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- Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systemsPublication . Canizes, Bruno; Soares, João; Vale, Zita; Khodr, H. M.This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.
- Power Quality of Renewable Energy Source Systems: A New Paradigm of Electrical GridsPublication . Baptista, José; Faria, Pedro; Canizes, Bruno; Pinto, TiagoThe power quality delivered by the distribution companies to consumers has always been a relevant issue, especially to industrial consumers, where power quality is directly related to productivity. However, until a few years ago, power quality was mostly synonymous with continuity of service, and the main concern was the minimization of power interruptions. Since the last decade of the twentieth century, power quality has become a strategic issue for all sectors involved in this market, from distribution companies to consumers, with a particular emphasis on industrial consumers as well as equipment manufacturers. The concept of power quality involves a wide range of electromagnetic phenomena that can occur in the power grid. Such changes may occur in different parts of the electrical power system, at customer facilities, or in the distribution network. In recent years, the electric power market has undergone huge transformations, electricity production has become decentralized, and consumers (who can now also be producers) have the opportunity to choose their supplier. The integration of renewable-based microgeneration systems into distribution grids has brought various disturbances to the grid (harmonics, voltage unbalance, voltage fluctuations, frequency deviations, etc.), leading to increasingly degraded power quality. This Special Issue focuses on the analysis of the consequences that renewables-based microgeneration systems have on power networks by finding new solutions for networks management (network optimization models, efficiency, and losses), integrating consumers and micro-producers in order to keep quality parameters at high levels. In this Special Issue, we can see that the interdisciplinarity of these issues is very present among researchers and scholars, who are well aware of the importance and impact that the new paradigm of network management brings in various domains, reflecting on the quality of the contributions submitted. Accordingly, the papers selected for publication cover a wide range of application topics, including electrical mobility, energy storage systems, facility management and control, impact analysis of different types of renewable energy sources, with focus on wind and solar generation, in both low-voltage (LV) and medium-voltage (MV) networks.
- Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-gridPublication . Soares, João; Sousa, Tiago; Morais, Hugo; Vale, Zita; Canizes, Bruno; Silva, António S.This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
- Benders’ Decomposition Applied to Energy Resource Management in Smart Distribution NetworksPublication . Soares, João; Canizes, Bruno; Vale, ZitaThis paper proposes a Benders’ decomposition approach for the large-scale Energy Resource Management (ERM). The problem considers large amount of Distributed Energy Resources (DER) including Electric Vehicles (EVs) with gridable capacity. The proposed model is designed for Virtual Power Players/Plants (VPPs) managing a smart distribution network with the aim to maximize profits considering the dayahead time horizon. Previous literature has shown difficulties in solving similar problems using classical techniques in a centralized scheme, namely considering nonlinear network constrains. The proposed approach reduces computational burden of the original Mixed Integer Nonlinear Programming (MINLP) problem. The Benders’ cuts are introduced for the ERM formulation in order to allow the communication between the slave and the master problem. Analysis of two large-scale instances have been carried out for smart distribution networks, namely a 33-bus and a real Portuguese 180-bus network assuming high penetration of DERs and EVs.
- LMP based bid formation for virtual power players operating in smart gridsPublication . Vale, Zita; Morais, H.; Faria, Pedro; Canizes, Bruno; Sousa, TiagoPower system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.
- Electric vehicles local flexibility strategies for congestion relief on distribution networksPublication . Soares, João; Almeida, José; Gomes, Lucas; Canizes, Bruno; Vale, Zita; Neto, EdisonDue to the rising concern for the environment and sustainability issues, the transportation system is experiencing important changes to its paradigm, with the increasing replacement of internal combustion vehicles by electric ones. Consequently, the electric systems need to adapt to the ever-increasing load demand from the grid and the challenge to identify driving patterns in electric vehicle users’ behavior. To prepare the grid for these changes, it is necessary to study the behavior of EV users and develop strategies to cope with the growing demand for electric vehicles. Knowing that electric vehicles experience long-parked periods at the charging stations (more than necessary to fully recharge the battery), this research paper proposes an EV charging strategy that intelligently explores these long-parked times. It interrupts charging of EVs that have enough charge to start their trip from certain charging stations to alleviate problems in the network in exchange for a certain incentive. This methodology is then applied in a realistic smart city to investigate its application. The results show that the proposed methodology brings benefits to the distribution network to relieve line congestion and improve the voltage magnitude at the network buses.
- Optimal Location of Normally Open Switches in Order to Minimize Power Losses in Distribution NetworksPublication . Batista, Samuel; Canizes, Bruno; Oliveira, António; Nogueira, Teresa; Vale, ZitaThis paper presents a deterministic optimization technique for the optimal location of normally open switch on a real distribution network, located in north of Portugal. The goal is to find the optimal radial topology that minimizes the power losses. The method is developed in TOMLAB software, and is formulated as a mixed integer quadratic programming problem. Given the current characteristics of the network, the method is based on optimal power flow through DC model. The power losses are given by the Joule effect, calculated according to each distribution line. In order to prove the viability of the obtained results, the proposed methodology is compared with a software used by Portuguese operator for distribution networks planning.
- Transmission costs allocation based on optimal re-dispatchPublication . Ferreira, Judite; Vale, Zita; Sousa, Tiago; Canizes, Bruno; Puga, RicardoCongestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.
- Energy Resource Scheduling Optimization for Smart Power Distribution Grids - Hour-Ahead HorizonPublication . Canizes, Bruno; Soares, João; Almeida, José; Paris, Wanderley; Vale, ZitaAs the use of renewable energy sources grows, the energy aggregator company plays an increasingly significant role in ensuring extremely flexible supply and demand, as requested by the smart grid architecture. This study presents a model for the problem of intraday energy resource scheduling (hour-ahead). The model is solved using the CPLEX solver and is developed as mixed integer linear programming. A distribution network with 180 buses located in Portugal considering high distributed energy resources penetration is used to demonstrate the application of the proposed model. The findings indicate how forecast errors and contractual restrictions with energy storage systems and electric car charging stations affect hour-ahead scheduling costs.
- Evolutionary Algorithms for Energy Scheduling under uncertainty considering Multiple AggregatorsPublication . Almeida, José; Soares, João; Canizes, Bruno; Lezama, Fernando; Fotouhi Ghazvini, Mohammad Ali; Vale, ZitaThe ever-increasing number of electric vehicles (EVs) circulating on the roads and renewable energy production to achieve carbon footprint reduction targets has brought many challenges to the electrical grid. The increasing integration of distributed energy resources (DER) in the grid is causing severe operational challenges, such as congestion and overloading for the grid. Active management of distribution network using the smart grid (SG) technologies and artificial intelligence (AI) techniques can support the grid's operation under such situations. Implementing evolutionary computational algorithms has become possible using SG technologies. This paper proposes an optimal day-ahead resource scheduling to minimize multiple aggregators' operational costs in a SG, considering a high DER penetration. The optimization is achieved considering three metaheuristics (DE, HyDE-DF, CUMDANCauchy++). Results show that CUMDANCauchy++ and HyDE-DF present the best overall results in comparison to the standard DE.