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.

Um Projecto de investimento concorrente a um incentivo financeiro do IEFP

Prova Para Atribuição do Título de Especialista em Contabilidade – Código n.º 344

Complex dynamics of financial indices

This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.

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.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

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.

Do economic and financial firm's situation affect the quality if financial reports?

We investigate whether firms’ economic and financial situation influence the Quality of their Financial Reports (FRQ). FRQ is fundamental for investors and it affects the international capital movements [Bradshaw et al. (2004)] and Gelos and Wei (2005)]. Following Schipper and Vicent (2003) we use two issues to access earnings quality: abnormal accruals and earnings persistence. For seventeen European countries, we find evidence that the economic performance affects FRQ. Big firms and those with high current earnings exhibit better financial information. These results are robust since they don’t depend on FRQ proxy and we have the same evidence when we estimate regression with economical and financial factors separately or together. About financial situation, it seems not to affect FRQ. However, in high leveraged firms, the capital structure becomes determinant.

The effect of financial reports’ auality on Ffrm’s rerformance

We analyse whether the quality of firms’ Financial Reports (FRQ) produces any effect on their performance. Bradshaw et al. (2004) and Gelos and Wei (2005) call attention to the fact that the international capital movements is affected by FRQ. Following Schipper and Vicent (2003) we use the abnormal accruals to access earnings quality. For seventeen European countries, we found evidence that FRQ produces a positive impact on firm’s performance. This finding indicates that mangers are not opportunists and tends to make decisions to defend the firm’s best interests. This result is robust since it does not depend on the accounting firms’ performance proxy (ROA/ROE). In addition, it is also consistent when we use data in time series and in cross-sectional and when we estimate regression with lagged or the current year information about abnormal accruals.

Auction of financial transmission rights in electricity market environment

An auction model is used to increase the individual profits for market players with products they do not use. A Financial Transmission Rights Auction has the goal of trade transmission rights between Bidders and helps them raise their own profits. The ISO plays a major rule on keep the system in technical limits without interfere on the auctions offers. In some auction models the ISO decide want bids are implemented on the network, always with the objective maximize the individual profits for all bidders in the auction. This paper proposes a methodology for a Financial Transmission Rights Auction and an informatics application. The application receives offers from the purchase and sale side and considers bilateral contracts as Base Case. This goal is maximize the individual profits within the system in their technical limits. The paper includes a case study for the 30 bus IEEE test case.

Numerical experiments with a modified regularization scheme for mathematical programs with complementarity constraints

On this paper we present a modified regularization scheme for Mathematical Programs with Complementarity Constraints. In the regularized formulations the complementarity condition is replaced by a constraint involving a positive parameter that can be decreased to zero. In our approach both the complementarity condition and the nonnegativity constraints are relaxed. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.

Responsabilidade ambiental no perímetro industrial da Monteiro, Ribas – Indústrias, S.A.

A presente dissertação tem como intuito aplicar o regime de Responsabilidade Ambiental no perímetro industrial da Monteiro, Ribas – Indústrias, S.A.. Para tal, averiguou-se que na ordem jurídica nacional, o regime de Responsabilidade Ambiental (RA) encontra-se consagrada na legislação nacional pelo Decreto-Lei nº 147/2008 de 29 de Julho (Diploma RA),e respetivas alterações, aplicando-se a danos ambientais ou ameaças iminentes de danos ambientais causados aos recursos naturais nomeadamente “espécies e habitats naturais protegidos”, “água” e “solo”. Também se verificou que este regime introduz obrigações específicas para os operadores abrangidos, designadamente é da responsabilidade do operador aplicar as medidas de prevenção e reparação dos danos, devendo ser reportados os acontecimentos à autoridade competente, Agência Portuguesa do Ambiente. Para cumprimento do requisito da garantia financeira e sendo a Monteiro, Ribas – Indústrias, S.A. enumerada no Anexo III do Decreto-Lei nº 147/2008 de 29 de Julho, optou-se pela constituição de um fundo próprio no valor de 50.000,00€. Com recurso à metodologia proposta pela Norma Espanhola UNE 150008:2008 - Análise e avaliação do Risco Ambiental, procedeu-se à formulação de vários cenários e quantificação de riscos para a Monteiro, Ribas – Indústrias, S.A. tendo-se apurado que os riscos estavam avaliados como baixo ou moderado. Por fim, conclui-se que em Portugal, embora exista um Decreto-Lei sobre Responsabilidade Ambiental, este tema ainda não está suficientemente desenvolvido pois não permite proceder a análise e avaliação do risco ambiental, tendo sido tomado assim como referência a metodologia aplicada na Norma Espanhola UNE 150008:2008.

