• Energy Research

Abstract High fuel costs, increasing energy security and concerns with reducing emissions have pushed governments to invest in the use of renewable energies for electricity generation. However, the intermittence of most renewable resources when renewable energy provides a significant share of the energy mix can create problems to electricity grids, which can be minimized by energy storage systems that are usually not available or expensive. An alternative solution consists on the use of demand side management strategies, which can have the double effect of reducing electricity consumption and allowing greater efficiency and flexibility in the grid management, namely by enabling a better match between supply and demand. This work analyzes the impact of demand side management strategies in the evolution of the electricity mix of Flores Island in the Azores archipelago which is characterized by high shares of renewable energy and therefore the introduction of more renewable energy sources makes it an interesting case study for testing innovative solutions. The electricity generation system is modeled in TIMES, a software which optimizes the investment and operation of wind and hydro plants until 2020 based on scenarios for demand growth, deployment of demand response technologies in the domestic sector and promotion of behavioral changes to eliminate standby power. The results show that demand side management strategies can lead to a significant delay in the investment on new generation capacity from renewable resources and improve the operation of the existing installed capacity.

Abstract Throughout the world, but mostly in developing countries, there are presently regions where electricity supply is insufficient or non-existing. Innumerous authors affirm that this lack of access to electricity is a key factor in perpetuating poverty around the world and compromises the socio-economic progress of those places. Thus, improving energy access is a priority since 1.3 billion people around the world still lack access to electricity, 84% of them living in rural areas. However, the energy demand in developing countries is completely different from what is observed in the regions like Europe or North America. According to the International Energy Agency, the households in many non-OECD countries still rely heavily on traditional, non-marketed energy sources, including wood and waste, for heating and cooking. Therefore, designing energy systems for developing countries presents a great challenge: designing from scratch a system that is both environmentally and economically viable and that enables social and economic development for the populations. This work focuses on the development of a system design methodology that optimizes the final solution taking into account a demand growth pathway that reflects the economic development associated with the introduction of electricity.

The road passenger transport is responsible for a large share of energy consumption and pollutants emission in Europe. Efforts have been made in the definition of new policies to reduce the environmental impacts of this sector. However, an integrated and consistent assessment of the most promising policies is required, using specific European indicators. For that matter, a life-cycle analysis was applied to the road passenger transport, for the European Union with 27 countries (EU27) in 2010, following a basket-of-products methodology and considering three main stages: production, use, and end-of-life of vehicles. Simapro 8 software was used, along with Ecoinvent 3 database and the impact assessment method International Reference Life Cycle Data System (ILCD) 2011 Midpoint+. Changes in vehicle production processes, vehicle constitution, and energy sources for vehicle propulsion were analyzed. The policies resulting in a decrease in all impact categories are the use of smaller or lightweight vehicles by positively influencing use, production, and end-of-life of vehicles. The use of more recent vehicles technology or diesel vehicles show substantial reductions in, respectively, five and eight impact categories (out of 15), justifying their adoption in the European fleet. Generally, the most notorious policies compared to the actual transport paradigm, like compressed natural gas (CNG), biofuels, or electric vehicles use, show the greatest reduction in climate change (up to 46%) but also a very significant rise of impacts in the categories that in the conventional basket-of-products already resulted in the worst indicators after normalization.

The design of transition pathways for sustainable electricity systems with high penetrations of renewable energy sources requires the use of energy modeling tools that are able to account for two key aspects: the evolution of fossil fuels and technology prices, and the natural dynamics of renewable resources. However, the modeling methodologies most currently used focus on only one of these two aspects, which hinders their suitability for performing long-term analysis with high penetrations of renewable energy sources. This paper presents a modeling framework that is able to optimize the investment in new renewable generation capacity on the long-term while taking into account the hourly dynamics of electricity supply and demand. The framework combines two of the most used energy planning tools, each able to account for one of the aspects of the modeling of energy systems. The framework was applied to continental Portugal for the time period of 2005–2050, in order to identify optimal investment plans in new renewable and fossil generation capacity with the goal of achieving significant CO2 emissions reduction, under different scenarios. The results show that the inclusion of dynamics in the modeling methodology can help avoid overinvestment and reduce the excess of electricity from renewable energy sources that cannot be used by the system. These results can have a significant impact on the design of a sustainable electricity system and may lead to a diversification of the energy sources used.

