Optimization approaches for exploiting the load flexibility of electric heating devices in smart grids

Energy systems all over the world are undergoing a fundamental transition to tackle climate change and other environmental challenges. The share of electricity generated by renewable energy sources has been steadily increasing. In order to cope with the intermittent nature of renewable energy sources, like photovoltaic systems and wind turbines, the electrical demand has to be adjusted to their power generation. To this end, flexible electrical loads are necessary. Moreover, optimization approaches and advanced information and communication technology can help to transform the traditional electricity grid into a smart grid. To shift the electricity consumption in time, electric heating devices, such as heat pumps or electric water heaters, provide significant flexibility. In order to exploit this flexibility, optimization approaches for controlling flexible devices are essential. Most studies in the literature use centralized optimization or uncoordinated decentralized optimization. Centralized optimization has crucial drawbacks regarding computational complexity, privacy, and robustness, but uncoordinated decentralized optimization leads to suboptimal results. In this thesis, coordinated decentralized and hybrid optimization approaches with low computational requirements are developed for exploiting the flexibility of electric heating devices. An essential feature of all developed methods is that they preserve the privacy of the residents. This cumulative thesis comprises four papers that introduce different types of optimization approaches. In Paper A, rule-based heuristic control algorithms for modulating electric heating devices are developed that minimize the heating costs of a residential area. Moreover, control algorithms for minimizing surplus energy that otherwise could be curtailed are introduced. They increase the self-consumption rate of locally generated electricity from photovoltaics. The heuristic control algorithms use a privacy-preserving control and communication architecture that combines centralized and decentralized control approaches. Compared to a conventional control strategy, the results of simulations show cost reductions of between 4.1% and 13.3% and reductions of between 38.3% and 52.6% regarding the surplus energy. Paper B introduces two novel coordinating decentralized optimization approaches for scheduling-based optimization. A comparison with different decentralized optimization approaches from the literature shows that the developed methods, on average, lead to 10% less surplus energy. Further, an optimization procedure is defined that generates a diverse solution pool for the problem of maximizing the self-consumption rate of locally generated renewable energy. This solution pool is needed for the coordination mechanisms of several decentralized optimization approaches. Combining the decentralized optimization approaches with the defined procedure to generate diverse solution pools, on average, leads to 100 kWh (16.5%) less surplus energy per day for a simulated residential area with 90 buildings. In Paper C, another decentralized optimization approach that aims to minimize surplus energy and reduce the peak load in a local grid is developed. Moreover, two methods that distribute a central wind power profile to the different buildings of a residential area are introduced. Compared to the approaches from the literature, the novel decentralized optimization approach leads to improvements of between 0.8% and 13.3% regarding the surplus energy and the peak load. Paper D introduces uncertainty handling control algorithms for modulating electricheating devices. The algorithms can help centralized and decentralized scheduling-based optimization approaches to react to erroneous predictions of demand and generation. The analysis shows that the developed methods avoid violations of the residents\u27 comfort limits and increase the self-consumption rate of electricity generated by photovoltaic systems. All introduced optimization approaches yield a good trade-off between runtime and the quality of the results. Further, they respect the privacy of residents, lead to better utilization of renewable energy, and stabilize the grid. Hence, the developed optimization approaches can help future energy systems to cope with the high share of intermittent renewable energy sources

Advances in Energy System Optimization

The papers presented in this open access book address diverse challenges in decarbonizing energy systems, ranging from operational to investment planning problems, from market economics to technical and environmental considerations, from distribution grids to transmission grids, and from theoretical considerations to data provision concerns and applied case studies. While most papers have a clear methodological focus, they address policy-relevant questions at the same time. The target audience therefore includes academics and experts in industry as well as policy makers, who are interested in state-of-the-art quantitative modelling of policy relevant problems in energy systems. The 2nd International Symposium on Energy System Optimization (ISESO 2018) was held at the Karlsruhe Institute of Technology (KIT) under the symposium theme “Bridging the Gap Between Mathematical Modelling and Policy Support” on October 10th and 11th 2018. ISESO 2018 was organized by the KIT, the Heidelberg Institute for Theoretical Studies (HITS), the Heidelberg University, the German Aerospace Center and the University of Stuttgart

The effect of price regulation on the performances of industrial symbiosis: a case study on district heating

