Trade & Cap: A Customer-Managed, Market-Based System for Trading Bandwidth Allowances at a Shared Link

We propose Trade & Cap (T&C), an economics-inspired mechanism that incentivizes users to voluntarily coordinate their consumption of the bandwidth of a shared resource (e.g., a DSLAM link) so as to converge on what they perceive to be an equitable allocation, while ensuring efficient resource utilization. Under T&C, rather than acting as an arbiter, an Internet Service Provider (ISP) acts as an enforcer of what the community of rational users sharing the resource decides is a fair allocation of that resource. Our T&C mechanism proceeds in two phases. In the first, software agents acting on behalf of users engage in a strategic trading game in which each user agent selfishly chooses bandwidth slots to reserve in support of primary, interactive network usage activities. In the second phase, each user is allowed to acquire additional bandwidth slots in support of presumed open-ended need for fluid bandwidth, catering to secondary applications. The acquisition of this fluid bandwidth is subject to the remaining "buying power" of each user and by prevalent "market prices" – both of which are determined by the results of the trading phase and a desirable aggregate cap on link utilization. We present analytical results that establish the underpinnings of our T&C mechanism, including game-theoretic results pertaining to the trading phase, and pricing of fluid bandwidth allocation pertaining to the capping phase. Using real network traces, we present extensive experimental results that demonstrate the benefits of our scheme, which we also show to be practical by highlighting the salient features of an efficient implementation architecture.National Science Foundation (CCF-0820138, CSR-0720604, EFRI-0735974, CNS-0524477, and CNS-0520166); Universidad Pontificia Bolivariana and COLCIENCIAS–Instituto Colombiano para el Desarrollo de la Ciencia y la Tecnología “Francisco Jose ́ de Caldas”

Study and analysis of the use of flexibility in local electricity markets

In this work an introduction to Local Electricity Markets (LEM) was done and afterwards evolutionary algorithms (EAs) such as Differential Evolution (DE), HybridAdaptive Differential Evolution (HyDE), Hybrid-Adaptive Differential Evolution with Decay Function (HyDE-DF) and Vortex Search (VS) were applied to a market model in order to test its efficiency and scalability. Then, the market model was expanded adding a network model from the BISITE laboratory and again tests using the evolutionary algorithms were performed. In more detail, first a literature review is done about distributed generation, load flexibility, LEM and EAs. Then a cost optimization problem in Local Electricity Markets is analyzed considering fixed-term flexibility contracts between the distribution system operator (DSO) and aggregators. In this market structure, the DSO procures flexibility while aggregators of different types (e.g., conventional demand response or thermo-load aggregators) offer the service. Its then solved the proposed model using evolutionary algorithms based on the well-known differential evolution (DE). First, a parameter-tuning analysis is done to assess the impact of the DE parameters on the quality of solutions to the problem. Later, after finding the best set of parameters for the “tuned” DE strategies, we compare their performance with other self-adaptive parameter algorithms, namely the HyDE, HyDE-DF, and VS. Overall, the algorithms are able to find near-optimal solutions to the problem and can be considered an alternative solver for more complex instances of the model. After this a network model, from BISITE laboratory, is added to the problem and new analyses are performed using evolutionary algorithms along with MATPOWER power flow algorithms. Results show that evolutionary algorithms support from simple to complex problems, that is, it is a scalable algorithm, and with these results it is possible to perform analyses of the proposed market model.Neste trabalho foi feita uma introdução aos Mercados Locais de Eletricidade (MLE) e posteriormente foram aplicados algoritmos evolutivos (AEs) como Differential Evolution (DE), Hybrid-Adaptive Differential Evolution (HyDE), Hybrid-Adaptive Differential Evolution with Decay Function (HyDE-DF) e Vortex Search (VS) a um modelo de mercado a fim de testar a sua eficiência e escalabilidade. O modelo de mercado foi expandido adicionando uma rede do laboratório BISITE e novamente foram realizados testes usando os algoritmos evolutivos. Em mais detalhe, no trabalho primeiro foi feita uma revisão bibliográfica sobre geração distribuída, flexibilidade de carga, MLE e AEs. É analisado um problema de optimização de custos nos MLE, considerando contratos de flexibilidade a prazo fixo entre os agentes. O distribuidor adquire flexibilidade enquanto que os agregadores de diferentes tipos (por exemplo, os agregadores convencionais de resposta à procura ou de carga térmica) oferecem o serviço. Resolve-se depois o modelo proposto utilizando AEs baseados na conhecida DE. É feita uma análise de afinação de parâmetros para avaliar o impacto dos parâmetros DE na qualidade das soluções para o problema. Após encontrarmos o melhor conjunto de parâmetros para as estratégias DE "afinadas", comparamos o seu desempenho com outros algoritmos de parâmetros autoadaptáveis, nomeadamente o HyDE, HyDE-DF, e VS. Globalmente, os algoritmos são capazes de encontrar soluções quase óptimas para o problema e podem ser considerados um solucionador alternativo para instâncias mais complexas do modelo. Então um modelo de rede, do laboratório BISITE, é acrescentado ao problema e novas análises são realizadas utilizando algoritmos evolutivos juntamente com algoritmos de fluxo de potência MATPOWER. Os resultados mostram que os algoritmos evolutivos suportam desde problemas simples a complexos, ou seja, é um algoritmo escalável, e com estes resultados é possível realizar análises do modelo de mercado proposto

Transactive Multi-Agent Systems over Flow Networks

This paper presented insights into the implementation of transactive multi-agent systems over flow networks where local resources are decentralized. Agents have local resource demand and supply, and are interconnected through a flow network to support the sharing of local resources while respecting restricted sharing/flow capacity. We first establish a competitive market with a pricing mechanism that internalizes flow capacity constraints into agents' private decisions. We then demonstrate through duality theory that competitive equilibrium and social welfare equilibrium exist and agree under convexity assumptions, indicating the efficiency of the pricing mechanism. Additionally, a new social acceptance sharing problem is defined to investigate homogeneous pricing when the optimal sharing prices at all agents under competitive equilibrium are always equal for social acceptance. A conceptual computation method is proposed, prescribing a class of socially admissible utility functions to solve the social acceptance problem. A special case of linear-quadratic multi-agent systems over undirected star graphs is provided as a pedagogical example of how to explicitly prescribe socially admissible utility functions. Finally, extensive experiments are provided to validate the results