The purpose of this study is to identify realistic opportunities and barriers regarding PEV charge management by analyzing real-world PEV data from customers in the Austin Energy service area and evaluating direct, quantifiable economic value benefits as it relates new revenue, cost avoidance, CO2 reductions, and MW potential for peak shaving. The main objective is to provide business analysis to support the strategic road-map for Austin Energy PEV home charging programs. Three main charge program implementations are considered: Uncontrolled Charging, Time of Use Rates, and One Way Utility Control. The data used for the analysis includes 45 households with PEVs from Mueller area; 24 were under a Time of Use trial with pricing incentives to charge at night, and 21 receive normal Austin Energy rates. Data analysis shows that 66% of Time of Use trial group successfully shifted PEV load to Off Peak hours (10:00PM to 6:00AM). The potential of One Way control, based on load availability for interruption, shows that it will not be possible to implement until there are 37,000 PEVs in the Austin Energy area. Uncontrolled Charging represents a risk by increasing load during the residential peak. Time of Use Rates program will incentivize load shifting, reduce wholesale energy costs for Austin Energy while allowing customers to reduce their overall electricity bill. / text

Residential demand is a large and important factor of the utility load during the system peak period. And the control of residential demand can make a significant change to the system load of the utility. This research is designed to study the residential end-use appliances under various direct load control schemes. These appliances are water heaters, air conditioners, and space heaters which are the major electrical demand of the residential load. The study will apply the LOADSIM, an Electrical Power Research Institute (EPRI) load simulation program, to conduct load control strategies of these residential appliances. The LOADSIM program can be applied both for cycling and shedding control strategies during a specified control period. In this study, the cycling control is done on an air conditioner and space heater. The water heating control is performed under shedding strategy. The research has studied the appliance use of four house types under the same weather and control conditions. A total of 100,000 houses have been used in the study. These houses have the same dwelling and appliance characteristics but their house insulations are different. Diversity in house insulations gives different results in terms of load reduction and temperature change due to the load control. For example, a better-insulated house demands less electricity for its appliance than a low-insulated house. This study also uses the EPRl-LOADSIM program to estimate the load reduction and temperature change of each house type under the load control. / Master of Science

For the purpose of this study, data for low voltage distribution transformer loading in small communities in Maryland was collected from a local electric utility company. Specifically, analysis was done on three distribution transformers on their system. Each of these transformers serves at least one electric vehicle (EV) owner. Of the three transformers analyzed, Transformer 2 serves eight residential homes and has the highest risk of experiencing an overload if all customers purchase at least one EV. Transformer 2 has a nameplate rating of 25kVA (22.5kW assuming a 0.9 power factor). With one EV owner, Transformer 2 has a peak load of 46.82kW during the study period between August 4 and August 17, 2013. When seven additional EVs of different types were added in a simulated scenario, the peak load for Transformer 2 increased from 46.82kW to 89.76kW, which is outside the transformer thermal limit. With the implementation of TOU pricing, the peak load was reduced to 56.71kW from 89.76kW. By implementing a combination of TOU pricing and appliance cycling through demand side management (DSM), the peak load was further reduced to 52.27kW. / Master of Science

This thesis on the project Anti-age takes an interest in the passing of time, the different ways in which we have historically measured it and its respective effects on how we view the subject. Time as a theme came about from reading about the period prior to us having a wide availability to clocks. There is an old practise in Sweden were you sing a psalm when boiling an egg, as to keep time. The psalm in turn becomes a clock, a time-keeper. The abstractness of time takes another form.  Because of the climate crise which we start seeing unravel, this project turns its attention to objects which exist in the realm of the ordinary and therefore is invisible or uninteresting to us. Here, a regular tin can, the official office chair of Konstfack and a balcony table that we’ve seen one too many times are being turned into pre-historic clocks. With their rather unprecise measuring of time, the clocks designed in this project works as sort of vessels. The objects become a sundial, clepsydra and what we know to be the oldest clocks in the world. Sand, sun and shadow are visible units of time which remind us and grant acess to a sense of something bigger, other and further away from ourselves.

