Multi-criteria optimisation approach to increase the delivered power in radial distribution networks

This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Energy-efficient MAC protocols for WBANs: Opportunities and challenges

Wireless body area networks (WBANs) are expected to play a significant role in smart healthcare systems. One of the most important attributes of WBANs is to increase network lifetime by introducing novel and low-power techniques on the energy-constrained sensor nodes. Medium access control (MAC) protocols play a significant role in determining the energy consumption in WBANs. Existing MAC protocols are unable to accommodate communication requirements in WBANs. There is a need to develop novel, scalable and reliable MAC protocols that must be able to address all these requirements in a reliable manner. In this special issue, we attracted high quality research and review papers on the recent advances in MAC protocols for WBANs.

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

Análise da viabilidade económica da implementação de uma central de micro-cogeração no setor da agropecuária

O crescente aumento do consumo energético das sociedades desenvolvidas e emergentes, motivado pelo progresso económico e social, tem induzido a procura de alternativas focalizadas nas energias renováveis, que possam contribuir para assegurar o fornecimento de energia sem agravar o consumo de combustíveis fósseis e a emissão de gases com efeito de estufa. Nesse sentido, a produção de energia eléctrica a partir do gás metano resultante da estabilização anaeróbia de efluentes tem vindo a ser estudada e praticada desde finais do século XIX, tendo assumido maior expressão a partir dos anos 70 do século XX, na sequência das primeiras crises petrolíferas. As instalações agropecuárias reúnem dois fatores chave para o sucesso do aproveitamento energético do biogás produzido no tratamento dos efluentes: por um lado, produzem matéria-prima com potencial energético – dejeto animal com um potencial enorme de criação de biogás quando procedido de tratamento anaeróbio - e, por outro, necessitam de energia eléctrica para o funcionamento dos equipamentos electromecânicos e de calor para a manutenção das instalações. A valorização energética do biogás produzido na estabilização anaeróbia dos efluentes agro-pecuários, para além de permitir obter um retorno financeiro, que contribui para o equilíbrio dos custos de investimento e de exploração, contribui igualmente para a redução das emissões de gases com efeito de estufa, como o dióxido de carbono e o metano, e para a segurança de abastecimento energético à instalação, na medida em que assegura a alimentação de energia eléctrica em caso de falha no fornecimento pela rede nacional. A presente dissertação apresenta um contributo para estudos a desenvolver por proprietários de agropecuárias, cooperativas regionais do setor da agropecuária, empresas de projecto e estudantes de Engenharia, constituído por uma compilação da informação mais relevante associada à estabilização anaeróbia de efluentes e à valorização energética do biogás produzido. Com base em informação referente ao número real de animais existentes em Portugal, este trabalho pretende fazer ver a essas entidades que o aproveitamento energético do biogás é viável e útil para o país. Com a criação de uma aplicação informática de análise económica de investimento, provar que o investimento em pequenas propriedades, com apenas 80 cabeças normais, pode obter um retorno financeiro razoável, com um prazo de recuperação do investimento bastante baixo, aproveitando um recurso que caso contrário será desperdiçado e poluirá o ambiente.