Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

Realistic Multi-Agent Simulation of Competitive Electricity Markets

The dynamism and ongoing changes that the electricity markets sector is constantly suffering, enhanced by the huge increase in competitiveness, create the need of using simulation platforms to support operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents an enhanced electricity market simulator, based on multi-agent technology, which provides an advanced simulation framework for the study of real electricity markets operation, and the interactions between the involved players. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) uses real data for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations bring to different countries. Also, the development of an upper-ontology to support the communication between participating agents, provides the means for the integration of this simulator with other frameworks, such as MAN-REM (Multi-Agent Negotiation and Risk Management in Electricity Markets). A case study using the enhanced simulation platform that results from the integration of several systems and different tools is presented, with a scenario based on real data, simulating the MIBEL electricity market environment, and comparing the simulation performance with the real electricity market results.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Distributed Intelligent Management of Microgrids using a Multi-Agent Simulation Platform

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

Avaliação do desempenho energético de uma pequena fracção de serviços existente tendo por base as metodologias regulamentares do RSECE e do RECS

A dependência energética das grandes economias mundiais, alertaram o mundo para a necessidade de mudar o comportamento relativo ao consumo de energia. O sector dos edifícios representa 40% dos consumos globais de energia na União Europeia, já no panorama nacional, o sector dos edifícios representa 28% dos consumos globais da energia, constituindo uma parte significativa no consumo global de energia, sendo portanto, essencial avaliar o desempenho energético dos edifícios, no sentido de promover a sua eficiência energética e beneficiar do grande potencial de economia de energia. Portugal à luz das linhas de orientação da União Europeia com o objectivo de instigar o aumento da eficiência energética nos edifícios, lançou o programa nacional para a eficiência energética nos Edifícios (P3E). Posteriormente, da transposição da Directiva 2002/91/CE para a ordem jurídica nacional surgiu o SCE, o RCCTE e o RSECE. Já em 2013, com a necessidade de transpor para a ordem da jurídica nacional a Directiva n.º 2010/31/EU, surge o Decreto-Lei n.º 118/2013, reunindo num só diploma o SCE, o REH e o RECS, promovendo uma revisão da legislação nacional, garantindo e promovendo a melhoria do desempenho energético dos edifícios. Através da presente dissertação, pretende-se avaliar o desempenho energético de uma pequena fracção de serviços existente tendo por base a metodologia regulamentar revogada do RSECE e a vigente metodologia regulamentar do RECS. Após apresentação dos dois regulamentos e da identificação das principais diferenças entre as duas metodologias regulamentares, procedeu-se ao enquadramento da fracção em estudo no âmbito de aplicação do RSECE e do RECS. Segundo os dois regulamentos a fracção não está sujeita a requisitos mínimos de qualidade térmica, nem a quaisquer requisitos energéticos e de eficiência dos sistemas técnicos, ao tratar-se de uma pequena fracção de serviços existente. Recorrendo ao software DesignBuilder, gerou-se o modelo da fracção em estudo, que através da simulação dinâmica multizona permitiu obter os consumos de energia anuais e a sua desagregação por utilização final. A partir dos consumos energia, determinaram-se os indicadores de eficiência energética de acordo com as duas metodologias, permitindo deste modo, proceder à classificação energética da fracção em estudo. De acordo com o RSECE a fracção em estudo obteve a classificação D, já segundo o RECS alcançou a classe C. Para aumentar a eficiência energética da fracção e consequentemente diminuir o consumo energético, foi proposto proceder à substituição das lâmpadas existentes por lâmpadas tubulares de tecnologia LED e à substituição do sistema de ventilação mecânico por um sistema de ventilação dimensionado para os novos valores de caudal de ar novo regulamentares. Com a implementação destas duas medidas a fracção em estudo melhoraria a sua classificação energética, exigindo um investimento baixo e apresentando um período de retorno de 1 ano e 5 meses. Segundo o RSECE passaria para a classe B, e aplicando a metodologia regulamentar do RECS alcançaria a classe B-.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.

Trade-Off Performance Regions of Slotted ALOHA Protocol using Multi-Objective Optimization

10th Conference on Telecommunications (Conftele 2015), Aveiro, Portugal.

A Random Access Protocol incorporating Multi-Packet Reception, Retransmission Diversity and Successive Interference Cancellation

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.

A Multi-DAG Model for Real-Time Parallel Applications with Conditional Execution

The 30th ACM/SIGAPP Symposium On Applied Computing (SAC 2015). 13 to 17, Apr, 2015, Embedded Systems. Salamanca, Spain.

