Energy Management in UK Non-Domestic Buildings - a New Perspective to Provoke Reduced Carbon Emissions

Politicians, industry and the public generally accept the need for energy consumption to be cut to deliver climate change mitigation measures essential for us to avoid climate disaster. For non-domestic fuel users current energy policy has attempted to drive this through rational economic responses to energy cost pressures. This reliance on voluntary action has created an “Energy Inconsistency”, that is a marked difference between energy opportunities that have been proven technically viable, financially rational and retrofit feasible and those actually adopted. Other factors must therefore be involved to influence what appear to be simple carbon and cost saving opportunities. This paper presents a new approach to energy efficiency and consumption in non-domestic buildings, viewing attitudes and behaviours of building owners and users as the key driver of energy consumption. A new framework is proposed as a method to examine the impact of building ownership on the users’ and owners’ abilities to improve energy efficiency and consumption and identify opportunities to overcome the barriers inherent in these ownership structures.

Dynamic cost indexing

This paper describes the development of a generic tool for dynamic cost indexing (DCI), which encompasses the ability to manage flight delay costs on a dynamic basis, trading accelerated fuel burn against ‘cost of time’. Many airlines have significant barriers to identifying which costs should be included in ‘cost of time’ calculations and how to quantify them. The need is highlighted to integrate historical passenger delay and policy data with real-time passenger connections data. The absence of industry standards for defining and interfacing necessary tools is recognised. Delay recovery decision windows and ATC cooperation are key constraints. DCI tools could also be used in the pre-departure phase, and may offer environmental decision support functionality: which could be used as a differentiating technology required for access to designated, future ‘green’ airspace. Short-term opportunities for saving fuel and/or reducing emissions are also identified.

Dynamic cost indexing: cost estimations and building the prototype

The design of a decision-support prototype tool for managing flight delay costs in the pre-departure and airborne phases of a flight is described. The tool trades accelerated fuel burn and emissions charges against 'cost of time'. Costs for all major 'cost of time' components, by three cost scenarios, twelve aircraft types and by magnitude of delay are derived. Short-term opportunities for saving fuel and/or reducing environmental impacts are identified. A shift in ATM from managing delay minutes to delay cost is also supported.

Site level cost benefit analysis of renewable energy in the near-shore environment

Senior thesis written for Oceanography 445

Does Cost-Effectiveness Analysis Have a Role in US Managed Care Drug Formularies? An Empirical Study of Utilization, Costs, Outcomes, and Elasticity of Demand of a Value-Based Formulary

Thesis (Ph.D.)--University of Washington, 2015

Evaluation and Potential Cost-Effectiveness of Active Surveillance Pharmacovigilance for First-Line HAART in Namibia

Thesis (Ph.D.)--University of Washington, 2016-02

Marginal Activity Access Cost (MAAC): a new indicator for sustainable Land Use/Transport (LUT) planning

The paper presents the ‘Marginal Activity Access Cost’, an accessibility indicator providing estimation in monetary terms of the impacts on mobility and on the environment of locating a single new activity in a specific zone of the urban area. In the first part of this paper, the new indicator is presented and compared to other accessibility indicators proposed in literature. In the second part, the MAAC is validated through an application to the urban area of Rome. The paper concludes with brief remarks on using the proposed accessibility indicator as index of performance for sustainable spatial planning.

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Transmission cost allocation using cooperative game theory: a comparative study

In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

A lightweight indoor localization model based on motley-keenan and COST

This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.

On international cost-sharing of pharmaceutical R&D

Ramsey pricing has been proposed in the pharmaceutical industry as a principle to price discriminate among markets while allowing to recover the (fixed) R&D cost. However, such analyses neglect the presence of insurance or the fund raising costs for most of drug reimbursement. By incorporating these new elements, we aim at providing some building blocks towards an economic theory incorporating Ramsey pricing and insurance coverage. We show how coinsurance affects the optimal prices to pay for the R&D investment. We also show that under certain conditions, there is no strategic incentive by governments to set coinsurance rates in order to shift the financial burden of R&D. This will have important implications to the application of Ramsey pricing principles to pharmaceutical products across countries.