Department of Energy's facilities for defense materials production : hearing before the Subcommittee on Energy Research and Development of the Committee on Energy and Natural Resources, United States Senate, One Hundredth Congress, first session, on the public health and safety and environmental aspects of operation ... July 17, 1987.

Pt. 2 has subtitle: Hearings before the Committee on Energy and Natural Resources, United States Senate, One Hundredth Congress, first session, on the status of the Department of Energy's effects to address issues concerning the defense materials production reactors ... October 27 and 29, 1987.

Department of Energy National Laboratory Cooperative Research Initiatives Act : hearings before the Subcommittee on Energy Research and Development of the Committee on Energy and Natural Resources, United States Senate, One Hundredth Congress, first session on S. 1480 ... September 15 and 17, 1987.

Shipping list no.: 88-374-P (pt. 1).

A review of the effects of distributed energy resources and power-electronic controlled loading on distribution network stability

This paper looks at potential distribution network stability problems under the Smart Grid scenario. This is to consider distributed energy resources (DERs) e.g. renewable power generations and intelligent loads with power-electronic controlled converters. The background of this topic is introduced and potential problems are defined from conventional power system stability and power electronic system stability theories. Challenges are identified with possible solutions from steady-state limits, small-signal, and large-signal stability indexes and criteria. Parallel computation techniques might be included for simulation or simplification approaches are required for a largescale distribution network analysis.

Reconfiguration of distribution network into islanded microgrids considering development of distributed energy resources

This paper discusses the potentiality of reconfiguring distribution networks into islanded Microgrids to reduce the network infrastructure reinforcement requirement and incorporate various dispersed energy resources. The major challenge would be properly breaking down the network and its resultant protection and automation system changes. A reconfiguration method is proposed based on allocation of distributed generation resources to fulfil this purpose, with a heuristic algorithm. Cost/reliability data is required for the next stage tasks to realise a case study of a particular network.

Review on protection issues of low-voltage distribution network with multiple powerelectronic-converter-interfaced distribution energy resources

The realisation of an eventual low-voltage (LV) Smart Grid with a complete communication infrastructure is a gradual process. During this evolution the protection scheme of distribution networks should be continuously adapted and optimised to fit the protection and cost requirements at the time. This paper aims to review practices and research around the design of an effective, adaptive and economical distribution network protection scheme. The background of this topic is introduced and potential problems are defined from conventional protection theories and new Smart Grid technologies. Challenges are identified with possible solutions defined as a pathway to the ultimate flexible and reliable LV protection systems.

Building partnership for drug and ag discovery and conservation of the natural resources in Brazil.

2009

Valuation of tourism's natural resources

Discusses the implications of the economic valuation of natural resources used for tourism and relates this valuation to the concept of total economic valuation. It demonstrates how applications of the concept of total economic valuation can be supportive of the conservation of natural resources used for tourism. Techniques for valuing tourism’s natural resources are then outlined and critically evaluated. Consideration is given to travel cost methods, contingent valuation methods, and hedonic pricing approaches before concentrating on current developments of valuation techniques, such as choice modelling. The general limitations of existing methods are considered and it is argued that more attention should be given to developing guidelines that will identify ‘optimally imperfect methods’. An overall assessment concludes this article.

Habitat requirements for the conservation of arboreal marsupials in dry sclerophyll forests of Southeast Queensland, Australia

The habitat requirements of arboreal marsupials were investigated in the dry sclerophyll forests of southeast Queensland, Australia. Species richness and abundance of arboreal marsupials was correlated to the proportion of total stand basal area occupied by lemon-scented gum (Corymbia citriodora), the height of the tallest trees, and density of hollow-bearing trees. The first two factors suggested that the most productive forests were also the most suitable habitats for arboreal marsupials. Importantly, the number of hollow-bearing trees was a significant factor in determining species richness and abundance of arboreal marsupials in this study, with the maximum number of species reached at sites containing greater than or equal to4 hollow-bearing trees/ha, and maximum abundance occurring at sites with :6 hollow-bearingtrees/ha. The proportion of C. citriodora was significant for the presence of the common brushtail possum (Trichosurus vulpecula), greater glider (Petauroides volans), and the yellow-bellied glider (Petaurus australis), while understory Acacia sp. density was important for the presence of the sugar glider (Petaurus breviceps). The yellow-bellied glider was also affected by two other variables: the density of hollow-bearing trees >50 cm diameter at breast height (dbh), and the time since the last logging. Current Codes of Practice regulating the density of hollow-bearing trees and silvicultural practices in state-owned timber production forests appear to provide adequate protection for arboreal marsupials, but the recently introduced increase in timber extraction rates within state forests may be detrimental to the animals. Also, protective prescriptions do not apply to the privately owned and leasehold estates, which contain the majority of the dry sclerophyll forests in southeast Queensland.

Short-term wind forecasting for energy resources scheduling

This paper proposes a wind power forecasting methodology based on two methods: direct wind power forecasting and wind speed forecasting in the first phase followed by wind power forecasting using turbines characteristics and the aforementioned wind speed forecast. The proposed forecasting methodology aims to support the operation in the scope of the intraday resources scheduling model, namely with a time horizon of 5 minutes. This intraday model supports distribution network operators in the short-term scheduling problem, in the smart grid context. A case study using a real database of 12 months recorded from a Portuguese wind power farm was used. The results show that the straightforward methodology can be applied in the intraday model with high wind speed and wind power accuracy. The wind power forecast direct method shows better performance than wind power forecast using turbine characteristics and wind speed forecast obtained in first phase.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Energy resources scheduling in competitive environment

The increasing use of distributed generation units based on renewable energy sources, the consideration of demand-side management as a distributed resource, and the operation in the scope of competitive electricity markets have caused important changes in the way that power systems are operated. The new distributed resources require an entity (player) capable to make them able to participate in electricity markets. This entity has been known as Virtual Power Player (VPP). VPPs need to consider all the business opportunities available to their resources, considering all the relevant players, the market and/or other VPPs to accomplish their goals. This paper presents a methodology that considers all these opportunities to minimize the operation costs of a VPP. The method is applied to a distribution network managed by four independent VPPs with intensive use of distributed resources.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.