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / With the Smart Grid trend setting in, various techniques to make the existing grid smarter are being considered. The price of electricity is one of the major factors, which affects the electric utility as well as the numerous consumers connected to the grid. Therefore deciding the right price of electricity for the time of day would be an important decision to make. Consumers’ response to this change in price will impact peak demand as well as their own annual energy bill. Owning a small wind generator under the Critical Peak Pricing (CPP) and Time of Use (TOU) price-based demand response programs could be a viable option. Economic evaluation of owning a small wind generator under the two pricing schemes, namely Critical Peak Pricing (CPP) and Time of Use (TOU), is the main focus of this research. Analysis shows that adopting either of the pricing schemes will not change the annual energy bill for the consumer. Taking into account the installed cost of the turbine, it may not be significantly economical for a residential homeowner to own a small wind turbine with either of the pricing schemes in effect under the conditions assumed.

Thesis advisor: Scott Fulford / Can smart metering program and time-of-use (TOU) prices help reduce energy consumption in New York City? Being able to track electricity consumption levels and to modify consumer usage patterns are important for policy makers to efficiently manage the energy markets. Unfortunately, no reliable and up-to-date data have been brought to bear on this question. I study the effects of time-of-use (TOU) prices and smart metering for the residents of Shanghai and I investigate further what can policy makers do in order to adapt and transfer this successful DSM experience from Shanghai to the residential sector in New York City. The primary objective of my study is to characterize the realistic short-term and long-term potential for the smart metering program in New York City given my empirical findings that the smart metering program has had brought great benefits to the residents of Shanghai. People respond to incentives; if electricity is charged at different prices throughout a day, consumers are likely to shift their usage to when it is cheaper. My findings suggest that policy makers should think harder about designing a pricing scheme that can optimize the social plus. / Thesis (BA) — Boston College, 2011. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: College Honors Program. / Discipline: Economics Honors Program. / Discipline: Economics.

Transmission charges are levied against generators and suppliers for their use of transmission networks. The majority of existing transmission charging methods were designed for a system dominated by conventional and controllable generation. The resultant transmission charges reflect network users’ contribution to the system peak. The integration of renewable generation brings fundamental challenges in transmission planning and charging. Main criteria of transmission planning have changed from meeting system peak demand to the trade-offs between operational and investment costs. Transmission charging is required to effectively reflect these trade-offs. This research work aims to develop novel transmission charging methods for low carbon power systems, reflecting the contribution to transmission investments from different generation technologies, different locations, and critically different times. It firstly identifies the key drivers and key conditions of transmission investments under the economic criteria. In the second step, the key drivers and conditions are reflected in the developing of T-LRIC method, ToU-LRIC method and ToU-ICRP method. Major innovations of the proposed methods include 1. reflecting the trade-offs between operational and investments costs by employing investment time horizons to reflect the impacts of system operation on transmission investments (T-LRIC method and ToU-LRIC method). 2. differentiating various generation technologies by firstly quantifying their impacts on the time horizons of network investments, then translating these impacts to transmission charges (T-LRIC method and ToU-LRIC method). 3. providing time-specific transmission charges, in which Time-of-Use periods are identified by clustering time-series congestion costs or transmission charges, thus reflecting the typical conditions of system congestions and the required transmission investments (ToU-LRIC method and ToU-ICRP method). The main benefits from introducing these innovations are i) to guide the short-run behaviours of network users, thus mitigating transmission congestions and promoting efficient utilization of existing networks; ii) to incentivize appropriate generation expansion, thus reducing or deferring costly future transmission investments.

