Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Anticipatory postural adjustments during sitting reach movement in post-stroke subjects

The study assessed the effect of velocity of arm movement on the generation of APAs in the contralateral and ipsilateral muscles of individuals with stroke in the sitting position. In the sitting position, 10 healthy and 8 post-stroke subjects reached for an object placed at the scapular plane and mid-sternum height at self-selected and fast velocities. Electromyography was recorded from the anterior deltoid (AD), upper (UT) and lower trapezius (LT), and latissimus dorsi (LD). Kinematic analysis was used to assess peak velocity and trunk displacement. Post-stroke subjects presented a delay of APAs on both sides of the body compared to healthy subjects. Differences were found between the timing of APAs on the ipsilateral and contralateral LD and LT in both movement speeds and in the ipsilateral UT during movement of the non-affected arm at a self-selected velocity. A delay in the contralateral LD in the reaching movement with the non-affected arm at fast velocity was also observed. Trunk displacement was greater in post-stroke subjects. In the sitting position, APAs were delayed in both fast and self-selected movements on both sides in post-stroke subjects, which also presented a higher trunk displacement.

An implicit GTS allocation mechanism in IEEE 802.15.4 for time-sensitive wireless sensor networks: theory and practice

Timeliness guarantee is an important feature of the recently standardized IEEE 802.15.4 protocol, turning it quite appealing for Wireless Sensor Network (WSN) applications under timing constraints. When operating in beacon-enabled mode, this protocol allows nodes with real-time requirements to allocate Guaranteed Time Slots (GTS) in the contention-free period. The protocol natively supports explicit GTS allocation, i.e. a node allocates a number of time slots in each superframe for exclusive use. The limitation of this explicit GTS allocation is that GTS resources may quickly disappear, since a maximum of seven GTSs can be allocated in each superframe, preventing other nodes to benefit from guaranteed service. Moreover, the GTS may be underutilized, resulting in wasted bandwidth. To overcome these limitations, this paper proposes i-GAME, an implicit GTS Allocation Mechanism in beacon-enabled IEEE 802.15.4 networks. The allocation is based on implicit GTS allocation requests, taking into account the traffic specifications and the delay requirements of the flows. The i-GAME approach enables the use of one GTS by multiple nodes, still guaranteeing that all their (delay, bandwidth) requirements are satisfied. For that purpose, we propose an admission control algorithm that enables to decide whether to accept a new GTS allocation request or not, based not only on the remaining time slots, but also on the traffic specifications of the flows, their delay requirements and the available bandwidth resources. We show that our approach improves the bandwidth utilization as compared to the native explicit allocation mechanism defined in the IEEE 802.15.4 standard. We also present some practical considerations for the implementation of i-GAME, ensuring backward compatibility with the IEEE 801.5.4 standard with only minor add-ons. Finally, an experimental evaluation on a real system that validates our theoretical analysis and demonstrates the implementation of i-GAME is also presented

Object transportation by multiple mobile robots controlled by attractor dynamics: theory and implementation

Dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for teams of mobile robots, that must transport a large object and simultaneously avoid collisions with (either static or dynamic) obstacles. Here we demonstrate in simulations and implementations in real robots that it is possible to simplify the architectures presented in previous work and to extend the approach to teams of n robots. The robots have no prior knowledge of the environment. The motion of each robot is controlled by a time series of asymptotical stable states. The attractor dynamics permits the integration of information from various sources in a graded manner. As a result, the robots show a strikingly smooth an stable team behaviour.

Bertrand and Cournot oligopolies when rivals' costs are unknown

We study Bertrand and Cournot oligopoly models with incomplete information about rivals’ costs, where the uncertainty is given by a uniform distribution. We compute the Bayesian- Nash equilibrium of both games, the ex-ante expected profits and the ex-post profits of each firm. We see that, in the price competition, even though only one firm produces in equilibrium, all firms have a positive ex-ante expected profit.

Uncertainty in a mixed duopoly with quadratic costs

In this paper, we consider a mixed market with uncertain demand, involving one private firm and one public firm with quadratic costs. The model is a two-stage game in which players choose to make their output decisions either in stage 1 or stage 2. We assume that the demand is unknown until the end of the first stage. We compute the output levels at equilibrium in each possible role. We also determine ex-ante and ex-post firms’ payoff functions.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.