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Energy systems are in transition towards more sustainable generation portfolios. In the envisioned smart grid generation will primarily depend on renewable power sources making uncertain quantities of electricity available, the delivery of which cannot be guaranteed. Current electricity tariffs promise certain delivery, and are thus not well-suited to trade uncertain quantities. However, if not traded...
We present a unified model for flexibility services in the power system, identify two existing categories (ramping and loading) and introduce a new category (stalling). Each service is characterised by duration, capacity and effort, with associated prices. We show that the effort of stalling, measurable in kWh2, is a significant cost component for balancing through storage and demand response (DR)...
Renewable generation of energy is becoming more affordable, and is therefore increasingly adopted to match local demand. In addition, storage and demand response solutions have reached the market, which provides flexibility and thereby facilitates intelligent energy management. It has been suggested that this bottom-up flexibility should contribute to the balancing of the future smart grid, but financial...
Today’s society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are desirable, e.g., for reasons of stability or parallelism, they are highly complex and therefore difficult to understand or predict. Multi-agent learning has been acknowledged to be indispensable to control or find solutions for...
Many different value-based or policy-search reinforcement learning algorithms have been applied to multi-agent settings. Value-based learners estimate the expected return (value) for each state-action combination and then derive a policy from these expectations. Policy-search learners optimize the agent's policy directly by using a parameterized representation of the policy and then optimizing the...
In this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for intelligent energy cooperatives at different aggregation scales of energy consumption. Next to scale, we investigate the...
Smart energy systems integrate renewables and demand response. Most European electricity markets coordinate the resulting time-varying flexibility in demand and supply by organising day-ahead trade with Walrasian mechanisms, using simultaneous call auctions and sealed bids. These mechanisms give bidders no information on each other's values and flexibilities until after clearing. In this paper we...
In this paper we investigate the evolutionary dynamics of strategic behavior in the game of poker by means of data gathered from a large number of real world poker games. We perform this study from an evolutionary game theoretic perspective using two Replicator Dynamics models. First we consider the basic selection model on this data, secondly we use a model which includes both selection and mutation...
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