ELEN5015A - Transmission Systems Study Notes
UNIVERSITY OF THE WITWATERSRAND SCHOOL OF ELECTRICAL AND INFORMATION ENGINEERING
ELEN5015A - Transmission Systems Notes
CHAPTER 1: CONCEPTS OF POWER SYSTEM ECONOMICS
1.1. Introduction
Vertically integrated utilities perform all three functions of generation, transmission, and distribution.
Tariffs are highly regulated to minimize the cost of electricity to end-users while allowing utilities to recover costs.
Restructuring typically involves separating the functions into three entities (often as independent subsidiaries under a holding company).
Generators operate independently of transmission and distribution entities in a competitive market, selling power wholesale at market-determined prices.
Independent Power Producers (IPPs) compete with traditional generators.
Transmission often remains regulated under a single System Operator (SO), which also manages the electricity market (sometimes called the Independent System and Market Operator (ISMO)).
Operating costs of the transmission system are transmitted to both generators and distribution companies, which are then passed on to end-users.
Distribution companies are responsible for selling power to end-users, acquiring it wholesale from the market managed by the SO.
1.2. Categories of Electricity Markets
The four electricity (physical) auction markets:
Day-ahead Market: At noon on the previous day, generation is procured for each hour of the next day (Dispatch Day) based on estimated demand.
Short-term Market (optional): Changes are made during Dispatch Day to generation procurement for remaining hours if significant demand changes occur.
Hour-ahead Market (real-time): Adjustments for the next hour are made during Dispatch Day for significant demand changes.
Ancillary Services Market: Additional generation procurement for each hour of the following day (similar timing as Day-ahead).
Generator preferences favor long-term price certainty through financial bilateral contracts (between seller and SO).
1.3. Concept of the Load Duration Curve (LDC)
The Load Duration Curve (LDC) is an essential tool for planning generation.
Financial Trading Arrangements
Bilateral Contracts (e.g., PPAs): Ongoing energy transactions between each generator and the SO.
Futures and Options (derivatives): Used to manage risk associated with energy trading.
Physical Trading Arrangements
Bilateral Contracts (PPAs): Used for ongoing energy and ancillary services transactions.
Market Structures:
DA (Day-Ahead) Market: Energy and ancillary services scheduling.
ST (Short-Term) Market: Energy transactions based on changes to DA contracts.
Load Forecasting:
Requires a day-ahead load forecast.
On-the-day constraints and forecasts must also be accounted for.
Capacity Classification
Load shedding as a demand-side measure, classified as:
Peaking capacity
Mid-merit capacity
Baseload capacity
LDC Graph: Describes the number of hours that various capacities exceed specific load levels.
1.4. Concept of the Marginal Cost of Generation
Cost Structure:
Fixed Costs: Costs independent of energy produced (e.g., capital costs for constructing power stations).
Variable Costs: Costs dependent on energy produced (e.g., fuel costs).
Short-run Marginal Cost ($R/MWh$): Calculated as follows:
ext{Short-run Marginal Cost} = ext{Marginal Cost of Fuel} + ext{Variable O&M Costs}
Fixed costs are substantial for nuclear energy compared to variable costs; for renewable options like solar or wind, fuel costs are zero, leading to operational marginal costs being primarily from O&M.
Capacity Categories
Mid-merit Capacity: Medium-level capital and fuel costs.
Baseload Capacity: High annualized capital costs but low fuel costs.
Peaking Capacity: Low capital costs but high fuel costs.
1.5. Concept of Economic Dispatch - Traditional Approach without Electricity Market
Definition: Economic dispatch refers to selecting which generators to utilize to meet electricity demand, contrasting with scheduling.
Objective Function: The goal is to minimize costs, expressed mathematically:
ext{Minimize } f(P) = ext{Cost}(C)
Variables:
Where:
$ ext{Power produced by unit i during period t}$
$ ext{Cost of generation for unit i}$
$ ext{Market Clearing Price (MCP)}$ when an electricity market is present.
Constraints for Optimization
Generation-load-balance constraint: Total power produced must equal total load consumption at all periods $t$.
Generator power range constraints: Each generator's operation must remain within its allowable limits across all periods.
Generator ramp rate constraints: Each generator’s output must not exceed its ramping capability.
Minimum uptime constraints: Generators should not be shut down unless their minimum uptime has been satisfied across periods.
Minimum downtime constraints: Each generator can only start after being down for the minimum downtime.
1.6. Economic Dispatch with Electricity Market – No Transmission Congestion
Merit Order Supply Stack: Used for dispatching based on cumulative generator capacity and ascending short-run marginal costs.
Market Equilibrium Point (MEP): Identified where the Merit Order Supply Stack intersects aggregate demand; the price at this point is the Market Clearing Price (MCP).
Uniform Pricing: All generators receive and pay the MCP; inframarginal generators recover capital costs while marginal generators do not.
1.7. Economic Dispatch with Electricity Market – With Transmission Congestion
Transmission Congestion: Occurs when transmission lines lack capacity to carry required electricity.
Locational Marginal Price (LMP): Each node has its own LMP impacted by supply stack, requiring potential dispatch of more costly generators at nodes due to congestion.
Hedging Risks:
Temporal Risk: Managed through Contracts for Difference (CfDs) which stabilize generator earnings to the average strike prices.
Locational Risk: Managed through Financial Transmission Rights (FTRs); suppliers compensated if energy prices vary significantly across nodes.
By using appropriate combinations of CfDs and FTRs, generators can hedge against both temporal and locational risks effectively.
Perfect Hedge Scenario: Achieved when quantities of CfD and FTR match energy supplied and consumed at different nodes, stabilizing prices against fluctuations.