Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

A methodological framework for the economic assessment of ict-tools for occupants’ engagement

The concept of smartness in building dates to the 1970s, but, in face of the breakthrough technological developments, a new notion of smart building is currently recognized. We talk about ambient intelligence, referring to a building which is responsive to the needs of the occupants and of the energy system. An ambient-intelligent building is human-centric; new services and interfaces are provided to the buildings occupants to learn and set their preferences, with a positive impact on their comfort level and satisfaction with the indoor environmental quality. ICT and IoT are part of the enabling technologies to exploit the potentials of smart buildings, by unlocking the capability of buildings to interact with the system they belong to. To bolster the diffusion of new technologies, methodologies to get quantitative results proving their effectiveness should be provided. In this paper the application of a well-established economic evaluation tool, the so-called Cost-Benefit Analysis, to the case of the deployment of new ICT-tools for occupants’ engagement is presented. The methodology is adopted within the H2020 Mobistyle project, where two levels of the evaluation are identified: the whole project level and the single demo case one. The purpose of the methodology is to assess the effectiveness of the adoption of the ICT-tools in producing economic value in terms of benefits for the occupants and the society. Some preliminary results of its application to the Italian case study are also presented, showing a positive socio-economic balance since the beginning of the deployment

Fostering Energy Resilience in the Rural Thai Power System—A Case Study in Nakhon Phanom

With rising electricity demand, heavy reliance on imports, and recent economic downturns due to the negative impact of the COVID-19 pandemic, supply chain bottlenecks, and the Russian invasion of Ukraine, Thailand is suffering severely from energy resilience risks. The government has therefore set a goal of decentralizing energy production through small-scale distributed renewable energy systems. To support their design and the planning process, we simulate multiple scenarios with wind turbines, photovoltaic systems, and battery storage for a model community in rural Nakhon Phanom, Thailand. Using the software NESSI4D, we evaluate and discuss their impact on energy resilience by considering environmental sustainability, economic attractiveness, and independence from the central power grid. To fill the gap of missing data on energy demand, we synthesize high-resolution load profiles from the Thailand Vietnam Socio-Economic Panel. We conclude that distributed photovoltaic systems with additional battery storage are only suitable to promote energy resilience if the government provides appropriate financial incentives. Considering temporal variations and local conditions, as well as a participatory decision-making process, are crucial for the long-term success of energy projects. Our advice to decision-makers is to design policies and regulatory support that are aligned with the preferences and needs of target communities

Life-cycle assessment of non-domestic building stocks: A meta-analysis of current modelling methods

Building stock models (BSMs) are essential for simulating the contributions of regional and national building sectors to climate change under different policy scenarios, and for identifying pathways to climate change mitigation. To date, BSMs have focused on the operational life-cycle impacts of domestic dwellings; there has been less emphasis either on non-domestic buildings (NDBs) or full life-cycle analysis. This paper provides a first review of the theory and practice of NDB stock modelling which considers life-cycle energy, emissions and costs. A meta-analysis of the literature was undertaken involving a structured search of relevant articles in key scientific repositories. 98 in-scope studies were identified and data collected on their aims and objectives, methodologies, data sources, system boundaries, considered impacts, representativeness, uncertainty analysis, validation and verification techniques, further research identified, model transparency and software tools employed. The review necessitated the classification of modelling methodologies. The existing ‘bottom-up’ and ‘top-down’ groups were found to be ambiguous and led to confusion. Therefore, an alternative methodology classification is proposed, considering both the modelling technique and model simulation data used. The findings of the analysis indicate that most approaches use engineering models employing archetype data. However, almost all current life-cycle models of NDB stocks are incomplete. Only one study considered the full building life-cycle and most did not include uncertainty analysis. The reproducibility of study results is poor since most do not provide sufficiently-detailed information on the models and data used. Critically, there is a lack of representative input data which limits their usefulness as evidence in policymaking

Bridging the gap between electricity demand and supply in West Africa : The role of renewable energy and interconnections

