ISEP - GECAD - Grupo de Investigação em Engenharia do Conhecimento a Apoio à Decisão
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GECAD is a research unit settled in the Institute of Engineering - Polytechnic of Porto (ISEP/IPP) having as mission the promotion and development of scientific research in the Knowledge and Decision Sciences domains, having Information Technologies as support. It involves 2 research groups: Intelligent Systems and Power Energy Systems. GECAD is known worldwide in its areas of research, leading some research domains. [-]
GECAD is coordinated by Prof. Zita Vale, and recognized by FCT (Portuguese Science and Technology Foundation). 79 researchers are involved in GECAD, including 37 with PhD degree. It is the largest R&D unit from the Polytechnic sub-system of Portugal.
GECAD was involved in more than 60 R&D projects (more than 20 on-going projects now) with external funding. We are one of the Portuguese R&D units with more success at this level. Just a number, 8, is the number of projects assigned to GECAD in the last FCT Call for Projects. GECAD has a tremendous success in publications in important scientific journals; many special issues of these journals are edited by GECAD researchers.
Understanding its responsibility for the Society development, GECAD has decided to adopt a new slogan: “Intelligence for a Sustainable, Safe, and Inclusive World”. For this reason, the most recent GECAD projects are applied to areas like Energy, Transportation, Environment, Economy, Inclusion, Critical Infrastructures, Security, Information Access and new ways of Socialization.
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Browsing ISEP - GECAD - Grupo de Investigação em Engenharia do Conhecimento a Apoio à Decisão by Author "Abrishambaf, Omid"
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- Aggregation of Consumers Participation in the Ramping of a Demand Response EventPublication . Abrishambaf, Omid; Faria, Pedro; Vale, ZitaAs the global population is daily soaring, the need for electrical energy is also increasing. This makes the role of the power distribution network more tangible, as the efficiency of all sectors should be increased. The need for smart management and strategic planning, such as demand response programs are obvious in the context. This paper proposes an aggregator model that employs DR programs for managing the network balance. In this model, a specific analysis has been provided for the ramp period and demand response timeline to show the financial behaviors of the aggregator. In the case study of the paper, two demand response events are proposed using actual consumption profiles and a cost comparison has been presented using various pricing schemes. The results remark the costs related to the ramp period before the event and show how such costs are important in daily electricity expenses of the aggregator model.
- Agricultural irrigation scheduling for a crop management system considering water and energy use optimizationPublication . Abrishambaf, Omid; Faria, Pedro; Gomes, Luis; Vale, ZitaCenter pivot systems are widely used to overcome the irrigation needs of agricultural fields. In this paper, an autonomous approach is proposed in order to improve the low efficiency of irrigation by developing a system based on the water requirement of the plantations, through field data. The data are local temperature, local wind, soil moisture, precipitation forecast, and soil evapotranspiration calculation. This information enables the system to calculate the real evapotranspiration for not being necessary to restrict to lysimetric measures. By this way, the system schedules the irrigation for the lower cost periods, considering the produced energy by the local resources, and the price of energy purchased from the utility grid. Also, it is considered that the irrigation must be carried out within the time interval in which the plantations do not reach the wilding point, so it will be carried out at the periods with the lowest cost. This will optimize the overall operational costs of the irrigation.
- Air conditioner consumption optimization in an office building considering user comfortPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaThe rapid growth of energy consumption and its consequences in the last decades, made the world persuaded to energy optimization and energy management. Therefore, producers and prosumers should be equipped with the automation infrastructures to perform the management programs, such as demand response programs. Office buildings are considering as a proper case for implementing energy consumption minimization since they are responsible for a huge portion of total energy consumption in the world. This paper proposes a multi-period optimization algorithm implemented in Supervisory Control and Data Acquisition system of an office building. The developed optimization algorithm is an efficient solution considered for minimizing the power consumption of air conditioners by considering the user comfort constraints. Two determinative parameters are defined to prevent over-power reduction from certain devices. In order to respect to user preferences, priority numbers are dedicated to each air conditioner to present the importance of each device. A case study with several scenarios is implemented to verify the performance of the proposed algorithm in real life using real data of the building. The obtained results show the impacts of proposed parameters and different comfort constraints of algorithm while the main target of the optimization has been reached.
- An Aggregation Model for Energy Resources Management and Market NegotiationsPublication . Abrishambaf, Omid; Faria, Pedro; Spínola, João; Vale, ZitaCurrently the use of distributed energy resources, especially renewable generation, and demand response programs are widely discussed in scientific contexts, since they are a reality in nowadays electricity markets and distribution networks. In order to benefit from these concepts, an efficient energy management system is needed to prevent energy wasting and increase profits. In this paper, an optimization based aggregation model is presented for distributed energy resources and demand response program management. This aggregation model allows different types of customers to participate in electricity market through several tariffs based demand response programs. The optimization algorithm is a mixed-integer linear problem, which focuses on minimizing operational costs of the aggregator. Moreover, the aggregation process has been done via K-Means clustering algorithm, which obtains the aggregated costs and energy of resources for remuneration. By this way, the aggregator is aware of energy available and minimum selling price in order to participate in the market with profit. A realistic low voltage distribution network has been proposed as a case study in order to test and validate the proposed methodology. This distribution network consists of 25 distributed generation units, including photovoltaic, wind and biomass generation, and 20 consumers, including residential, commercial, and industrial buildings.
