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An implementation of the planning phase of Triana using the flexible power application infrastructure

Dagioglou, S. (2014) An implementation of the planning phase of Triana using the flexible power application infrastructure.

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Abstract:Over the last decades, the impacts induced from human activities on the planet are a multiple of the impacts the human species induced since its existence. The technological advancements of the �rst and second Industrial Revolution, led to a rapid growth of world population and life expectancy and to a subsequent growth of world energy consumption. Human technology is still improving very fast and predictions show that world population and energy consumption will further increase over the coming decades. Although all these technological advancements improved the quality of life for a large part of the world population, they also had tremendous impacts on the environment that threaten the ability of future generations to meet their own needs. The greenhouse e�ect, deforestation, drought and potable water shortage, biodiversity loss, are only some of the problems that the future generation will inherit as a result of the human activity of the last centuries. The energy used to produce the electricity consumed nowadays, is approximately one third of the energy consumed world-wide. But only less of the half of the energy used to produce electricity is �nally converted to electricity, as a result of the losses that occur during the production of electricity [34]. After electricity is produced 5-10 % of this energy is lost during the transmission and distribution of electricity to the end-users [2]. The largest part of the electricity consumed today, is still produced by large power plants using fossil fuels like coal and oil and is delivered to the consumers using the transmission and distribution grids that result in the losses mentioned above. The e�ciency of these power plants is also relatively low unless used for the parallel production of heat and electricity (Combined Heat and Power-CHP). The aforementioned evolutions lead governments and other administrative institutions to the establishment of measures that protect the environment and improve the overall energy production chain. An example is the \20-20-20" target of the European Union that aim to 3 objectives by 2020: reducing the EU greenhouse emissions by 20% compared to 1990, produce 20% of the energy consumed using renewable sources and improve energy e�ciency by 20% [28]. As far as electricity is concerned, the evolution of the above grid to a Smart Grid is considered a necessity in order to achieve goals like the ones mentioned. Although it is risky to give an explicit de�nition of the Smart Grid, we could generally argue that the Smart Grids are systems which use modern technologies to create more e�cient energy systems compared to the present ones. A Smart Grid usually combines decentralized energy production (often from renewable energy sources), smart metering, information technology, energy storage devices, load and generation monitoring and control and other modern technologies to produce and distribute electrical and thermal energy in the most e�cient way possible [12]. Some of the challenges the electric utilities face today are meeting the rising electricity demand without a parallel increase in greenhouse emissions, improving the e�ciency with which energy is produced, transmitted and distributed and increasing the grid reliability so that an uninterrupted energy supply can be made possible to a larger extent. Regarding the latter one, the electricity supply is frequently threatened during the hours of peak electricity consumption. Utilities must always be prepared to meet the maximum electricity consumption expected. An interrupted or disturbed (regarding the voltage and frequency levels) electricity supply has major negative e�ects on industries whose operation depends on a stable electricity supply but also to commercial consumers as electricity is necessary to meet basic needs nowadays. Furthermore, meeting the large peak demands have a negative �nancial impact to electricity producers as they can use cheaper energy sources to cover the base and intermediate demand and have to use more expensive sources to cover the peak demand. One method to reduce the peak electricity demand is to shift demand from peak hours to hours with lower demand. By this the need for expensive peak production units is decreased as well as the cost of the electricity production. Till now the production was driven by the demand of consumers. Demand Side Management (DSM) technology is one the Smart Grid aspects and aims to shift the energy consumption from hours of high consumption to hours of lower consumption. By doing so, the electricity production can in a certain extent reduce its dependence on the electricity demand. That would allow the energy producers to use cheap sources to cover a larger percentage of the electricity consumed and increase the grid reliability. DSM and the improvements in forecasting the electricity produced by renewable sources may also lead to a larger integration of electricity produced by renewable energy sources. DSM usually includes an application which can communicate with the devices whose energy consumption is desired to be controlled. An important problem that holds up the implementation of DSM in large scale is that devices use di�erent communication protocols to send messages or data to other devices or controllers making the communication between devices and energy applications di�cult. The Flexible Power Application Infrastructure (FPAI) is a platform developed by the Netherlands Organisation for Applied Scienti�c Research (TNO) which aims to solve this problem. The purpose of FPAI is to create an intermediate platform that is able to connect to a variety of devices and also to support di�erent DSM systems [24]. Furthermore if a user wants to substitute its current DSM system with another, nowadays the installation of a new device that contains the hardware and software of the new system would be necessary. With FPAI the user just needs to uninstall the previous system and install a new one. One of the many DSM methodologies developed during the last years is Triana; a DSM technique developed at the University of Twente. The goal of the Triana methodology is given in [4] and it is \to manage the energy pro�les of individual devices in buildings to support the transition towards an energy supply chain which can provide all the required energy in a sustainable way". Triana has three main stages: Forecasting, Planning and Real-time Control. The ultimate goal of Triana is to exploit the exibility of devices in order to achieve a goal related to the energy consumption of these devices. A typical goal is to achieve an aggregated energy consumption pro�le for a number of devices that is as at as possible. In the Forecasting step, Triana tries to predict the exibility o�ered by devices for a speci�c time horizon. Flexibility denotes the range of controllability of every device; how much the consumption pattern of a device can be altered in order to achieve a certain goal for a number of devices. The exibility of devices can be estimated by determining parameters that in uence the operation of a device. For example a useful parameter for a domestic device that consumes electricity and produces heat, would be to predict the heat demand of the house (using information like weather data). The Planning phase takes into account the exibility of a number of devices and determines the operation of devices for a planning horizon, in order to achieve a global goal. In Real-time Control a replanning process might need to take place if we �nd that the forecast which formed the base for the Planning did not lead to the desired goal. Hereby, the replanning process takes into consideration new forecasts which use more recent data related to the behavior of the devices. The research question of the current thesis is to explore if it is possible to implement the Planning phase of Triana using the FPAI platform. It was considered useful for both the developers of FPAI and Triana to search if FPAI can indeed provide a platform on top of which Triana can be executed, as FPAI had previously been used by only one other DSM system, the Powermatcher. During the implementation, incompatibilities between FPAI and Triana had to be detected and by using speci�c tools provided by FPAI or by introducing additional methods the gap between FPAI and Triana had to be bridged.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:43 environmental science, 52 mechanical engineering
Programme:Sustainable Energy Technology MSc (60443)
Link to this item:http://purl.utwente.nl/essays/70985
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