NCRF 21 – provisões, passivos contingentes e activos contingentes: suas implicações fiscais e de auditoria

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto (ISCAP) para a obtenção do Grau de Mestre em Auditoria Docente orientador: Mestre Domingos da Silva Duarte

Estágio profissional: Câmara Municipal da Trofa

Relatório de Estágio apresentado ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Auditoria Orientador: Rodrigo Mário Oliveira Carvalho, Dr. Coorientador: Vicente António Fernandes Seixas, Dr.

Stochastic Short-term Incentive-based Demand Response Scheduling of Load-serving Entities

In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

Eficiência Energética no Hospital Pedro Hispano

Os crescentes custos ligados ao consumo elétrico, não apenas de cariz financeiro mas também ambiental, despertam cada vez mais para a importância da definição de estratégias de melhor utilização de recursos e eficiência energética. Esta importância tem sido reforçada pela definição de decretos-lei que vêm colocar metas e limites relativamente às despesas energéticas. Estes diplomas são também acompanhados por programas de incentivo para um setor ligado à eficiência energética. Em Portugal as medidas ligadas ao setor tem vindo a ser redirecionadas para o consumo final de energia, com a definição de metas para as instalações de maior consumo. As instalações hospitalares são grandes centros de consumo energético devido não só ao elevado número de utentes que recebem mas também pelos diversos tipos de equipamentos elétricos usados para a prestação dos serviços médicos. Como consequência disso, os investimentos e os custos operacionais são elevados, o que reforça a necessidade de gerir os gastos e consumos energéticos com a procura constante de melhoria na recolha de informação sobre todo o sistema e na adequação de intervenções com vista a uma maior eficiência energética. O Hospital Pedro Hispano vem desde algum tempo a investir no sentido de conhecer mais e melhor toda a instalação bem como os consumos energéticos a ela associados. Algumas medidas foram tomadas nesse sentido nomeadamente a instalação de analisadores de energia, de modo a obter um retrato mais fiel e fidedigno dos principais vetores de consumo. Neste momento a gestão técnica do hospital tem em análise uma grande parte da instalação recolhendo dados do consumo elétrico real do hospital. Nesta dissertação procurou-se fazer uma análise e enquadramento dos programas e metas ligados ao setor energético com ênfase nos diplomas que visão e abrangem as instalações hospitalares. Dos vários programas de incentivo à adoção de políticas de maior eficiência energética é dado especial destaque ao programa ECO.AP que visa a celebração de contratos para implementação de medidas de poupança energética ao setor público. Em colaboração com o HPH, iniciaram-se os trabalhos pelo estudo e identificação das principais fases e ferramentas utilizadas na gestão energética do edifício tendo como objetivo a reavaliação dos vetores energéticos já identificados no HPH e a criação e contabilização de novos grupos de consumo. Através de várias medições do consumo elétrico, num total superior a 650 horas de funcionamento, foi possível a criação do mapa de desagregação de consumos para o ano de 2013. A desagregação realizada conta com 3 novos vetores energéticos e com a reavaliação do peso relativo de mais 5 grupos de consumo. Das medições efetuadas destaca-se a reavaliação do consumo da central de bombagem onde a parcela considerada até à data estava 3 vezes acima do valor real medido. Com base na desagregação feita foram apontadas e estudadas medidas de implementação com o objetivo de reduzir os consumos energético em todo o hospital, destacando-se a solução apresentada para a central de bombagem. Esta medida traria um grande impacto em toda a fatura energética, não só pela sua viabilidade, mas também porque atuaria num grande centro de consumo onde até ao momento nenhuma ação do género foi implementada.

Electricity markets modeling considering complex contracts and aggregators

All over the world, the liberalization of electricity markets, which follows different paradigms, has created new challenges for those involved in this sector. In order to respond to these challenges, electric power systems suffered a significant restructuring in its mode of operation and planning. This restructuring resulted in a considerable increase of the electric sector competitiveness. Particularly, the Ancillary Services (AS) market has been target of constant renovations in its operation mode as it is a targeted market for the trading of services, which have as main objective to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. In this way, with the increasing penetration of distributed energy resources including distributed generation, demand response, storage units and electric vehicles, it is essential to develop new smarter and hierarchical methods of operation of electric power systems. As these resources are mostly connected to the distribution network, it is important to consider the introduction of this kind of resources in AS delivery in order to achieve greater reliability and cost efficiency of electrical power systems operation. The main contribution of this work is the design and development of mechanisms and methodologies of AS market and for energy and AS joint market, considering different management entities of transmission and distribution networks. Several models developed in this work consider the most common AS in the liberalized market environment: Regulation Down; Regulation Up; Spinning Reserve and Non-Spinning Reserve. The presented models consider different rules and ways of operation, such as the division of market by network areas, which allows the congestion management of interconnections between areas; or the ancillary service cascading process, which allows the replacement of AS of superior quality by lower quality of AS, ensuring a better economic performance of the market. A major contribution of this work is the development an innovative methodology of market clearing process to be used in the energy and AS joint market, able to ensure viable and feasible solutions in markets, where there are technical constraints in the transmission network involving its division into areas or regions. The proposed method is based on the determination of Bialek topological factors and considers the contribution of the dispatch for all services of increase of generation (energy, Regulation Up, Spinning and Non-Spinning reserves) in network congestion. The use of Bialek factors in each iteration of the proposed methodology allows limiting the bids in the market while ensuring that the solution is feasible in any context of system operation. Another important contribution of this work is the model of the contribution of distributed energy resources in the ancillary services. In this way, a Virtual Power Player (VPP) is considered in order to aggregate, manage and interact with distributed energy resources. The VPP manages all the agents aggregated, being able to supply AS to the system operator, with the main purpose of participation in electricity market. In order to ensure their participation in the AS, the VPP should have a set of contracts with the agents that include a set of diversified and adapted rules to each kind of distributed resource. All methodologies developed and implemented in this work have been integrated into the MASCEM simulator, which is a simulator based on a multi-agent system that allows to study complex operation of electricity markets. In this way, the developed methodologies allow the simulator to cover more operation contexts of the present and future of the electricity market. In this way, this dissertation offers a huge contribution to the AS market simulation, based on models and mechanisms currently used in several real markets, as well as the introduction of innovative methodologies of market clearing process on the energy and AS joint market. This dissertation presents five case studies; each one consists of multiple scenarios. The first case study illustrates the application of AS market simulation considering several bids of market players. The energy and ancillary services joint market simulation is exposed in the second case study. In the third case study it is developed a comparison between the simulation of the joint market methodology, in which the player bids to the ancillary services is considered by network areas and a reference methodology. The fourth case study presents the simulation of joint market methodology based on Bialek topological distribution factors applied to transmission network with 7 buses managed by a TSO. The last case study presents a joint market model simulation which considers the aggregation of small players to a VPP, as well as complex contracts related to these entities. The case study comprises a distribution network with 33 buses managed by VPP, which comprises several kinds of distributed resources, such as photovoltaic, CHP, fuel cells, wind turbines, biomass, small hydro, municipal solid waste, demand response, and storage units.

Formal Contracts for Runtime Verification Support in the Ada Programming Language

Poster presented in The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 26, Mar, 2015. Porto, Portugal.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

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.