The electricity sector of West African countries is experiencing several challenges including, low electricity access rates, high usage of oil generators, frequent power outages and high electricity tariff rates. In an effort to solve these challenges, the West African Power Pool (WAPP) aims to interconnect all fourteen countries and develop regional power plants to benefit multiple countries. This research evaluates the role of renewable energy sources (RES) and interconnections in providing access to affordable and reliable electricity supply. This is achieved by first developing a demand model called HeDEMO (Hourly electricity DEmand MOdel) to generate hourly electricity demand in the year 2016 and 2030. The hourly demand in the residential sector of each country is modelled using a bottom-up methodology for urban and rural households, while the non-residential sectors are modelled using a top-down methodology. Next, a multi-regional economic dispatch model of West Africa’s interconnected electricity network is developed using the 2030 hourly demand dataset. The dispatch model adequately represents the intermittent characteristics of RES in different locations of the region. Six scenarios are optimized to evaluate the impact of high integration of grid-connected RES and additional interconnections. Finally, a multi criteria decision analysis is applied to assess and rank these six scenarios, based on eight sustainability criteria. The results indicate that in 2030, electricity demand in West Africa is forecasted to be five times its 2016 level. Furthermore, most of the planned interconnections by WAPP will be underutilized in 2030. Thereby providing an opportunity to integrate unexplored RES in the region. The demand methodology presented in this thesis can be applicable to developing countries that have challenges of scarce historical hourly demand data, electricity supply-demand gap, and urban/rural economic divide. Additionally, the sustainability assessment of the 2030 scenarios will help inform energy policy makers on optimal RES integration and interconnection expansion policies for the region

Techno-economic assessment of solar technologies to meet hospitals energy needs

Hospitals present one of the highest energy consumptions per surface unit, meaning that on-site renewable energy generation and energy efficiency improvements are key to lower hospitals energy demand, external energy dependence and greenhouse gases (GHG)emissions. In this work, the feasibility from the techno-economical point of view of the installation of three solar-based energy generating technologies in hospitals in different climate locations in Europe is addressed. The potential of solar energy technologies to cover the energy needs of the hospitals under study is conducted proposing a novel design and sizing optimization methodology for on-roof installations. The profitability of the different solar-based installations will vary depending on the solar technology output (electrical, thermal or both) and on the type of energy needs of the hospital; but in all cases, profitability is mostly influenced by the price of the current energy source supplying the hospital energy needs. Levelized cost of energy (LCOE)values for on-roof photovoltaic (PV), solar thermal (ST),and photovoltaic-thermal (PV-T) installations obtained are in the range of 0.028-0.056, 0.051-0.096, and 0.053-0.128 €/kWh, respectively; for locations in latitudes from 37 N (Seville) to 60N (Oslo) in Europe. Results from this work aim to serve as reference for similar studies in a wide range of climatesAlba Ramos acknowledges the Universitat Politècnica de Catalunya for her Serra Hunter Professor postPostprint (published version

Determination of the methane budget of the Amazon region utilizing airborne methane observations in combination with atmospheric transport and vegetation modeling

The Amazon basin is an important player in the global methane cycle. Objectives of this work are to establish a forward and inverse modelling framework on regional scale and to determine the methane budget in the Amazon region. Within the BARCA project (Balanço Atmosférico Regional de Carbono na Amazônia) to airborne measurement campaigns were conducted, one in November 2008 and one in May 2009. The analysis of the methane observations confirms that the Amazon basin is a strong source of methane. The majority of the emissions is found to have biogenic origin, i.e. from wetlands. A comparison of five global methane inversions shows the advantage of using satellite observations in inversion systems. The WRF (Weather Research and Forecasting) Greenhouse Gas model was developed to perform high-resolution simulations of the atmospheric methane distribution in the Amazon region. The newly written code is available within the official WRF-Chem version 3.4 release. Simulations for the two months of the BARCA campaigns with two different wetland models and three different wetland maps were conducted with the WRF Greenhouse Gas model. The comparison to observations indicates that the choice of the wetland map is more important than the choice of the wetland model for a comparison to aircraft observations. Flights with a good representation of the atmospheric transport in the model show a higher correlation between observations and simulations. The two-step regional inversion scheme TM3-STILT was applied to the Amazon region for the year 2009 using observations from the 35 m high TT34 tower. The inversion shows improvements in the representation of the seasonal cycle of the methane emissions in the Amazon basin. However, the determination of the methane budget in the Amazon basin is still highly uncertain.Das Amazonasgebiet ist eine bedeutende Methanquelle im globalen Methankreislauf. Gegenstand dieser Dissertation ist der Aufbau einer Modellinfrastruktur auf regionaler Skala sowie die Bestimmung des Methanbudgets im Amazonasgebiet. Innerhalb des BARCA Projektes (Balanço Atmosférico Regional de Carbono na Amazônia) wurden zwei Flugzeugmesskampagnen im Amazonasgebiet im November 2008 und im Mai 2009 durchgeführt. Die Analyse der Methandaten bestätigt, dass das Amazonasgebiet eine starke Methanquelle ist und der Großteil der Emissionen aus Feuchtgebieten (sogenannten „Wetlands“) stammt. Vergleiche mit fünf globalen Methaninversionen zeigen den Vorteil der Nutzung von Satellitendaten in Inversionssystemen. Das WRF (Weather Research and Forecasting) Greenhouse Gas Modell wurde entwickelt, um hoch aufgelöste Simulationen der atmosphärischen Methanverteilung im Amazonasgebiet durchführen zu können. Der Programmcode steht innerhalb der offiziellen WRF-Chem Version 3.4 zu wissenschaftlichen Zwecken frei zur Verfügung. Hiermit wurden für die beiden Monate der BARCA Flugzeugkampagnen Methansimulationen mit zwei verschiedenen Wetland-Modellen und drei verschiedenen Wetland-Karten durchgeführt. Der Vergleich mit den Beobachtungen zeigt, dass die richtige Wahl der Wetland-Karte für den Vergleich mit Flugzeugdaten entscheidender ist als die Wahl des Wetland-Modells. Flüge, bei denen das Atmosphärentransportmodell den konvektiven Transport in der Atmosphäre gut wiedergibt, zeigen eine höhere Korrelation von Beobachtungen und Simulationen. Das zweistufige regionale Inversionsschema TM3-STILT wurde für das Jahr 2009 für Methan unter Zuhilfenahme von TT34-Turmbeobachtungen in 35 m Höhe für das Amazonasgebiet angewendet. Die Inversion zeigte Verbesserungen bei der korrekten Wiedergabe des saisonalen Verlaufs der Methanemissionen im Amazonasgebiet. Insgesamt ist die Bestimmung des Methanbudgets im Amazonasgebiet immer noch mit sehr großen Unsicherheiten behaftet

