Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

Octopus Lipid and Vitamin E Composition: Interspecies, Interorigin, and Nutritional Variability

Octopus vulgaris, Octopus maya, and Eledone cirrhosa from distinct marine environments [Northeast Atlantic (NEA), Northwest Atlantic (NWA), Eastern Central Atlantic, Western Central Atlantic (WCA), Pacific Ocean, and Mediterranean Sea] were characterized regarding their lipid and vitamin E composition. These species are those commercially more relevant worldwide. Significant interspecies and interorigin differences were observed. Unsaturated fatty acids account for more than 65% of total fatty acids, mostly ω-3 PUFA due to docosahexaenoic (18.4−29.3%) and eicosapentanoic acid (11.4− 23.9%) contributions. The highest ω-3 PUFA amounts and ω-3/ω-6 ratios were quantified in the heaviest specimens, O. vulgaris from NWA, with high market price, and simultaneously in the lowest graded samples, E. cirrhosa from NEA, of reduced dimensions. Although having the highest cholesterol contents, E. cirrhosa from NEA and O. maya from WCA have also higher protective fatty acid indexes. Chemometric discrimination allowed clustering the selected species and several origins based on lipid and vitamin E profiles.

Defining Electricity Tariffs Using the Knowledge About the Consumers Profiles in ELECON Project

The increasing importance of the integration of distributed generation and demand response in the power systems operation and planning, namely at lower voltage levels of distribution networks and in the competitive environment of electricity markets, leads us to the concept of smart grids. In both traditional and smart grid operation, non-technical losses are a great economic concern, which can be addressed. In this context, the ELECON project addresses the use of demand response contributions to the identification of non-technical losses. The present paper proposes a methodology to be used by Virtual Power Players (VPPs), which are entities able to aggregate distributed small-size resources, aiming to define the best electricity tariffs for several, clusters of consumers. A case study based on real consumption data demonstrates the application of the proposed methodology.

Intelligent Remuneration and Tariffs for Virtual Power Players

Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Automatic Electricity Markets Data Extraction for Realistic Multi-agent Simulations

Electricity markets worldwide suffered profound transformations. The privatization of previously nationally owned systems; the deregulation of privately owned systems that were regulated; and the strong interconnection of national systems, are some examples of such transformations [1, 2]. In general, competitive environments, as is the case of electricity markets, require good decision-support tools to assist players in their decisions. Relevant research is being undertaken in this field, namely concerning player modeling and simulation, strategic bidding and decision-support.

Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Uncertainty on a Bertrand duopoly with product differentiation

The conclusions of the Bertrand model of competition are substantially altered by the presence of either differentiated goods or asymmetric information about rival’s production costs. In this paper, we consider a Bertrand competition, with differentiated goods. Furthermore, we suppose that each firm has two different technologies, and uses one of them according to a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We show that this game has exactly one Bayesian Nash equilibrium. We do ex-ante and ex-post analyses of firms’ profits and market prices. We prove that the expected profit of each firm increases with the variance of its production costs. We also show that the expected price of each good increases with both expected production costs, being the effect of the expected production costs of the rival dominated by the effect of the own expected production costs.

Cournot model with investments to change the market size

We present a new deterministic dynamical model on the market size of Cournot competitions, based on Nash equilibria of R&D investment strategies to increase the size of the market of the firms at every period of the game. We compute the unique Nash equilibrium for the second subgame and the profit functions for both firms. Adding uncertainty to the R&D investment strategies, we get a new stochastic dynamical model and we analyse the importance of the uncertainty to reverse the initial advantage of one firm with respect to the other.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Significance of Biogenic Amines in Cold-Smoked Fish and Their Relation to Microbiological Characteristics of Products Available in Portuguese Retail Markets

Studies on microbial characterization of cold-smoked salmon and salmon trout during cold storage were performed on samples available in the Portuguese market. Samples were also classified microbiologically according to guidelines for ready-to-eat (RTE) products. Further investigations on sample variability and microbial abilities to produce tyramine and histamine were also performed. The coefficient of variation for viable counts of different groups of microorganisms of samples collected at retail market point was high in the first 2 wk of storage, mainly in the Enterobacteriaceae group and aerobic plate count (APC), suggesting that microbiological characteristics of samples were different in numbers, even within the same batch from the same producer. This variation seemed to be decreased when storage and temperature were controlled under lab conditions. The numbers of Enterobacteriaceae were influenced by storage temperature, as indicated by low microbial numbers in samples from controlled refrigeration. Lactic acid bacteria (LAB) and Enterobacteriaceae were predominant in commercial products, a significant percentage of which were tyramine and less histamine producers. These results might be influenced by (1) the technological processes in the early stages of production, (2) contamination during the smoking process, and (3) conditions and temperature fluctuations during cold storage at retail market point of sale.

Caracterización y determinación del proceso para la producción de cal comercial a partir de la piedra caliza

La cal es un material producido a partir de la calcinación de la roca caliza y tiene diversas utilidades en el mundo de la industria como la siderúrgica, papelera, alimentaria, en la construcción, entre otras. Es fundamental conocer todas las características de la caliza para poder determinar su grado de calcinación. Con el presente trabajo se pretende estudiar las propriedades de la caliza para su posterior calcinación y el dimensionamento de una planta de producción de cal desde que el mineral llega de la explotación hasta que sale al mercado.Para determinar los equipos se calularon sus dimensiones para una producción de 600 t/h de cal, sabiendo que la planta principal de machaquero solo trabajará 5 días de la semana en jornadas de 8 horas, mientras que a partir del horno de calcinación estará en funcionamento los 7 dias de la semana, 24 horas al día. A partir de esas consideraciones se obtienen las dimensiones de todos los equipos y se realiza un estudio para la elección de un horno, o un horno de eje vertical y un horno rotativo, así como el combustible empleado, ya que es una parte fundamental para determinar los costes para la producción de cal.Tmbién fue objeto de este trabajo, el estudio ambiental de la instalación de la planta, en función de la mezcla de combustible empleada y del impacto en el entorno de la lisma, así como un estudio de viabilidad de la planta, estimando unos costes de la misma y un precio de mercado "ex Works".