Abstract The potential to reschedule part of the electricity demand in energy systems is seen as a significant opportunity to improve the efficiency of the systems, especially on remote and isolated systems. From the supply point of view, that flexibility might bring significant improvements to the generation dispatch, especially when in the presence of renewable resources; from the demand point of view, that flexibility could allow customers to benefit from reducing their energy bills. To study these types of implications, modeling tools have been introducing the possibility to include flexible loads on the optimization process, although some use very simplified methodologies to do it. This study compares how different modeling tools consider fixed and flexible loads in the dispatch optimization, analyzing their different strategies. Three different scenarios were simulated in HOMER, EnergyPLAN and an economic dispatch self-built model in Matlab, using as case study the Corvo Island, Portugal. The comparison results indicate that HOMER and EnergyPLAN still assume that flexible loads are a second priority load that are met in off-peak hours or in the presence of excess electricity from renewable sources, not taking directly into account the economic impact of such decision. On the other hand, the self-built model that is more flexible on the optimization approach is the more close to the actual operation and presents the best savings when using demand response strategies, albeit representing only a 0.3% decrease in the operation costs. We conclude that the modeling tools should evolve and refine their optimization strategies to capture the total benefits of using demand response to improve energy systems performance.

This work analyzes different modeling methodologies for balancing the electricity supply sources and the electricity demand in systems with high penetration of intermittent renewable energy sources, such as wind and run-of-river hydro. This work also explores the reasons and the circumstances where common balance approaches used by mid- and long-term energy models show significant differences in dispatched renewable sources, overestimating the renewable share in the electricity mix and underestimating the amount of CO2 emitted by the electric system, when compared to balance methods with high time resolution. These reasons and circumstances are illustrated for the Flores island (Azores) case study which has already achieved a share of 50% of renewable energies in electricity production in 2009.

The European Union proposed the introduction of taxes on emitted CO2 as an effective policy measure for the reduction of CO2 emissions in its electricity sector. Applying the TIMES (The Integrated MARKAL-EFOM System) modeling tool, this paper examines the cost effectiveness of different evolutions of CO2 taxes under the Emissions Trading System in Europe by 2050 in order to analyze the possible roles and limits of different mitigation technologies within the Portuguese electricity supply system. The results were analyzed based on the final year CO2 emissions of the electricity system when compared to 1990 levels. The results show that when CO2 prices stay below 50 €/tonne by 2050 there is no reduction in emitted CO2 emissions when compared to the levels of 1990. For CO2 prices reaching between 50 and 100 €/tonne there is a clear reduction in CO2 with the increase in the price, from 7% with 50 €/tonne to 79% with 100 €/tonne. For prices above 100 €/tonne the increased taxation has only a slight impact on the reduction of CO2 emissions, as even with a 300 €/tonne price the CO2 reductions achieved are only of 87%.

Abstract Urban metabolism provides a characterization of anthropogenic material flows in urban systems and should contribute to identify the economic activities that were involved on their supply and transformation. Typically, its quantification requires data that is not easily available in different geographies. This paper makes use of a methodology based on monetary input–output tables and international trade statistics that might be easily replicable to many metropolitan areas in the world, and which is intended to provide a first rough estimation of urban material flows. The paper discusses the results obtained for four metropolitan areas (Lisbon, Paris, Seoul–Incheon and Shanghai), assessing the material requirements of these economies. The urban areas are compared in terms of the quantity and the type of material input, destination of materials within the economy and their distribution among economic activities. The results showed that while Lisbon is the most diverse urban area in terms of the consumption of material types, it is also the urban area with the least diversified manufacturing sector. The application of this methodology to several urban areas and across multiple years enables the assessment of the technological and economic evolution of those regions.

Abstract Energy policies are often related to the global effort in reducing greenhouse gas emissions through increased use of renewable energies in electricity production. The impact of these policies is usually calculated by energy planning tools. However, the modeling methodologies most currently used are not adequate to simulate long-term scenarios while considering the hourly dynamics of supply and demand. This paper presents an extension of the TIMES energy planning tool for investment decisions in electricity production that considers seasonal, daily and hourly supply and demand dynamics. The inclusion of these dynamics enables the model to produce more accurate results in what concerns the impact of introducing energy efficiency policies and the increased use of renewable energies. The model was validated in Sao Miguel (Azores, Portugal) for the years 2006–2009, where a comparison with real data showed that the model can simulate the supply and demand dynamics. Further, the long-term analysis shows that the inclusion of these dynamics contributes to a better assessment of the renewable energy potential, suggests the postponement of investments in new generation capacity, and demonstrates that using fine time resolution modeling is very valuable for the design of effective policy measures under high renewable penetration energy systems.