Electrification of domestic hot water to aid the integration of renewable energy in the California grid

Water heating in residential buildings, also known as domestic hot water (DHW), is the third largest use of energy after appliances and space conditioning. About 90% of the residential buildings in the state use natural gas fueled water heaters, 6% use electricity, and a small percent use liquefied petroleum gas (LPG) or solar water heaters. The current energy use associated with residential water heating is small relative to the total amount of energy consumption in the residential building sector, but it is still a contributor of greenhouse gas (GHG) emissions. Improving hot water systems can be beneficial for bill customer savings, energy use, and water savings. Heat pump water heaters (HPWH) can function as grid batteries by using the water tank capability of thermal storage. The use of aggregated electrical DHW systems to store extra electricity during peak generation times or during low utility time of use (TOU) rates has the potential to alleviate some of the curtailed renewable energy power generation sources in the California grid while reducing carbon emissions and customer cost. Water heating technology was simulated using the Building Energy Modeling software California Building Energy for Code Compliance (CBECC-Res) and the California Simulation Engine (CSE). Different climate zones were explored to compare the electricity needed for a water heater operation given the same input parameters of water draw profiles and building envelope. The results show the feasibility of using HPWH and ERWH technology to participate in demand response management programs. The demand response capability of HPWH and ERWH show that they could be useful tools to accommodate surplus energy from solar generation during the solar peak hours. Whether the demand response is implemented using traditional HPWH or ERWH units, the capability of the technology to act on control signals is a necessary condition for a successful program

Environomical analysis of peak hours‘ electricity production in targeted European countries

The generation of electricity is one of the most impactful factors related to climate change. In order to mitigate the effects of Global Warming, analyzing electricity production with a time-dependency perspective is essential, to better develop further efficient grid improvement strategies. Environmental impacts and prices are two main outputs related to the power generation. This work presents the methodology to assess the potential environmental impacts and the market prices of hourly generation profiles, by means of the ENTSO-E Transparency Platform, and applying Attributional Life Cycle Assessment. This methodology is then applied to analyze the electricity production of the five pilotsites in the INVADE H2020 Project. Green House Gases emissions are determined, using the Global Warming potential indicator to assess the environmental impacts of the hourly electricity production on each targeted country. The electricity prices related to peak hours are then analyzed to discover possible links with the emissions. The highlight is on the type of resources used to meet peak hours demand, in order to understand the time variability outcomes of electricity generation. The results show the importance of having a base load covered by nuclear power plants. Furthermore, it reveals the usefulness of hydro resources, especially the flexible reservoir and pumped storage. In addition, evaluating the time-slots in which peak hours occur becomes relevant to implement energy storage strategies and peak-shaving solutions. This study can be seen as optimal support in the development of policies to increase the grid integration of renewable energy resources

Portugal's route to neutrality: the challenge of high shares of variable renewable energy

This project examines the challenge of managing the Portugueseelectric powergrid, whichwill experiencethe installationof large amounts of solar and wind capacity and full coalphasing-out during the next decade.The Irena FlexTool is used tostudy the flexibility of the power grid in 2030 under differentscenarios.Weconcludethatthe variable renewable energy (VRE)expectedinstalled capacity will frequentlyproduceexcessiveenergysupply, leading to high levelsof curtailment. Hence, the power baseload price will decreasebetween 1% and 13%andinvestments opportunities between 30,1M and 71,3M (€ 2019)will be generatedby 2030