Sustainability reporting and financial reporting: the relevance of an integrated reporting approach

In the business world, there are issues such as globalisation, environmental awareness, and the rising expectations of public opinion which have a specific role in what is required from companies as providers of information to the market. This chapter refers to the current state of corporate reporting (financial reporting and sustainability reporting) and demonstrates the need for evolution to a more integrated method of reporting which meets the stakeholders’ needs. This research offers a reflection on how this development can be achieved, which notes the ongoing efforts by international organisations in implementing the diffusion and adoption, as well as looking at the characteristics which are needed for this type of reporting. It also makes the link between an actual case of a company that is one of the world references in sustainable development and integrated reporting. Whether or not the integrated reporting is the natural evolution of the history of financial and sustainability reporting, it still cannot yet claim to be infallible. However, it may definitely be concluded that a new approach is necessary to meet the needs which are continuously developing for a network of stakeholders.

The cross crypto scheme cipher integration for securing SCADA component communication

Critical Infrastructures became more vulnerable to attacks from adversaries as SCADA systems become connected to the Internet. The open standards for SCADA Communications make it very easy for attackers to gain in-depth knowledge about the working and operations of SCADA networks. A number of Intenrnet SCADA security issues were raised that have compromised the authenticity, confidentiality, integrity and non-repudiation of information transfer between SCADA Components. This paper presents an integration of the Cross Crypto Scheme Cipher to secure communications for SCADA components. The proposed scheme integrates both the best features of symmetric and asymmetric encryptiontechniques. It also utilizes the MD5 hashing algorithm to ensure the integrity of information being transmitted.

LNT: a logical neighbor tree secure group communication scheme for wireless sensor networks

Secure group communication is a paradigm that primarily designates one-to-many communication security. The proposed works relevant to secure group communication have predominantly considered the whole network as being a single group managed by a central powerful node capable of supporting heavy communication, computation and storage cost. However, a typical Wireless Sensor Network (WSN) may contain several groups, and each one is maintained by a sensor node (the group controller) with constrained resources. Moreover, the previously proposed schemes require a multicast routing support to deliver the rekeying messages. Nevertheless, multicast routing can incur heavy storage and communication overheads in the case of a wireless sensor network. Due to these two major limitations, we have reckoned it necessary to propose a new secure group communication with a lightweight rekeying process. Our proposal overcomes the two limitations mentioned above, and can be applied to a homogeneous WSN with resource-constrained nodes with no need for a multicast routing support. Actually, the analysis and simulation results have clearly demonstrated that our scheme outperforms the previous well-known solutions.

Power law analysis of financial index dynamics

Power law PL and fractional calculus are two faces of phenomena with long memory behavior. This paper applies PL description to analyze different periods of the business cycle. With such purpose the evolution of ten important stock market indices DAX, Dow Jones, NASDAQ, Nikkei, NYSE, S&P500, SSEC, HSI, TWII, and BSE over time is studied. An evolutionary algorithm is used for the fitting of the PL parameters. It is observed that the PL curve fitting constitutes a good tool for revealing the signal main characteristics leading to the emergence of the global financial dynamic evolution.