Using strong sustainability to optimize electricity generation fuel mixes

This work represents a contribution to the field of sustainable electricity system design by using an optimization tool to specify the final mix composition, subject to the constraints of: emissions that are within the biocapacity of the region; a diverse and robust electricity supply system; and supply that at least meets current demand. The 25-country European Union (EU-25) is used as a case study. All the goals, save diversity, can be met by re-structuring the current fuel mix, thus maintaining current consumption levels. The diversity target is only met when consumption is reduced by 10-15% and the constraint on maximum material throughput is relaxed. Re-structuring the mix and reducing consumption is insufficient to achieve a sustainable EU carbon footprint. However, the solution proposed singlehandedly allows the EU to meet its Kyoto emissions target as well as its 2007 policy of a reduction of 20% in greenhouse gas emissions by 2020. © 2007 Elsevier Ltd. All rights reserved.

Linking energy policy, electricity generation and transmission using strong sustainability and co-optimization

The design of a sustainable electricity generation and transmission system is based on the established science of anthropogenic climate change and the realization that depending on imported fossil-fuels is becoming a measure of energy insecurity of supply. A model is proposed which integrates generation fuel mix composition, assignment of plants and optimized power flow, using Portugal as a case study. The result of this co-optimized approach is an overall set of generator types/fuels which increases the diversity of Portuguese electricity supply, lowers its dependency on imported fuels by 14.62% and moves the country towards meeting its regional and international obligations of 31% energy from renewables by 2020 and a 27% reduction in greenhouse gas emissions by 2012, respectively. The quantity and composition of power generation at each bus is specified, with particular focus on quantifying the amount of distributed generation. Based on other works, the resultant, overall distributed capacity penetration of 19.02% of total installed generation is expected to yield positive network benefits. Thus, the model demonstrates that national energy policy and technical deployment can be linked through sustainability and, moreover, that the respective goals may be mutually achieved via holistic, integrated design. ©2009 IEEE.

Electricity Storage Using a Thermal Storage Scheme

The increasing use of renewable energy technologies for electricity generation, many of which have an unpredictably intermittent nature, will inevitably lead to a greater demand for large-scale electricity storage schemes. For example, the expanding fraction of electricity produced by wind turbines will require either backup or storage capacity to cover extended periods of wind lull. This paper describes a recently proposed storage scheme, referred to here as Pumped Thermal Storage (PTS), and which is based on "sensible heat" storage in large thermal reservoirs. During the charging phase, the system effectively operates as a high temperature-ratio heat pump, extracting heat from a cold reservoir and delivering heat to a hot one. In the discharge phase the processes are reversed and it operates as a heat engine. The round- trip efficiency is limited only by process irreversibilities (as opposed to Second Law limitations on the coefficient of performance and the thermal efficiency of the heat pump and heat engine respectively). PTS is currently being developed in both France and England. In both cases, the schemes operate on the Joule-Brayton (gas turbine) cycle, using argon as the working fluid. However, the French scheme proposes the use of turbomachinery for compression and expansion, whereas for that being developed in England reciprocating devices are proposed. The current paper focuses on the impact of the various process irreversibilities on the thermodynamic round-trip efficiency of the scheme. Consideration is given to compression and expansion losses and pressure losses (in pipe-work, valves and thermal reservoirs); heat transfer related irreversibility in the thermal reservoirs is discussed but not included in the analysis. Results are presented demonstrating how the various loss parameters and operating conditions influence the overall performance.

Thermodynamic analysis of pumped thermal electricity storage

The increasing use of renewable energy technologies for electricity generation, many of which have an unpredictably intermittent nature, will inevitably lead to a greater need for electricity storage. Although there are many existing and emerging storage technologies, most have limitations in terms of geographical constraints, high capital cost or low cycle life, and few are of sufficient scale (in terms of both power and storage capacity) for integration at the transmission and distribution levels. This paper is concerned with a relatively new concept which will be referred to here as Pumped Thermal Electricity Storage (PTES), and which may be able to make a significant contribution towards future storage needs. During charge, PTES makes use of a high temperature-ratio heat pump to convert electrical energy into thermal energy which is stored as ‘sensible heat’ in two thermal reservoirs, one hot and one cold. When required, the thermal energy is then converted back to electricity by effectively running the heat pump backwards as a heat engine. The paper focuses on thermodynamic aspects of PTES, including energy and power density, and the various sources of irreversibility and their impact on round-trip efficiency.

Phrase-based statistical language generation using graphical models and active learning

Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation decision process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to new domains. This paper presents BAGEL, a statistical language generator which uses dynamic Bayesian networks to learn from semantically-aligned data produced by 42 untrained annotators. A human evaluation shows that BAGEL can generate natural and informative utterances from unseen inputs in the information presentation domain. Additionally, generation performance on sparse datasets is improved significantly by using certainty-based active learning, yielding ratings close to the human gold standard with a fraction of the data. © 2010 Association for Computational Linguistics.

Reducing energy demand: what are the practical limits?

Concern over the global energy system, whether driven by climate change, national security, or fears of shortage, is being discussed widely and in every arena but with a bias toward energy supply options. While demand reduction is often mentioned in passing, it is rarely a priority for implementation, whether through policy or through the search for innovation. This paper aims to draw attention to the opportunity for major reduction in energy demand, by presenting an analysis of how much of current global energy demand could be avoided. Previous work led to a "map" of global energy use that traces the flow of energy from primary sources (fuels or renewable sources), through fuel refinery, electricity generation, and end-use conversion devices, to passive systems and the delivery of final energy services (transport, illumination, and sustenance). The key passive systems are presented here and analyzed through simple engineering models with scalar equations using data based on current global practice. Physically credible options for change to key design parameters are identified and used to predict the energy savings possible for each system. The result demonstrates that 73% of global energy use could be saved by practically achievable design changes to passive systems. This reduction could be increased by further efficiency improvements in conversion devices. A list of the solutions required to achieve these savings is provided.

Addressing the cognitive and social influence inhibitors during the ideation stages of technology roadmapping workshops

Technology roadmapping workshops are essentially a social mechanism for exploring, creating, shaping and implementing ideas. The front-end of a roadmapping session is based on brainstorming in order to tap into the group's diverse knowledge. The aim of this idea stimulation activity is to capture and share as many perspectives as possible across the full scope of the area of interest. The premise to such group brainstorming is that the sharing and exchange of ideas leads to cognitive stimulation resulting in a greater overall group idea generation performance in terms of the number, variety and originality of ideas. However, it must be recognized that the ideation stage in a roadmapping workshop is a complex psychosocial phenomenon with underlying cognitive and social processes. Thus, there are downsides to group interactions and these must be addressed in order to fully benefit from the power of a roadmapping workshop. This paper will highlight and discuss the key cognitive and social inhibitors involved. These include: production blocking, evaluation apprehension, free riding/social loafing, low norm setting/matching. Facilitation actions and process adjustments to counter such negative factors will be identified so as to provide a psychosocial basis for improving the running of roadmapping workshops. © 2009 PICMET.