programing is used to deal with uncertainty of end-users' behavior, outdoor temperature, electricity demand and PV generation. The proposed approach was compared to other benchmark strategy, using a case study of 1000 prosumers from the Iberian market.

2018

Optimal supply and demand bidding strategy for an aggregator of small prosumers

Authors
Iria, J; Soares, F; Matos, M;

Publication
APPLIED ENERGY

Abstract
This paper addresses the problem faced by an aggregator of small prosumers, when participating in the energy market. The aggregator exploits the flexibility of prosumers' appliances, in order to reduce its market net costs. Two optimization procedures are proposed. A two-stage stochastic optimization model to support the aggregator in the definition of demand and supply bids. The aim is to minimize the net cost of the aggregator buying and selling energy at day-ahead and real-time market stages. Scenario-based stochastic programing is used to deal with the uncertainty of electricity demand, end-users' behavior, outdoor temperature and renewable generation. The second optimization is a model predictive control method to set the operation of flexible loads in real-time. A case study of 1000 small prosumers from the Iberian market is used to compare four day-ahead bidding strategies and two real-time control strategies, as well as the performance of combined day-ahead and real-time strategies. The numerical results show that the proposed strategies allow the aggregator to reduce the net cost by 14% compared to a benchmark typically used by retailers (inflexible strategy).

2017

Stochastic Market Clearing Model with Probabilistic Participation of Wind and Electric Vehicles

Authors
Neyestani, N; Soares, FJ; Iria, JP;

Publication
2017 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE)

Abstract
In this paper, a mixed-integer linear programing (MILP) model for the stochastic clearing of electricity markets with probabilistic participants is proposed. It is assumed that the sources of uncertainty in the market comes both from generation and demand side. The wind generating unit and electric vehicle aggregator are the supposed sources of uncertainty in the system. For the compensation of probable deviation of stochastic participants, flexible generation and demand will offer for the reserve activation. The two-stage model takes into account the day-ahead cost as well as the expected balancing costs due to probabilistic behavior of uncertain participants. A scenario-based approach is used to model the probabilistic participants. The proposed model stochastically clears the market and the results discuss the lower costs obtained by incorporating various resources of uncertainty and flexibility in the market.

  • 2
  • 8