This study of the district heating system of Aalborg (Denmark) analyses how fiscal instruments affect the extent excess heat recovery helps reduce the carbon footprint of heat. It builds on a supply-and-demand framework and characterizes the changes in excess heat supply with consequential life cycle assessment in reference to one gigajoule distributed. The heat supply curve is defined through ten scenarios, which represent incremental shares of excess heat as the constraints of the said legal instruments are lifted. The heat demand curve follows the end-users’ response to price changes. The most ambitious scenario doubles the amount of excess heat supplied and reduces the heat carbon footprint by 90% compared to current level, for an end-user price increase of 41%. The price increase results from a higher supply of excess heat at a higher price and an unchanged purchase cost from the coal-fired CHP plant despite a lower supply. This highlights the necessity of a flexible supplier when the share of recovered excess heat is high

Kysyntäjouston ohjausstrategioiden optimointi suomalaisissa kaupungin omistamissa kiinteistöissä

The entire energy business from producers to energy end-users is currently undergoing major reforms due to more and more ambitious targets for climate change mitigation measures and energy efficiency of buildings stemming from various international agreements and dwindling of conventional fossil fuel resources. Both supply and demand side measures are required to tackle the issues at hand and much work has already been done in regards to developing and increasing renewable energy generation and demand side energy efficiency. Demand response is a more novel demand side action which targets reducing energy demand during peak demand hours, which in turn can reduce the need for expensive peak production and contribute to increasing the stability of the grid when system reliability is jeopardized. In practice, demand response means that energy use is changed from its typical patterns when it is beneficial from the relevant parties’ point of view. This thesis investigates heat load reduction potential for demand response purposes in typical Finnish city-owned district heated buildings. The potential is analyzed for three different types of buildings individually (office, school and apartment building) and on a city scale for a certain city located in southern Finland by creating building energy models for example buildings in the simulation software IDA ICE and optimizing demand response control strategies in the optimization software MOBO. MOBO is used to determine an optimal combination of controls for these strategies in terms of maximum direct cost saving potential resulting from reduced energy consumption. The optimizations are conducted for a few different example days in winter and in spring, and for a single three-hour-long demand response event on these days. Furthermore, the district heat producer’s point of view is regarded by using hourly marginal cost based district heat pricing as one of the minimized objectives in the optimizations. Hourly heat production costs and marginal costs before and after demand response implementation are calculated for the studied city in a previously developed MATLAB simulation model. The results of the simulations and optimizations indicate that heat load reduction potential for demand response in individual buildings is 50-80% for a single demand response event during the day and depending on the building type. On a city-scale, the achieved heat load reduction is 59 MW or 60-70% of the original heat demand at most, which accounts for approximately 10% of the heat demand of the entire city at the time.Energiateollisuus ja energiajärjestelmät tuottajista loppukäyttäjiin ovat tällä hetkellä keskellä merkittävää uusiutumista ja suuria muutoksia johtuen yhä kunnianhimoisemmista kansainvälisistä ilmastotavoitteista ja jatkuvasti tiukkenevista kansallisista energiatehokkuusmääräyksistä. Muutokset koskevat sekä tuottajia että kuluttajia, ja paljon työtä on jo tehty liittyen uusiutuvien energiamuotojen kehittämiseen ja käytön lisäämiseen sekä kuluttajapuolenkin energiatehokkuuteen. Kysyntäjousto on eräs vähemmän yleistynyt kuluttajapuolen toimintamalli, jolla pyritään vähentämään energiankulutusta kulutuspiikkien aikana, jolloin myös kalliin huipputuotannon tarve vähenee, ja parantamaan tarvittaessa systeemin tasapainoa sen ollessa uhattuna. Käytännössä kysyntäjousto tarkoittaa energiankäytön hetkellistä muuttamista normaalitilanteesta sen ollessa kysyntäjoustoon osallistuvien osapuolten kannalta edullista. Tässä diplomityössä tutkitaan kaukolämmön kysyntäjoustopotentiaalia lämmitystehon pienentämisen kannalta tyypillisissä Suomen kaupunkien omistamissa kiinteistöissä. Potentiaalia tutkitaan kolmessa erilaisessa rakennuksessa (toimisto, asuinkerrostalo ja koulu) yksitellen sekä koko kaupungin tasolla eräässä Etelä-Suomen kaupungissa. Esimerkkirakennuksista luodaan energiasimulointimallit IDA ICE – ohjelmalla, jonka jälkeen MOBO-optimointityökalulla määritetään erilaisista talotekniikkaohjauksista koostuva optimaalinen kysyntäjoustokombinaatio, jolla voidaan saavuttaa suurimmat energiankäytön vähenemisestä johtuvat kustannussäästöt kiinteistönomistajan sekä kaukolämpöyhtiön kannalta. Optimointitapaukset tehdään esimerkinomaisille talvi- ja kevätpäiville, joina kumpanakin toteutetaan yksi kolmen tunnin pituinen kysyntäjoustojakso aamupäivän aikana. Kaukolämmön tuottajan näkökulmaa pyritään tuomaan esille käyttämällä yhtenä optimoitavan tekijänä kaukolämmön kuluttajahintana käytettäviä lämmöntuotannon tuntikohtaisia marginaalikustannuksia. Tuntikohtaiset tuotantokustannukset ja marginaalikustannukset ilman kysyntäjoustoa ja sen kanssa määritetään MATLAB simulointimallia hyväksi käyttäen. Simulointien ja optimointien tulosten perusteella kaikilla kolmella rakennustyypillä on selvää tehonleikkauspotentiaalia kysyntäjoustotarpeisiin. Yksittäisille rakennuksille tehon alenema yksittäisen kysyntäjouston aikana on 50-80% alkuperäisestä kaukolämpötehosta. Koko kaupungin tasolle skaalattuna tämä tarkoittaa yhteensä maksimissaan 59 MW:n kaukolämpötehon leikkausta, joka on 60-70% alkuperäisestä näiden rakennustyyppien koko kaupungin omistaman rakennusmassan tehosta ja yhteensä noin 10% koko kaupungin kyseisen hetken kaukolämmön tarpeesta

