Integrating Distributed or Renewable Resources Minitrack

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The capabilities and characteristics of innovative supply-side and demand-side technologies in the electric power industry, as well as power system operations, planning and markets are evolving rapidly. Efficient integration of distributed, variable and uncertain system resources with portfolios of existing resources requires evolution in planning, operational and control strategies. Policies and market structures must also continue to advance. This mini-track invites papers that address modeling, simulation and hardware developments, as well as economic analyses (such as market or rate design), system analyses and case studies, relating to planning, operations and control of distributed and renewable resources in electric power systems.


Minitrack Chair:

Judy Cardell
Smith College
Email: jcardell@smith.edu


Session 1: Renewables and Distributed Energy Resources
Session Organizer and Chair: Charlie Smith, Charlie@variablegen.org

Electricity market restructuring, advances in energy generation technology and agreements on the reduction of global greenhouse gas emissions have paved the way for a large increase in the use of renewable generation connected at both the transmission and distribution level. With wind generation currently having the largest share of the new capacity, and solar generation having the highest rate of growth, this trend is expected to continue to produce an increasing amount of variability and uncertainty in system generation portfolios. A broad array of issues associated with the incorporation of large shares of variable generation (VG) into power system planning, design, and operation, including market operation, needs to be considered.

This session invites technical papers addressing new approaches, models and methods for the planning, design and operation of power systems with large or increasing shares of VG. A focus on the key issues of managing increased levels of variability and uncertainty on both the transmission and distribution system with new approaches to increasing system flexibility and incorporating VG plant output forecasting on all time scales, is encouraged. Integration of renewable resources will also require continuing innovation in technology capability to enable the participation of variable generation in AGC systems, ancillary service markets and distribution system management. New approaches to the evolution of the wind and photovoltaic plant design to enable this participation are necessary. This session will address some of the challenges and approaches to achieve these goals.


Session 2: Demand Response, Microgrids, and Storage
Session Organizer and Chair: Ward Jewell, ward.jewell@wichita.edu

Distributed energy resources (DERs) include customer-side generation, energy storage, flexible loads, and distribution-side sensing devices, and may or may not have coordinated operation as microgrids. There is an emerging consensus that DERs will play a critical role in providing services to the power system. Flexible loads can be scheduled to balance variable generation, microgrids and strategic storage can provide reliability and security and distributed sensing can offer unprecedented system visibility. Integration of DERs requires continuing innovation in control, optimization, and modeling, and technology to enable the participation in regulation and balancing services, ancillary service markets and distribution system management.

This session invites technical papers presenting new approaches, models and methods for planning, architecting, and operating interconnected power systems with significant DER penetration. We are especially interested in papers that focus on the role of DERs in responding to variability and uncertainty on both the transmission and distribution systems, as well as papers that study the economic aspects of integrating DERs.

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Recent Submissions

Now showing 1 - 5 of 9
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    The Impact of Distributed Energy Resources on the Bulk Power System: A Deeper Dive
    ( 2017-01-04) Birk, Michael ; Tabors, Richard
    solar photovoltaics (PV), electric storage and electric \ vehicles, demand response, combined heat and \ power, wind, fuel cells, and micro-turbines are \ typically installed on the low or medium voltage \ distribution network. Changes on the distribution \ network can have rippling effects throughout the rest \ of the power system. In this paper, we have \ calculated both traditional locational marginal \ prices (LMPs) and distributed locational marginal \ prices (DLMPs) using an optimal power flow (DC \ OPF). This paper provides an analysis of the energy \ price impacts resulting from significant additions of \ Distributed Energy Resources (DER), namely solar \ PV, electric batteries and demand response, in a \ distribution feeder. The impact is measured in terms \ of nodal approximations to DLMPs, realistic \ calculation of LMPs in the transmission system and \ overall price suppression effects that trickle down to \ consumers on the feeder. Policy implications are \ drawn concerning the potential impacts of \ penetration of DER on future planning, and \ operation of the power system as well as on energy \ markets and the environment.
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    Optimal Electricity Pricing for Societal Infrastructure Systems
    ( 2017-01-04) Alizadeh, Mahnoosh ; Wai, Hoi-to ; Goldsmith, Andrea ; Scaglione, Anna
    We develop a general framework for pricing electricity in order to optimally manage the electricity load of societal infrastructures that interact with power systems through their price-responsive electricity load. In such infrastructure systems, electricity is not the sole resource needed to serve users' needs. Examples include cloud computing infrastructure or electric transportation networks. In these cases, other shared networked resources such as charging stations or communication links and data centers are also required to serve users. Hence, pricing of electricity becomes intertwined to managing other congestible resources not priced by the power system operator, leading to a complex economic dispatch problem. For brevity of notation, our analysis is performed under a static setting. We discuss how the power system operator should model the effects of the mobility of loads and congestion in the infrastructure in the economic dispatch. We numerically study the performance of our algorithms using the example of a simple electric transportation network.
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    Learning to Shift Thermostatically Controlled Loads
    ( 2017-01-04) Lesage-Landry, Antoine ; Taylor, Joshua A.
    Demand response is a key mechanism for accommodating renewable power in the electric grid. Models of loads in demand response programs are typically assumed to be known a priori, leaving the load aggregator the task of choosing the best command. However, accurate load models are often hard to obtain. To address this problem, we propose an online learning algorithm that performs demand response while learning the model of an aggregation of thermostatically controlled loads. Specifically, we combine an adversarial multi-armed bandit framework with a standard formulation of load-shifting. We develop an Exp3-like algorithm to solve the learning problems. Numerical examples based on Ontario load data confirm that the algorithm achieves sub-linear regret and performs within 1% of the ideal case when the load is perfectly known. \
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    Impact of Uncertainty on Wind Power Curtailment Estimation
    ( 2017-01-04) Dillon, Joseph ; O'Malley, Mark
    Ireland and other countries in the EU have binding targets for production of energy from renewable sources by 2020. Ireland’s Renewable Energy Action Plan aims to meet this target by producing 40% of electrical energy from renewable sources and most of this will come from wind power. In order to forecast the amount of wind power capacity required, it is necessary to forecast the amount of wind power curtailment that will arise from the need to maintain a certain amount of conventional generation online to provide system services such as reserve, inertia and system balance. Estimation of future levels of wind power curtailment is also necessary for investors. In this paper, a stochastic scheduling model is used to study the impact of forecast error related uncertainty on wind power curtailment estimation. Results are shown illustrating the impact of uncertainty on final energy production from wind power and the impact improvements in forecasting could have on these estimates.
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    Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems
    ( 2017-01-04) Kim, Insu ; Begovic, Miroslav M. ; Vidakovic, Branislav ; Djuric, Petar ; Jeremic, Vladimir
    When viewed in hourly intervals, a solar photovoltaic (PV) system appears to have a more stable output than usual. However, there are short-term rapid variations in its generation output that result from transient cloudiness and weather disturbances in the atmosphere. By using Monte Carlo simulations applied to a Markov model, this study demonstrates the short-term intermittency of the transient weather conditions and estimates the generation of geographically dispersed PV systems with a capacity of ten percent of peak demand of a statewide grid in one-minute intervals. This study found that geographically distributed PV systems evaluated in one-minute intervals could cope with peaks of a statewide power grid because of the smoothing effect caused by the geographical spread. The purpose of the exercise is to create a framework for integration and optimization of multiple generation sources in order to meet the uncertainty of the fast changing PV output under certain weather conditions. \