Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.

Multi-agent negotiation for coalition formation and management in electricity markets

Negotiation is a fundamental tool for reaching understandings that allow each involved party to gain an advantage for themselves by the end of the process. In recent years, with the increasing of compe-titiveness in most sectors, negotiation procedures become present in practically all of them. One particular environment in which the competitiveness has been increasing exponentially is the electricity markets sector. This work is directed to the study of electricity markets’ partici-pating entities interaction, namely in what concerns the formation, management and operation of aggregating entities – Virtual Power Players (VPPs). VPPs are responsible for managing coalitions of market players with small market negotiating influence, which take strategic advantage in entering such aggregations, to increase their negotiating power. This chapter presents a negotiation methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using MASCEM, taking advantage of its ability to provide the means to model and simulate VPPs. VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.

Multilevel negotiation in smart grids for VPP management of distributed resources

A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.

Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

Energy resources management for more sustainable distribution systems: an intelligent approach

Energy Resources Management can play a very relevant role in future power systems in SmartGrid context, with high penetration of distributed generation and storage systems. This paper deals with the importance of resources management in incident situation. The system to consider a high penetration of distributed generation, demand response, storage units and network reconfiguration. A case study evidences the advantages of using a flexible SCADA to control the energy resources in incident situation.

Emergency energy resource management in SmartGrids

Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Motivations and management factors of volunteer work in nonprofit organisations: a literature review

The objective of this paper is to review and discuss the literature about volunteers’ motivations to donate their time to NPOs and the management factors that can influence volunteer work. Firstly, the paper illustrates and compares the different types of motivation followed by a presentation of a typology that organises the volunteers’ motivations into four types: (i) altruism, (ii) belonging, (iii) ego and social recognition and (iv) development and learning. Secondly we discuss the key management factors in volunteering: recruitment, training and rewarding. Finally, we present four gaps in the literature that justify the scope for further research: (i) omission of differences between motivations related to volunteers’ "Attraction" versus "Retention"; (ii) focus of the research on the USA, UK and Australia context; (iii) absence of comparative analyses that relate motivations by NPO types and (iv) comprehension of how management factors (recruitment, training and rewarding) influence volunteers’ satisfaction and retention.

Volunteers and management factors in nonprofit organisations: a brief literature review

The objective of this paper is to review and discuss the literature about the management factors that can influence volunteer work. First we present the different management factors. This discussion is followed by the identification of the key management factors in volunteering: recruitment, training and rewarding. Finally, we present two main gaps in the literature that justify the scope for further research: (i) how management factors (recruitment, training and rewarding) influence volunteers’ satisfaction and retention; and (ii) predominance of the investigations in the North American context, followed by English and Australian context.

Corporate brand identity management – proposal of a new framework

The term “corporate brand” has been widely used in literature since the eighties. According to Balmer (1998) this concept tends to be used as an alternative to the concept of corporate identity. The author argues that the use of branding principles to discuss corporate identity has tended to align the area more closely with marketing. However, the literature on brand management (Aaker, 1991; Kapferer, 1991 and de Chernatony and McDonald, 1992), gives little attention to the corporate brand” (p. 985). Based on the concepts of corporate brand, brand identity and B2B relationship, the authors are interested in eliminating this gap in literature by designing a framework of corporate brand identity management. The aim of this investigation is to investigate the impact of B2B relationships in corporate brand identity management. The methodology used is quantitative analysis of surveys and scale development. The originality of this paper is to investigate the influence of the relationship between brands in corporate brand identity. This investigation is very important to help the decisions of the corporate brand managers and academics. According to literature, namely on corporate brands (Balmer 2002b, Hatch and Schultz, 2001, 2003) and on brand identity (Kapferer, 1991, 2008, Aaker, 1996, de Chernatony, 1999) the authors developed a corporate brand identity management framework considering relationships between brands a context variable with definite impact on identity management as stated by Hakansson and Snehota (1989, 1995). These authors consider that organisations´ identity management is pursued under a relational perspective with impact on identity management. Most researchers on identity and corporate brand emphasise the importance of external influences (Kennedy, 1977; King, 1991; de Chernatony, 1999; Balmer and Gray, 2000; Balmer, 2002a). Those influences concern legislation, concurrence, political issues... and stakeholders’ perceptions and reputations (due to the holistic approach demanded by corporate brands). In this context the authors claim the importance of another influence: B2B relationships. This decision is inspired in sociological studies (Mannheim, 1950; and Tajfel and Turner, 1979) regarding individual identity. These authors claim that individuals form their personality by interacting in the social field. The authors argue that corporate brand identity also develops itself under a relational approach. The relationships selected to pursue this investigation are the ones that are developed by Portuguese universities and investigation centres that cooperate by developing investigation. Those centres are administrative and financially autonomous

Corporate brand identity management in a technological faculty – how brand relationships influence students and companies reputations

Identity is traditionally defined as an emission concept [1]. Yet, some research points out that there are external factors that can influence it [2]; [3]; [4]. This subject is even more relevant if one considers corporate brands. According to Aaker [5] the number, the power and the credibility of corporate associations are bigger in the case of corporate brands. Literature recognizes the influence of relationships between companies in identity management. Yet, given the increasingly important role of corporate brands, it is surprising that to date no attempt to evaluate that influence has been made in the management of corporate brand identity. Also Keller and Lehman [6] highlight relationships and costumer experience as two areas requiring more investigation. In line with this, the authors intend to develop an empirical research in order to evaluate the influence of relationships between brands in the identity of corporate brand from an internal perspective by interviewing internal stakeholders (brand managers and internal clients). This paper is organized by main contents: theoretical background, research methodology, data analysis and conclusions and finally cues to future investigation.