A Combined Equivalenced-Electric, Economic, and Market Representation of the Northeastern Power Coordinating Council U.S. Electric Power System

Allen, Eric; Lang, Jeffrey H.; Ilić, Marija

doi:10.1109/tpwrs.2008.926715

Cited by 52 publications

(26 citation statements)

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“…The electric transmission portion of the test system is taken directly from the 36-bus NPCC model in [21], with a few modifications. At this stage of model development, our power grid model is a pure AC system, so DC elements in the 36-bus NPCC model are ignored.…”

Section: Test System Descriptionsmentioning

confidence: 99%

“…At this stage of model development, our power grid model is a pure AC system, so DC elements in the 36-bus NPCC model are ignored. Rather than utilizing the locational price (bid) data provided in [21], we utilize marginal costs for coal, nuclear, hydro, wind, oil and refuse generation as reported in [22]. Our marginal cost figures for gas-fired power plants utilize average wintertime natural gas prices paid by power plants, as reported to the U.S. Energy Information Administration, for the states covered by our test system (Pennsylvania, New Jersey, New York and the six New England States).…”

Section: Test System Descriptionsmentioning

confidence: 99%

See 1 more Smart Citation

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Sánchez

Bent

Backhaus

et al. 2016

2016 49th Hawaii International Conference on System Sciences (HICSS)

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Section: Test System Descriptionsmentioning

confidence: 99%

Section: Test System Descriptionsmentioning

confidence: 99%

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Sánchez

Bent

Backhaus

et al. 2016

2016 49th Hawaii International Conference on System Sciences (HICSS)

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“…Within the U.S. portion of the NPCC system, several utilities are regulated by one State (in NY), while in the other parts of NPCC system (NE) individual utilities are regulated by the separate State regulators. Shown in Figure 1 is the one-line diagram of the equivalent NPCC system described in [8]. The buses in the reduced model are individually selected to provide a good representation of the Northeastern US bulk electric power system, particularly in New York and to a lesser extent in New England, while limiting the size of the model to 40 buses or less.…”

Section: Maxmentioning

confidence: 99%

“…The power flow solution for the NPCC system described in [8] is used as the starting point around which short-term reliability studies are carried out. This solution has short-term reliability in the sense that it satisfies all equality and inequality constraints (1)- (9) when the load demand pattern is as given (normal), and all equipment components are functional.…”

Section: Contingency Analysis Of the Npcc Equivalent Systemmentioning

confidence: 99%

“…Therefore, there is no need to modify the line flow limits (5) for purposes of ensuring that the network as a whole is reliable for the given supply/demand pattern. It can be seen in the NPCC system data provided in [8] 8 However, in order to ensure that the system would meet the (N − 1) and (N − 2) reliability criteria, it is necessary to assess the system response to taking out equipment of interest and determining the most critical failures.…”

Section: Contingency Analysis Of the Npcc Equivalent Systemmentioning

confidence: 99%

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The role of numerical tools in maintaining reliability during economic transfers An illustration using the NPCC equivalent system model

Ilić

Lang

Allen

2007

2007 iREP Symposium - Bulk Power System Dynamics and Control - VII. Revitalizing Operational Reliability

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In this paper we are concerned with the increased complexity facing operators when monitoring and scheduling available resources needed to serve customers without interruptions and at the reasonable costs. Historically, this task has been met by combining human expert knowledge about the specifics of the system with the results obtained by approximate numerical tools for near real-time analysis and assessment of system conditions. The emphasis in this paper is on demonstrating fundamental limits to relying on human decision making due to a highly combinatorial nature and complexity of managing reliability and economics of electricity services in today's nonlinear electric power network systems. This complexity calls for development of more accurate and quantifiable numerical methods for decision making in such systems. We illustrate the type of nearreal time numerical tools essential for implementing such decisions. A comparison of the NPCC system utilization by means of current and future numerical tools is presented.

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Using deferrable demand in a smart grid to reduce the cost of electricity for customers

Jeon

Lamadrid

et al. 2015

J Regul Econ

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The primary purpose of this paper is to evaluate the benefits of distributed storage capacity in the form of deferrable demand managed centrally by a system operator, and in particular, to determine the savings in the total annual cost of supplying electricity for a system that has a substantial amount of variable generation from wind turbines. Since the objective of a centrally controlled system is to minimize the expected daily operating costs subject to the availability of generating units and storage capacity, the basic economic question is whether the savings in the annual system cost of supply, including the capital cost of installed generating capacity, can offset the capital cost of installing deferrable demand capacity. The analysis uses a new multi-period model of a power grid that treats stochastic generation explicitly and determines the optimum hourly commitment of conventional generators and the charging/discharging of deferrable demand needed to maintain the reliability of supply. A simulation example shows that deferrable demand can reduce system costs by (1) shifting demand from expensive peak periods to less expensive off-peak periods, (2) providing ramping services to mitigate the variability of wind generation, and (3) 123 W. Jeon et al.reducing the amount of installed peaking capacity needed for System Adequacy and the associated capital costs. If customers pay rates for electricity that reflect the true system costs of supplying their patterns of purchases from the grid, customers with deferrable demand will pay lower bills for electricity and their savings will be substantially more than the cost of installing deferrable demand devices. The results also show that if customers pay typical flat rates for electric energy, the economic incentives for installing deferrable demand are perverse.

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A Combined Equivalenced-Electric, Economic, and Market Representation of the Northeastern Power Coordinating Council U.S. Electric Power System

Cited by 52 publications

References 0 publications

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

The role of numerical tools in maintaining reliability during economic transfers An illustration using the NPCC equivalent system model

Using deferrable demand in a smart grid to reduce the cost of electricity for customers

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