Energy planning

Energy planning has a number of different meanings, but the most common meaning of the term is the process of developing long-range policies to help guide the future of a local, national, regional or even the global energy system. Energy planning is often conducted within governmental organizations but may also be carried out by large energy companies such as electric utilities or oil and gas producers. These oil and gas producers release greenhouse gas emissions. Energy planning may be carried out with input from different stakeholders drawn from government agencies, local utilities, academia and other interest groups. Since 1973, energy modeling, on which energy planning is based, has developed significantly. Energy models can be classified into three groups: descriptive, normative, and futuristic forecasting. Energy planning is often conducted using integrated approaches that consider both the provision of energy supplies and the role of energy efficiency in redu

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L'analyse critique de stratégies énergétiques nécessite de comprendre les différentes filières énergétiques impliquées dans l'approvisionnement en énergie et leurs impacts sur l'économie, l'environnement et la société. Le cours introduit à la formalisation de problèmes de stratégies énergétiques.

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Urban Energy System Design from the Heat Perspective using mathematical Programming including thermal Storage

Jakob Moritz Fabian Rager

Energy planning recently received more attention in Switzerland through the new strategy phasing out nuclear energy by 2034. Often however the energy planning is only done from the electrical side. This work takes a different angel and helps communities and energy utilities planning tomorrows energy system from a heat based perspective. After the data collection and structuring, the methodology presented here designs an energy system. Based on the quality of the collected data, the approach to define the energy demand should be chosen. In order to reduce calculation time, a data reduction approach is developed to reduce the input data without loosing significant information and precision. In particular, the methodology focuses on the integration of a stochastic resource, in this case solar thermal heat production, in combination with thermal energy storage. The thermal energy storage can be used as a short or long term thermal energy storage. The framework compares design solutions for the two storage types considering either a total cost approach or a life cycle assessment approach using the cumulative exergy demand (CExD). The proposed mathematical programming framework is based on a mixed integer linear programming (MILP) approach, that can work on different levels of detail between building to community or city level. The optimization problem can also be further simplified to a linear problem, increasing the size of problem that can be solved while reducing or keeping a constant computation time. The discussed cases show an interest in further investigating storage solution using both, the short and long term storage at once, because they allow to reduce the system's overall costs or CExD significantly. The framework is then extended to consider buildings as an energy storage. The building's internal temperature can be raised from 20 \degree C up to 23 \degree C, giving a comfort temperature range that can be used for storing heat. The integrating of both storage types, the thermal energy storage and the building as an energy storage, show no significant impact on the energy system design. However, costs or CExD can be reduced. In addition, the heat demand can be modified through the decision of optimal energy retrofitting strategy for a group of buildings. The framework decides which of the building to refurbish based the overall CExD including CExD used for retrofitting the building. Finally, a method is proposed to integrate uncertainty of the model's input parameters into the system design. A global sensitivity analysis evaluates the impact of each uncertain parameter onto the system, allowing to focusing on the outputs of interest. Robust optimization is applied with a simulation-based approach, the additional costs for a robust design are calculated, as well as the different unit sizes. The low complexity of the developed models allows for an easy integration of new data collected during the development of a project, which is often the case in urban energy planning applications.

EPFL2015

ECOS: Integrated and practical energy planning for new districts

Cédric Dorsaz, François Maréchal, Jakob Moritz Fabian Rager

In this paper, we propose a unified method for the integrated energy planning during the development of new districts for all involved actors. Taking energy related problems such as equipment choice and size, costs and environmental impact early into consideration avoids confronting engineers later on with difficult to resolve problems. We provide a method that has been proven during the bidding process of the Metamorphose project in Lausanne. During the planning of new districts, different stakeholders such as politicians, architects or urban plan- ners are involved in the definition of the requirements. Each actor has its own set of methods with its specialized tools to assure reaching his goals. Bringing the actors together and integrating their tools into the decision process from the beginning on helps finding a sustainable solution and economizes time for each actor. Based on the initial demand of the City of Lausanne, the following set of indicators is used: • operation and investment costs, • primary energy: renewable and fossil fuel usage, • greenhouse gas emissions and • exergy efficiency. A dynamic building simulation software, CitySim, defines the energy demand and estimates the solar irradiation on the roof tops. This demand is converted into a composite curve using EnerGIS. Applying process integration techniques identifies the best equipment size and type which will then be used to calculate the different indicators. The City of Lausanne defined the square meters to be constructed for each category. In addition to the private program with big multi-story dwellings and office buildings, the city included a public program with an Olympic swimming pool and a football stadium. Our proposed method considers both programs and evaluated systematically each proposal based on the criteria mentioned in the bidding process. Compared to the last public bidding process during the metamorphose project, this time, the winner was scored among the top scored proposals in the energy field. Besides energy, the jury used other criteria such as mobility and architectural design to identify their winner. Using expertise from different laboratories at EPFL, the City of Lausanne was able to consider a com- plex set of indicators to identify their winner.

2013

MEU: An urban energy management tool for communities and multi-energy utilities

Massimiliano Capezzali, Gaëtan Cherix, François Maréchal, Jakob Moritz Fabian Rager, Damien Rebeix

In order to facilitate urban energy management and energy planning, the project MEU developed a web based tool as a decision support system for decision makers. Using a web based approach minimizes the effort on the client site as no software needs to be installed or be updated on the personal computer. Updates are published by the development team on the central server. During the first phase of the project, First, data are collected based on the buildings in the federal land registry offices' data. The data contains all the relevant elements in the energy conversion chain of a given city over the last couple of years available on an annual basis: meteorological data, a list of accessible resources, energy conversion technologies, energy distribution networks and buildings as consumers of different energy services. Second, all buildings and networks are geo-referenced to allow plotting maps. This already gives a comprehensive overview of the current energy state of a city. Third, measurements of (annual) energy consumptions are introduced allowing the performance monitoring. With the annual energy consumption of each energy conversion system, the current state of a city can be monitoring and compared to previous years. Fourth, this data is structured and completed for the use in the energy simulation software: CitySim for the dynamic building energy demand simulation and EnergyTechnology for the calculation of the energy conversion technologies. Especially the completion demands supplementary work as the data sets are often not very comprehensive. Therefore default values based on the current Swiss norms and previous publications are used to minimize the errors made in the simulations. As a set of default values is provided in the platform, it runs even if only a small data set is imported. When more information is available such as the energy consumption or the physical building data, the platform can easily be updated to increase the accuracy of the results. With this approach, urban energy flows from resource to useful energy can be tracked and inefficiencies can be spotted easily along the conversion processes. Furthermore, the creation of scenarios based on a given actual year allows for example the quick comparison of different energy conversion scenarios for different technological measures introduced in a city or the evaluation of refurbishment strategies on the energy demand. The maps allow to geo-localize priority areas and help representing the results.

2013