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A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem

Publication . Vieira, Miguel; Faia, Ricardo; Lezama, Fernando; Canizes, Bruno; Vale, Zita

Energy community markets have emerged to promote prosumers' active participation and empowerment in the electrical power system. These initiatives allow prosumers to transact electricity locally without an intermediary such as an aggregator. However, it is necessary to implement optimization methods that determine the best transactions within the energy community, obtaining the best solution under these models. Particle Swarm Optimization (PSO) fits this type of problem well because it allows reaching results in short optimization times. Furthermore, applying this metaheuristic to the problem is easy compared to other available optimization tools. In this work, we provide a sensitivity analysis of the impact of different parameters of PSO in solving an energy community market problem. As a result, the combination of parameters that lead to the best results is obtained, demonstrating the effectiveness of PSO solving different case studies.

2022Conference object

Open access

Intraday Energy Resource Scheduling for Load Aggregators Considering Local Market

Publication . Almeida, José; Soares, João; Canizes, Bruno; Razo-Zapata, Ivan; Vale, Zita

Demand response (DR) programs and local markets (LM) are two suitable technologies to mitigate the high penetration of distributed energy resources (DER) that is vastly increasing even during the current pandemic in the world. It is intended to improve operation by incorporating such mechanisms in the energy resource management problem while mitigating the present issues with Smart Grid (SG) technologies and optimization techniques. This paper presents an efficient intraday energy resource management starting from the day-ahead time horizon, which considers load uncertainty and implements both DR programs and LM trading to reduce the operating costs of three load aggregator in an SG. A random perturbation was used to generate the intraday scenarios from the day-ahead time horizon. A recent evolutionary algorithm HyDE-DF, is used to achieve optimization. Results show that the aggregators can manage consumption and generation resources, including DR and power balance compensation, through an implemented LM.

2022Journal article

Open access

Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City

Publication . Canizes, Bruno; Soares, João; Vale, Zita; Corchado, Juan Manuel

The use of electric vehicles (EVs) is growing in popularity each year, and as a result, considerable demand increase is expected in the distribution network (DN). Additionally, the uncertainty of EV user behavior is high, making it urgent to understand its impact on the network. Thus, this paper proposes an EV user behavior simulator, which operates in conjunction with an innovative smart distribution locational marginal pricing based on operation/reconfiguration, for the purpose of understanding the impact of the dynamic energy pricing on both sides: the grid and the user. The main goal, besides the distribution system operator (DSO) expenditure minimization, is to understand how and to what extent dynamic pricing of energy for EV charging can positively affect the operation of the smart grid and the EV charging cost. A smart city with a 13-bus DN and a high penetration of distributed energy resources is used to demonstrate the application of the proposed models. The results demonstrate that dynamic energy pricing for EV charging is an efficient approach that increases monetary savings considerably for both the DSO and EV users.

2019Journal article

Open access

An Optimization Model for Energy Community Costs Minimization Considering a Local Electricity Market between Prosumers and Electric Vehicles

Publication . Faia, Ricardo; Soares, João; Vale, Zita; Corchado, Juan Manuel

Electric vehicles have emerged as one of the most promising technologies, and their mass introduction may pose threats to the electricity grid. Several solutions have been proposed in an attempt to overcome this challenge in order to ease the integration of electric vehicles. A promising concept that can contribute to the proliferation of electric vehicles is the local electricity market. In this way, consumers and prosumers may transact electricity between peers at the local community level, reducing congestion, energy costs and the necessity of intermediary players such as retailers. Thus, this paper proposes an optimization model that simulates an electric energy market between prosumers and electric vehicles. An energy community with different types of prosumers is considered (household, commercial and industrial), and each of them is equipped with a photovoltaic panel and a battery system. This market is considered local because it takes place within a distribution grid and a local energy community. A mixed-integer linear programming model is proposed to solve the local energy transaction problem. The results suggest that our approach can provide a reduction between 1.6% to 3.5% in community energy costs

2021Journal article

Open access

Safety Isolating Transformer Design using HyDE-DF algorithm

Publication . Soares, João; Lezama, Fernando; Vale, Zita; Brisset, Stephane; Francois, Bruno

This paper presents an application of Evolutionary Computation (EC) to the benchmark of the safety isolating transformer problem. The benchmark adopts multidisciplinary optimization strategies, namely the multidisciplinary feasible (MDF) and the individual discipline feasible (IDF) formulations. The benchmark meets the requirements of engineers and scientists working with machine design problem, such as in the first part of the design process that is the choice of structure and materials. The EC methods employed in this paper are based on Evolutionary Algorithms (EAs), namely two variants of Differential Evolution (DE), two variants of Hybrid Adaptive DE (HyDE) and the Vortex Search (VS). The results showed in this paper suggest that EA methods are competitive with the classical optimization method, the sequential quadratic programming (SQP). Among the developed EAs, HyDE-DF is able to obtain better values than SQP on a significant battery of trials.

2020Conference object

Open access