- An Optimization Algorithm for Cost Minimization in Residential BuildingsPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaThe increment of the electricity consumption around the world has led many efforts on the network operators to reduce the consumption in the demand side and encourage to increase the use of renewable energies. Since the buildings have a significant part in energy consumption, and lighting systems have an important role in the energy consumption of the buildings, the optimization of the lighting system should be effective. Hence, the focus of this paper is to minimize the lamps consumption of a residential house based on electricity price and try to take advantages from photovoltaic generation as much as possible. The methodology of this work is proposed as a linear optimization problem that manages the generation of a renewable energy resource, which supplies a part of the energy consumption of the house. For the case studies, the amount of the renewable energy generation, total consumption of building, consumption of the lights, and electricity price are considered.
- An Optimization Based Community Model of Consumers and Prosumers: A Real-Time Simulation and Emulation ApproachPublication . Abrishambaf, Omid; Silva, Cátia; Faria, Pedro; Vale, ZitaThe electricity consumption pattern is being increased day by day. Currently, network operators are moving towards renewable energy resources and applying demand response programs. However, the small and medium scale consumers and producers are needed to be aggregated and participate in the electricity markets as a unique resource. This paper proposes an optimization-based community model for aggregating the small scales consumers and producers. The model includes a central controller, which is considered as an aggregator, and several local community managers to keep the network balanced locally. Furthermore. real-time simulation approach and several real devices as hardware-in-the-loop are used to validate the system under practical challenges. The results of the paper reveal a gap between the simulation and experimental results and prove the performance of system in real-time mode using actual devices.
- Application of a Home Energy Management System for Incentive-Based Demand Response Program ImplementationPublication . Abrishambaf, Omid; Fotouhi Ghazvini, Mohammad Ali; Gomes, Luis; Faria, Pedro; Vale, Zita; Corchado, Juan M.This paper presents an experimental real-time implementation of an incentive-based demand response program with hardware demonstration of a home energy management system. This system controls the electricity consumption of a residential electricity customer. For this purpose, the real consumption and generation profiles of a typical Portuguese household equipped with a home-scale photovoltaic system are employed. These profiles are simulated by the real-time digital simulator using real hardware resources. In the case studies, three different scenarios are simulated for a period of 24 hours with the consideration of the demand response programs and a 2 kW photovoltaic system. Different pricing scenarios are considered and the performance of the home energy management system is evaluated under each scenario. The focus is given to demonstrate how a home-scale photovoltaic system, and demand response programs, especially load-shifting scenario, can be cost-effective in the daily electricity costs of the residential customers.
- Application of an optimization-based curtailment service provider in real-time simulationPublication . Abrishambaf, Omid; Faria, Pedro; Vale, ZitaThe use of demand response programs and distributed renewable energy resources are intensively discussed. These concepts play a key role in the distribution network, especially smart grids and microgrids. Nowadays, most of the implemented demand response programs are considered for large-scale resources, which make small and medium resources unable to participate in electricity market negotiations. In order to overcome this barrier, a third-party entity, namely an aggregator, can be considered as an intermediate player between the demand side and grid side. For this purpose, curtailment service provider is considered as an aggregator, which aggregates small and medium-scale resources, who do not have adequate capacity of reduction or generation and allow them to participate in wholesale electricity markets as a unique resource. However, before massive implementation of business models, the performance of the curtailment service provider should be adequately surveyed and validated in order to prevent future problems. This paper proposes a real-time simulation model of a curtailment service provider, which employs several real and laboratory hardware equipment considered as hardware-in-the-loop in the real-time simulator. Furthermore, an optimization problem is developed for a curtailment service provider in order to optimally schedule the available resources including several demand response programs and distributed renewable resources, aiming at minimizing its operation costs. The implemented case study considers a distribution network with 20 consumers and prosumers, and 26 renewable-based producers including wind and photovoltaic generation, where the developed model is performed in real-time for 12 min and behaviors of small and medium prosumers and producers is surveyed.
- Applying real-time pricing for wind curtailment scenario using D2RD module of TOOCCPublication . Teixeira, Brígida; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaMulti-agent systems are widely used tools to simulate and study the energy sector because of their distributed architecture. There are several simulator tools available in literature, however, much of these prove to be very domain specific. The emergence of the Tools Control Center tool allows these simulators to cooperate in order to solve more comprehensive problems and more complex scenarios. This paper presents a module of this tool known as Demand Response Registration Digital, which allows the study of the model and programs of Demand Response. To understand the operation of this module, an example is given considering a wind curtailment scenario.
- Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy managementPublication . Faia, R.; Pinto, Tiago; Abrishambaf, Omid; Fernandes, Filipe; Vale, Zita; Corchado, Juan ManuelThis paper proposes a novel Case Based Reasoning (CBR) application for intelligent management of energy resources in residential buildings. The proposed CBR approach enables analyzing the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. The innovations of the proposed CBR model are the application of the k-Nearest Neighbors algorithm (k-NN) clustering algorithm to identify similar past cases, the adaptation of Particle Swarm Optimization (PSO) meta-heuristic optimization method to optimize the choice of the variables that characterize each case, and the development of expert systems to adapt and refine the final solution. A case study is presented, which considers a knowledge base containing a set of scenarios obtained from the consumption of a residential building. In order to provide a response for a new case, the proposed CBR application selects the most similar cases and elaborates a response, which is provided to the SCADA House Intelligent Management (SHIM) system as input data. SHIM uses this specification to determine the loads that should be reduced in order to fulfill the reduction suggested by the CBR approach. Results show that the proposed approach is capable of suggesting the most adequate levels of reduction for the considered house, without compromising the comfort of the users.