Accountability in Smart Microgrids Based on Conservative Power Theory

Smart microgrids offer a new challenging domain for power theories and metering techniques because they include a variety of intermittent power sources which positively impact on power flow and distribution losses but may cause voltage asymmetry and frequency variation. In smart microgrids, the voltage distortion and asymmetry in presence of poly-phase nonlinear loads can be also greater than in usual distribution lines fed by the utility, thus affecting measurement accuracy and possibly causing tripping of protections. In such a context, a reconsideration of power theories is required since they form the basis for supply and load characterization. A revision of revenue metering techniques is also suggested to ensure a correct penalization of the loads for their responsibility in generating reactive power, voltage asymmetry, and distortion. This paper shows that the conservative power theory provides a suitable background to cope with smart grids characterization and metering needs. Simulation and experimental results show the properties of the proposed approach.

Improving the grid operation and reliability cost of distribution systems with dispersed generation

In this work, a mathematical model to analyze the impact of the installation and operation of dispersed generation units in power distribution systems is proposed. The main focus is to determine the trade-off between the reliability and operational costs of distribution networks when the operation of isolated areas is allowed. In order to increase the system operator revenue, an optimal power flow makes use of the different energy prices offered by the dispersed generation connected to the grid. Simultaneously, the type and location of the protective devices initially installed on the protection system are reconfigured in order to minimize the interruption and expenditure of adjusting the protection system to conditions imposed by the operation of dispersed units. The interruption cost regards the unsupplied energy to customers in secure systems but affected by the normal tripping of protective devices. Therefore, the tripping of fuses, reclosers, and overcurrent relays aims to protect the system against both temporary and permanent fault types. Additionally, in order to reduce the average duration of the system interruption experienced by customers, the isolated operation of dispersed generation is allowed by installing directional overcurrent relays with synchronized reclose capabilities. A 135-bus real distribution system is used in order to show the advantages of using the mathematical model proposed. © 1969-2012 IEEE.

Smart Grid e Carros Elétricos - Influência da Carga de Carros Elétricos Sobre o Sistema Elétrico

The technologies are advancing at a pace so expressive that allow the increase of the power quality from generation until the distribution to end customers. This improvement has been made possible through the automation of the energy that follows to a better quality of the energy provided, a lower energy supply disruptions and a very short recovery time. The trend of today and the near future is the distributed energy generation. To keep the automated control of the chain, the presence of Smart Grids is needed and that will be the most efficient and economical way to manage the entire system. Within this theme, is going to be necessary analyze the electric cars that promise to promote a more sustainable transport because it doesn’t uses fossil fuels, and more healthy because it does not emit pollutants into the atmosphere. The popularization of this type of vehicle is estimated to happen in a few decades and the case study analyzing its influence on the demand of the electrical system is something that will be very important in the near future. This paper presents a study of the influence of the inclusion of charges refering to electric cars

Desenvolvimento de um smart meter: um estudo sobre eficiência energética através das redes inteligentes

Pós-graduação em Engenharia Elétrica - FEB

Volt-VAR multiobjective optimization to peak-load relief and energy efficiency in distribution networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Smart electricity grids: A very slow deployment in the EU. Egmont Paper No. 74, February 2015

Summary. The European electricity sector will have to deal with a huge challenge in the decades to come. On the one hand, electrical power is increasingly substituted for other forms of energy. It has been forecast that electricity demand will increase in the future (notably because of new needs in transport and heat sectors), although it is currently stagnant, mainly because of the economic crisis. Unless a major alternative energy source is discovered, electricity will become the central energy pillar in the long term. On the other hand, electricity production remains uncertain and will depend on numerous factors: the growth of renewable energy and decentralized energy, the renewal of old power generation capacities, increased external dependency, CO2 charges, etc. This increases the demand for electricity networks that are more reliable, more efficient, and more flexible. Europe’s current electricity networks are ageing, and, as already indicated by the International Energy Agency, many of them will need to be modernized or replaced in the decades to come. Finally, the growing impact of energy trading also needs to be taken into account. These considerations explain the need to modernize the electric grid through various ICT means. This modernization alone may allow the grid to become more flexible and interactive, to provide real time feedback, more adaptation to a fluctuating demand, and finally to reduce the global electricity costs. The paper begins with a description of the EU definition of the term ‘smart grid’ (§ 1) and of the body in charge of advising the Commission (§ 2). The EU legal framework applicable to smart grids is also detailed (§ 3). It is a rather complex domain, connected to various regulations. The paper then examines three critical factors in the development of smart grids (and smart meters as a precondition). Standardization is quite complex, but absolutely essential (§ 4). Innovation is not easily put into action (§ 5). Finally, as digital insecurity has worsened dramatically in recent years, the security of electricity networks, and especially their multiplied electronic components, will become increasingly important (§ 6). Lastly, the paper provides a concise overview of the progress of smart grids in the EU in recent years (§ 7). In a nutshell, the conclusion is that progress is quite slow, many obstacles remain, and, given the appearance of many new regulatory problems, it would be useful to organize a review of the present EU strategy.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

Mobi_System: A Personal Travel Assistance for Electrical Vehicles in Smart Cities

In this work it is proposed the design of a mobile system to assist car drivers in a smart city environment oriented to the upcoming reality of Electric Vehicles (EV). Taking into account the new reality of smart cites, EV introduction, Smart Grids (SG), Electrical Markets (EM), with deregulation of electricity production and use, drivers will need more information for decision and mobility purposes. A mobile application to recommend useful related information will help drivers to deal with this new reality, giving guidance towards traffic, batteries charging process, and city mobility infrastructures (e. g. public transportation information, parking places availability and car & bike sharing systems). Since this is an upcoming reality with possible process changes, development must be based on agile process approaches (Web services).

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

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.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.