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 Proposed for review 

Communications

What effects do communications systems have on the operations of smart grid technologies?

Communications Apps:

  1. Central control to device (load shed signal)
  2. Point to Point (end of line measurement to voltage regulator)
  3. End use to meter (Home EMS)
  4. Multipath communications (packet switching)

Communications Technologies:

  1. Power Line Carrier (inc TWACS)
  2. Radio (inc UHF, broadcast, dedicated, ad-hoc)
  3. Internet Cable (inc fiber optics)

Short description of purpose of Analysis:

  1. Understand impact of communications limitations and outages. Assume that a functioning comm system has no impact, but comm system failures and limnitations have adverse impact. What type of failures and limitations charaterize various comm schemes? What effect do these have?

Major Results of Analysis

  1. highlight inadequacy of some comm technology in some applications

Examine:

  1. Impact of Latencies on operations
  2. Impact of bandwidth limitations on operations
  3. Impacts of data loss on operations
  4. Interaction between data collection and data storage (centralized vs decentralized)
  5. Impacts of cyber security (encryption and authentication overhead)
  6. Impacts of privacy overhead.
  7. For these issues, look at power reliability, ability to do transactive control, revenue impact,feeder reconfig, voltage regulator, tap changer, more

Modeling Concepts

Communications Modeling Concept

The basic modeling approach is to model each network as a single "network" object that embeds the basic performance characteristics of a network, such as latency, reliability, and bandwidth limits. Each data path that must be handled is modeled as an "port" object whose parent is the network that handles its transport. This object describes where the data comes from, where it goes to, and how the transmission is triggered, e.g., on demand, on change, or at a regular interval. The size of the data packet is computed from the data item referenced, unless specified explicitly by the port object.

Example

A simple example

The follow example illustrates how to model the flow of data from a source object to a destination object where the source data is sent as soon as the data changes. 

class myclass {
  double item1;
  double item2;
  double item3;
  double item4;
  boolean send;
}
object myclass {
  name "Obj1";
  item1 0.5;
}
object myclass {
  name "Obj2";
}
object network {
  name Net1;
  latency 0;
  bandwidth 1 Mb/s;
  droprate 0.1%;

  // first example: transmission on change only
  object port {
    from Obj1.item1;
    to Obj2.item2;
    synctype DELTA;  // the data will transfer only when source data changes
  };

  // second example: transmission on send command only
  object port {
    from Obj1.item1;
    to Obj2.item3;
    synctype ASYNC;  // the data will transfer only when sendflag is true
    sendflag Obj1.send;  // reference to the sendflag at source
  };

  // third example: transmission on send command only
  object port {
    from Obj1.item1;
    to Obj2.item3;
    synctype ASYNC;  // the data will transfer only when sendflag is true
    sendflag Obj2.send;  // reference to the sendflag at destination
  };

  // fourth example: regular interval transmission
  object port {
    from Obj1.item1;
    to Obj2.item4;
    synctype CLOCK;  // the data will transfer periodically
    frequency 10s;   // the frequency of the update
  };
}

Using Demand Response to Offset Variable Generation

Short Description of Purpose of Analysis:

  1. Model a “whole” system from generation to transmission to distribution to load.
  2. Study the effectiveness of demand response in mitigating the effects of non-controllable generation.

Major Results of Analysis:

  1. Implement generator models that contain bidding models commonly used in transmission planning/operation (cost curves, PV buses, economic dispatch models, etc.).
  2. A good, general central plant model is needed.
  3. Do generators need a template model containing various aspects required – e.g. cost curves, market tie-ins, etc.
  4. There needs to be a mechanism for bidding generation (it may be piece-wise linear, cubic, etc.).
  5. External generator controls are required (AGC, etc.).
  6. An overarching generational dispatch or unit commitment object is required.
  7. How much detail is required to accurately represent a true operational system?

Effects of Control Strategies on Responsive Loads

Short Description of Purpose of Analysis

  1. What are the effects of different control strategies on responsive loads?
    1. Frequency
    2. Voltage
    3. Price
    4. Other regulatory signals
  2. How do these control strategies directly affect customers?
  3. How do these control strategies affect the demand (locally and regionally)?