Energy for Development: The Potential Role of Renewable Energy in Meeting the Millennium Development Goals

This report identifies renewable energy options that are currently in wide use in some regions and that are now ready for large-scale introduction in many areas of the developing world. Through 26 case studies, the report cites biogas, small hydro, solar, wind, ethanol, and biodiesel, among other technologies, as viable options for poverty alleviation in developing countries.As their cost has declined and their reliability has improved, renewable energy technologies have often emerged as more affordable and practical means of providing essential energy services. Although the strongest renewable energy growth has been in grid-connected power systems and liquid fuels for transportation, several technologies are well-suited to providing modern energy services for low-income people. Scaling up a broad portfolio of renewable energy options can make a major contribution to achieving the Millennium Development Goals, concludes the report.The creation of REN 21 was sponsored by the German Federal Ministry for Economic Cooperation and Development and the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety. Formally established in Copenhagen in June 2005, REN 21 is now supported by a steering committee of 11 governments, five intergovernmental organizations, five non-governmental organizations, and several regional, local and private organizations

Towards the implementation of the Green Building concept in agricultural buildings: a literature review

The “Green Building” is an interdisciplinary theme, where the green building concept includes a multitude of elements, components and procedures which diverge to several subtopics that intertwined to form the green building concept.  Generally, the green building is considered to be an environmental component, as the green building materials are manufactured from local eco-sources, i.e. environmentally friendly materials, which are then used to make an eco-construction subject to an eco-design that provides a healthy habitat built on the cultural and architectural heritage in construction while ensuring conservation of natural resources.  This ensures disassembling the building components and materials, after a determined building lifetime, to environmentally friendly materials that can be either re-used or recycled.  During their lifecycle, the green buildings minimize the use of resources (energy and water); reduce the harmful impact on the ecology, and provide better indoor environment.    Green buildings afford a high level of environmental, economic, and engineering performance.  These include energy efficiency and conservation, improved indoor air quality, resource and material efficiency, and occupant's health and productivity.  This study focuses on defining green buildings and elaborating their interaction with the environment, energy, and indoor air quality and ventilation.  Furthermore, the present study investigates the green building materials (e.g. biocement, eco-cement and green concrete), green designs, green roofs, and green technologies.  Additionally, the present study highlights the green buildings rating systems, the economics of green buildings, and the challenges that face the implementation. Eventually, the interdependency between the green buildings and agriculture has been discussed.   Keywords: green building, agricultural buildings, biocement, eco-cement, green concrete, green roofs, low-energy building, zero-carbon building, eco-constructio