An efficient numerical scheme for solving multi-dimensional fractional optimal control problems with a quadratic performance index

The shifted Legendre orthogonal polynomials are used for the numerical solution of a new formulation for the multi-dimensional fractional optimal control problem (M-DFOCP) with a quadratic performance index. The fractional derivatives are described in the Caputo sense. The Lagrange multiplier method for the constrained extremum and the operational matrix of fractional integrals are used together with the help of the properties of the shifted Legendre orthonormal polynomials. The method reduces the M-DFOCP to a simpler problem that consists of solving a system of algebraic equations. For confirming the efficiency and accuracy of the proposed scheme, some test problems are implemented with their approximate solutions.

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures supported by an FTT-SE Network

Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

Serpentine bacteria influence metal translocation and bioconcentration of Brassica juncea and Ricinus communis grown in multi-metal polluted soils

The aim of this study was to assess the effects of inoculation of rhizosphere or endophytic bacteria (Psychrobacter sp. SRS8 and Pseudomonas sp. A3R3, respectively) isolated from a serpentine environment on the plant growth and the translocation and accumulation of Ni, Zn, and Fe by Brassica juncea and Ricinus communis on a multi-metal polluted serpentine soil (SS). Field collected SS was diluted to 0, 25, 50, and 75% with pristine soil in order to obtain a range of heavy metal concentrations and used in microcosm experiments. Regardless of inoculation with bacteria, the biomass of both plant species decreased with increase of the proportion of SS. Inoculation of plants with bacteria significantly increased the plant biomass and the heavy metal accumulation compared with non-inoculated control in the presence of different proportion of SS, which was attributed to the production of plant growth promoting and/or metal mobilizing metabolites by bacteria. However, SRS8 showed a maximum increase in the biomass of the test plants grown even in the treatment of 75% SS. In turn, A3R3 showed maximum effects on the accumulation of heavy metals in both plants. Regardless of inoculation of bacteria and proportion of SS, both plant species exhibited low values of bioconcentration factor (<1) for Ni and Fe. The inoculation of both bacterial strains significantly increased the translocation factor (TF) of Ni while decreasing the TF of Zn in both plant species. Besides this contrasting effect, the TFs of all metals were <1, indicating that all studied bacteria–plant combinations are suitable for phytostabilization. This study demonstrates that the bacterial isolates A3R3 and SRS8 improved the growth of B. juncea and R. communis in SS soils and have a great potential to be used as inoculants in phytostabilization scenarios of multi-metal contaminated soils.

The hyperaccumulator Sedum plumbizincicola harbors metal-resistant endophytic bacteria that improve its phytoextraction capacity in multi-metal contaminated soil

Endophyte-assisted phytoremediation has recently been suggested as a successful approach for ecological restoration of metal contaminated soils, however little information is available on the influence of endophytic bacteria on the phytoextraction capacity of metal hyperaccumulating plants in multi-metal polluted soils. The aims of our study were to isolate and characterize metal-resistant and 1-aminocyclopropane-1-carboxylate (ACC) utilizing endophytic bacteria from tissues of the newly discovered Zn/Cd hyperaccumulator Sedum plumbizincicola and to examine if these endophytic bacterial strains could improve the efficiency of phytoextraction of multi-metal contaminated soils. Among a collection of 42 metal resistant bacterial strains isolated from the tissues of S. plumbizincicola grown on Pb/Zn mine tailings, five plant growth promoting endophytic bacterial strains (PGPE) were selected due to their ability to promote plant growth and to utilize ACC as the sole nitrogen source. The five isolates were identified as Bacillus pumilus E2S2, Bacillus sp. E1S2, Bacillus sp. E4S1, Achromobacter sp. E4L5 and Stenotrophomonas sp. E1L and subsequent testing revealed that they all exhibited traits associated with plant growth promotion, such as production of indole-3-acetic acid and siderophores and solubilization of phosphorus. These five strains showed high resistance to heavy metals (Cd, Zn and Pb) and various antibiotics. Further, inoculation of these ACC utilizing strains significantly increased the concentrations of water extractable Cd and Zn in soil. Moreover, a pot experiment was conducted to elucidate the effects of inoculating metal-resistant ACC utilizing strains on the growth of S. plumbizincicola and its uptake of Cd, Zn and Pb in multi-metal contaminated soils. Out of the five strains, B. pumilus E2S2 significantly increased root (146%) and shoot (17%) length, fresh (37%) and dry biomass (32%) of S. plumbizincicola as well as plant Cd uptake (43%), whereas Bacillus sp. E1S2 significantly enhanced the accumulation of Zn (18%) in plants compared with non-inoculated controls. The inoculated strains also showed high levels of colonization in rhizosphere and plant tissues. Results demonstrate the potential to improve phytoextraction of soils contaminated with multiple heavy metals by inoculating metal hyperaccumulating plants with their own selected functional endophytic bacterial strains.