Major Results of Analysis:

  1. What are the regionalized effects of control strategies?
    1. What level of granularity is desired?
    2. Multiple control signals should be applicable. Should there be a limit to the number of control signals available?
  2. For frequency responses, coupling with other software is desired (e.g. using another software platform for dynamic simulations, while GridLAB-D provides the load response).
  3. Loads other than residential homes are highly desired.
  4. Do loads need to be frequency dependent? To what level of detail should this be implemented?
  5. Is there a more user friendly way of implementing control algorithms with GridLAB-D?

Interaction of DR and Two Settlement Markets

Short Desc:

  1. How do LSE’s manage supply and demand portfolio when regulations differ?
    1. Risk Management for DG, PHEV, DR etc
    2. Role of AMI (Enabler), strategies for control?
  2. How does DR affect wholesale real time market operation, rules, monitoring etc
  3. How well does DR mitigate wholesale market power?
  4. How is DR affected by wholesale + retail prices?
    1. Take advantage of market opportunities
    2. Consequences of Active Market Participation

Major Analysis

  1. How do LSE’s manage supply and demand portfolio when regulations differ?
    1. Pro forma, Balance Sheet, Cost/Benefit Analysis, Profitability
    2. Portfolio Analysis Results, Risk Analysis
    3. Description of Strategy (Bidding, Retail Rate, Portfolio Management)
    4. Contract Portfolio Composition
    5. How does LSE manage risk of DG, DR, PHEV?
      1. Rate of return estimates/payback time
      2. Fraction change in reserve requirements for DR/DG/PHEV
    6. What is the role of AMI (Strategies for Control)?
      1. ?
  2. How does DR affect wholesale real time market operation, rules, monitoring etc
    1. Different between forecast and actual load
    2. Impact on reserve requirements of DR (Different base case and study)
  3. How well does DR mitigate wholesale market power?
    1. Supply profits (Base case/cost bid, study/strategy bid, with/without DR)
    2. Compare energy and reserve market power
  1. How is DR affected by wholesale and retail prices?
    1. Gross Revenues
    2. Net (per KWh) Energy Cost Change
    3. Counterfactual (Bid) demand
    4. Rebound Effects
    5. Overrides/Penalties
    6. Separate by load class
    7. Elasticity
    8. Saturation of DR Control/Overloads/Stability
    9. Evaluate Surplus (change, total?)
    10. Change in rate of control (cycling rate)
    11. Lag between price and control action
    1. Take advantage of market opportunities
      1. Load Shift
      2. Preheat/cool
      3. Charge/Discharge
      4. Storage

Quantify the above

    1. Consequences of Active Market Participation
      1. Consumer Fatigue
      2. Consumer Resistance
      3. Attrition
      4. Impact on suppliers(reliability, repair costs, availability)s

Agent based Transient and Power Quality Analysis

Short Desc:

  1. Design of power electronic controllers
  2. Effect of power electronic controllers
    1. What Types?
    2. What does it do?
  3. Fault Analysis
  4. Full Transient Stability Analysis
  5. Full EM Transient Analysis

Major Analysis

  1. Design of Power electronic Controllers
    1. DC to DC convertor models
    2. AC to DC convertor models
    3. They can be frequency dependent models
    4. Harmonic distortion on the system caused by the devices
  2. Effect of power electronic controllers

Same as 1.

  1. Fault Analysis
    1. Fault Currents
    2. Relay Response, Breaker response, all protection equipment response
    3. Component responses to system faults (like distributed resource response and demand response) to system faults
  1. Full Transient Stability Analysis
    1. System Inertia Modeling (generators, motors etc)
    2. Order of millisecond analysis (voltage response, inertial swing equation)
    3. Generator dynamic modeling (exciters, governors, PSS etc)
  1. Full EM Transient analysis
    1. Effect of lightning
    2. PSpice, EMTP

Aggregate Demand Response Modeling

  1. Capture composite load behavior in a single agent, including
    1. Natural behavior (e.g., thermal cycle)
    2. Demand variation (e.g., enduse, daytype, hour)
    3. Curtailment signals (e.g., direct load control, duty cycle control, thermostat reset)
  2. Time-independent solution
    1. Equilibrium initial conditions
    2. Forecasting and glance-ahead
  3. Time-dependent solution
    1. Fixed internal time-step
    2. Separate model data for each end-use
  4. Model inputs
    1. Thermal rates (e.g., duty cycle if any)
    2. Control band (e.g., thermostat)
    3. Load fractions (ZIP)
  5. Model variables
    1. Demand and curtailment
    2. Thermostat reset
  6. Model outputs
    1. Effective duty-cycle

Appliance Control Models

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