Pf Paulo Ribeiro

A Game Theory Strategy to Integrate Distributed Agent-Based Functions in Smart Grids

The increasing incorporation of renewable energy sources and the emergence of new forms and patterns of electricity consumption are contributing to the upsurge in the complexity of power grids. A bottom-up-agent-based approach is able to handle the new environment, such that the system reliability can be maintained and costs reduced. However, this approach leads to possible conflicting interests between maintaining secure grid operation and the market requirements. This paper proposes a strategy to solve the conflicting interests in order to achieve overall optimal performance in the electricity supply system. The method is based on a cooperative game theory to optimally allocate resources from all (local) actors, i.e., network operators, active producers, and consumers. Via this approach, agent-based functions, for facilitating both network services and energy markets, can be integrated and coordinated. Simulations are performed to verify the proposed concept on a medium voltage 30-bus test network. Results show the effectiveness of the approach in optimally harmonizing functions of power routing and matching.

Smart Power Router: A Flexible Agent-Based Converter Interface in Active Distribution Networks

Due to the large-scale implementation of distributed generation, the power delivery system is changing gradually from a “vertically” to a “horizontally” controlled and operated structure. This transition has prompted the emergence of the active distribution network (ADN) concept as an efficient and flexible distribution system to deal with various challenging issues. This paper addresses a multiagent system (MAS) as a suitable technology to manage autonomous control actions and perform the coordination in an ADN. In this agent-based ADN a smart power router is implemented, which can flexibly integrate network areas and optimally manage power flows. Operational and control functions of the power router has been investigated in a laboratory experiment. In this lab setup, a configuration of the power router is established in a combination of a three-inverter system and an agent. The experiments show that the ADN can operate in an efficient and flexible way with the support of the power router interface. The control function of the inverters and the operation of MAS are thoroughly verified.

Integrated energy optimization with smart home energy management systems

Optimization of energy use is a vital concept in providing solutions to many of the energy challenges in our world today. Large chemical, mechanical, pneumatic, hydraulic, and electrical systems require energy efficiency as one of the important aspects of operating systems. At the micro-scale, the built environment experiences progressive changes in energy consumption. There is steady increase in the annual energy consumption of households as a result of population growth, increase of economic activity and increased use of domestic appliances. The drive to reduce this growing trend has stimulated many mechanisms such as the use of energy labels on domestic appliances. Home appliance manufacturers research into developing energy-efficient products with the end-goal of making consumer devices more energy efficient. One important step towards energy efficiency and savings in the built environment is the introduction of Smart Home Energy Management Systems. (SHEMS). This paper analyses how the implementation of such solutions could contribute to energy savings and enhance efficiency for residential customers. The paper presents a general overview of energy efficiency measures focusing on residential loads. It further highlights, via modelling and simulation the potentials of Smart Home Energy Management Solutions for future domestic applications.

Home energy management systems: Evolution, trends and frameworks

The incentive and motivation to manage energy at the household level is influenced by commercial and technical reasons. Commercially, it offers the otherwise passive residential customer to be active in the energy market. The technical aspect enables them to provide support to the network operator through demand response, peak shaving and load shifting measures as well as provide ancillary services. There are pilot projects demonstrating advantages of functional home energy management systems. Also important are the socio-economic impacts of such systems, an aspect though often overlooked. This paper reviews the concept of energy management systems for residential customers and looks into the background of smart home energy management system technologies. It highlights the major components, and comparatively analyzes various technological approaches. It also discusses some of the concerns and challenges such as cost, implementation and privacy issues of smart technologies and makes suggests a framework for future systems.

Multi-agent system architecture for smart home energy management and optimization

The smart grid concept is not limited to the public network but it is also envisioned in the residential setting. The integration of automation technologies into home is being driven by comfort and economic benefits to homeowners. The shift towards dynamic electricity pricing and demand response application for residential customers implies that the traditional building control strategies are no longer sufficient and flexible enough. A smarter and more efficient, flexible and intelligent energy management system is therefore required. Agent-based systems which implement distributed intelligence are capable of solving such complex and dynamic decision processes. This paper proposes a multi-agent based architecture for optimal energy management in smart homes. Four optimization strategies - comfort, cost, green (energy-efficient) and smart (demand side management) - are proposed and explained. The strategies are expected to provide savings (energy and cots), flexibility and control to homeowners in their energy use, and to support utility companies in the management of the electricity network.

A Predictive Control Scheme for Real-Time Demand Response Applications

In this work, the focus is placed on the proof of concept of a novel control scheme for demand response. The control architecture considers a uniform representation of non-homogeneous distributed energy resources and allows the participation of virtually all system users in electricity markets. The proposed scheme captures the operational planning, the real-time operations, the verification of the energy and service provision, and the financial settlement. The research involves the experimental verification of the proposed control and communication architecture between the aggregator and a system user in a laboratory environment. Emphasis is given on the real-time operations, whereas the case study is about the domestic freezer appliance. The convergence of the demand response system under load frequency control is investigated through simulation studies and the time response is compared to that of conventional balance suppliers in The Netherlands.

Planning and Designing Smart Grids: Philosophical Considerations

The electric power grid is a crucial part of societal infrastructure and needs constant attention to maintain its performance and reliability. European grid project investments are currently valued at over 5 billion Euros and are estimated to reach 56 billion by 2020 [2]. Successful smart grid deployment will require a holistic analysis and design process if it is to function properly and in an environmentally sustainable way. The entire system must be treated as integrated, not as isolated parts [3]. System integration and full customer engagement are crucial elements of this development. An evaluation of European smart grid projects showed that it was very difficult to grasp technological and non-technological key characteristics of this complex system [4].

History of demand side management and classification of demand response control schemes

The scope of this paper is to provide a review on the topic of demand side management. A historical overview provides a critical insight to applied cases, while the discovery of new evidence calls for reconsideration of the design of demand response control schemes. The developments at the demand side are analyzed, and philosophical considerations are made with respect to envisioned energy management systems. Finally, the authors classify demand response control schemes based on the formulation of the rate structures and the employed technology. This classification follows a historical order, and addresses both applied cases and research developments.

Social interaction interface for performance analysis of smart grids

Socio-economical and technological developments have prompted electric power systems to move forward to an era of Smart Grids. This mainstream concept has a strong interdisciplinary nature by using state-of-the-art technologies in the fields of Information and Communication Technology (ICT), power electronics, and control systems. Modeling and simulation are fundamental steps to accomplish possible applications of this complex and integrated scheme. However, most of the existing simulation platforms, either commercial or free and open source packages, hardly adapt to this requirements of Smart Grids. This paper presents an on-going framework which integrates open source software, OpenDSS, to provide different web services for end-users. This application aims to create a robust computation platform to support customers in making decisions. Different network functions can be verified in this assessment context tool. Working as a social network, this program will empower end-users with an interaction interface to make them fully aware of Smart Grid applications.

Optimization of State-Estimator-Based Operation Framework Including Measurement Placement for Medium Voltage Distribution Grid

To provide a guideline for grid operators to manage medium voltage distribution grids, this paper presents a probabilistic approach for measurement placement optimization and a state-estimator-based operation framework. The Monte Carlo method is used to optimize the measurement placement with minimum measured points, which support the observability of state estimator and satisfy the requirements for operation activities. The proposed framework covers several important factors from practical situations, including cost allocation of measurement systems, unavailability of measurement data, and small voltage deviation across medium voltage (MV) grids. Finally, a case study on a typical European distribution grid demonstrates the feasibility of the framework.