Carlos Ramos

Multi-agent based electricity market simulator with VPP: Conceptual and implementation issues

This paper presents a new architecture for MASCEM, a multi-agent electricity market simulator. The main focus is the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. VPPs can reinforce the importance of distributed generation technologies, mainly based on renewable energy sources, making them valuable in electricity markets. The new features are implemented in Prolog which is integrated in the JAVA program by using the LPA Win-Prolog Intelligence Server (IS) that provides a DLL interface between Win-Prolog and other applications.

Smart offices and intelligent decision rooms

Nowadays computing technology research is focused on the development of Smart Environments. Following that line of thought several Smart Rooms projects were developed and their appliances are very diversified. The appliances include projects in the context of workplace or everyday living, entertainment, play and education. These appliances envisage to acquire and apply knowledge about the environment state in order to reason about it so as to define a desired state for its inhabitants and perform adaptation adaptation to these desires and therefore improving their involvement and satisfaction with that environment.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

The role of demand response in future power systems

Power systems are planed and operated according to the optimization of the available resources. Traditionally these tasks were mostly undertaken in a centralized way which is no longer adequate in a competitive environment. Demand response can play a very relevant role in this context but adequate tools to negotiate this kind of resources are required. This paper presents an approach to deal with these issues, by using a multi-agent simulator able to model demand side players and simulate their strategic behavior. The paper includes an illustrative case study that considers an incident situation. The distribution company is able to reduce load curtailment due to load flexibility contracts previously established with demand side players.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

Using remote experimentation in a large undergraduate course: Initial findings

The use of remote labs in undergraduate courses has been reported in literature several times since the mid 90s. Nevertheless, very few articles present results about the correspondent learning gains obtained by students, and in what conditions those systems can be more efficient, thus suggesting a lack of data concerning their pedagogical effectiveness. This paper addresses such a gap by presenting some initial findings concerning the use of a remote lab (VISIR), in a large undergraduate course on Physics, with over 550 students enrolled.

Ancillary services market clearing simulation: A comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Computer Applications for Software Engineering, Disaster Recovery, and Business Continuity

This book comprises the refereed proceedings of the International Conferences, ASEA and DRBC 2012, held in conjunction with GST 2012 on Jeju Island, Korea, in November/December 2012. The papers presented were carefully reviewed and selected from numerous submissions and focus on the various aspects of advanced software engineering and its applications, and disaster recovery and business continuity.

Cooperation Mechanism for Team-Work based Multi-Agent System in Dynamic Scheduling through Meta-Heuristics

This paper describes a multi-agent scheduling system that assumes the existence of several machines agents (which are decision-making entities) distributed inside the manufacturing system that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some multi-agent systems (MAS) organizational aspects are considered. An original cooperation mechanism for a team-work based architecture is proposed to address dynamic scheduling using meta-heuristics.

Ubiquitous Sensor Networks and Its Application

Ubiquitous sensor networks and its application are emerging rapidly as an exciting new paradigm to provide reliable and comfortable life services. The ever-growing ubiquitous sensor networks and its application will provide an intelligent and ubiquitous communication and network technology for tomorrow. That is, the UCMA have emerged rapidly as an exciting new paradigm that includes ubiquitous, grid, and peer-to-peer computing to provide computing and communication services at anytime and anywhere. In order to realize the advantages of such services, it is important that intelligent systems be suitable for UCMA.