The current Internet architecture presents a barrier to accommodate the vigorous arising demand for deploying new network services and applications. The next-generation architecture views the network virtualization as the gateway to overcome this limitation. Network virtualization promises to run efficiently and securely multiple dedicated virtual networks (VNs) over a shared physical infrastructure. Each VN is tailored to host a unique application based on the user’s preferences. This thesis addresses the problem of the efficient embedding of multiple VNs onto a shared substrate network (SN). The contribution of this thesis are twofold: First, a novel hierarchical SN management framework is proposed that efficiently selects the optimum VN mapping scheme for the requested VN from more than one proposed VN mapping candidates obtained in parallel. In order to accommodate the arbitrary architecture of the VNs, the proposed scheme divides the VN request into smaller subgraphs, and individually maps them on the SN using a variation of the exact subgraph matching techniques. Second, the physical resources pricing policy is introduced that is based on time-ofuse, that reflects the effect of resource congestion introduced by VN users. The preferences of the VN users are first represented through corresponding demand-utility functions that quantify the sensitivity of the applications hosted by the VNs to resource consumption and time-of-use. A novel model of time-varying VNs is presented, where users are allowed to up- or down-scale the requested resources to continuously maximize their utility while minimizing the VNs embedding cost. In contrast to existing solutions, the proposed work does not impose any limitations on the size or topology of the VN requests. Instead, the search is customized according to the VN size and the associated utility. Extensive simulations are then conducted to demonstrate the improvement achieved through the proposed work in terms of network utilization, the ratio of accepted VN requests and the SP profits.

This dissertation proposed a new methodology for determining the optimal operating strategies for a chilled water storage system under a Time-of-Use electricity rate structure. It is based on a new classification of operating strategies and an investigation of multiple search paths. Each operating strategy consists of a control strategy and the maximum number of chillers running during the off-peak and on-peak periods. For each month, the strategy with the lowest monthly billing cost and minimal water level higher than the setpoint is selected as the optimal operating strategy for the current month. A system model is built to simulate the tank water level at the end of each time step and the system total power during each time step. This model includes six sub-models. Specifically, the plant model is a forward model using a wire-to-water concept to simulate the plant total power. For the Thermal Energy Storage (TES) model, the tank state is described with total chilled water volume in the tank and its derivation is the tank charging or discharging flow rate. A regression model is adopted to simulate the loop supply and return temperature difference as well as the loop total flow rate demand. In the control strategy sub-model, except for three conventional control strategies and the operation without TES, a new control strategy is advanced to load the chiller optimally. The final results will be a table showing the monthly control strategy and maximal number of chillers staged on during the off-peak and on-peak periods, an approach which is easy for the operators to follow. Two project applications of this methodology are introduced in this dissertation. One is an existing TES system with state-of-the-art control and metering systems. The monthly optimal operating strategies are generated, which will achieve significant savings. The comparisons among different control strategies are also provided. The other application consists of multiple plants with little data. The purpose of the study is to evaluate the economic feasibility of designing a new chilled water storage tank and sharing it among four plants. This problem can be solved with a simplified system model, and an optimal tank size is recommended.

The current Internet architecture presents a barrier to accommodate the vigorous arising demand for deploying new network services and applications. The next-generation architecture views the network virtualization as the gateway to overcome this limitation. Network virtualization promises to run efficiently and securely multiple dedicated virtual networks (VNs) over a shared physical infrastructure. Each VN is tailored to host a unique application based on the user’s preferences. This thesis addresses the problem of the efficient embedding of multiple VNs onto a shared substrate network (SN). The contribution of this thesis are twofold: First, a novel hierarchical SN management framework is proposed that efficiently selects the optimum VN mapping scheme for the requested VN from more than one proposed VN mapping candidates obtained in parallel. In order to accommodate the arbitrary architecture of the VNs, the proposed scheme divides the VN request into smaller subgraphs, and individually maps them on the SN using a variation of the exact subgraph matching techniques. Second, the physical resources pricing policy is introduced that is based on time-ofuse, that reflects the effect of resource congestion introduced by VN users. The preferences of the VN users are first represented through corresponding demand-utility functions that quantify the sensitivity of the applications hosted by the VNs to resource consumption and time-of-use. A novel model of time-varying VNs is presented, where users are allowed to up- or down-scale the requested resources to continuously maximize their utility while minimizing the VNs embedding cost. In contrast to existing solutions, the proposed work does not impose any limitations on the size or topology of the VN requests. Instead, the search is customized according to the VN size and the associated utility. Extensive simulations are then conducted to demonstrate the improvement achieved through the proposed work in terms of network utilization, the ratio of accepted VN requests and the SP profits.