GENCO-Investment-Strategies-by-Simulation-for-Demand-Side-Role-for-Investments-and-Capacity-Adequacy
Project Article here: https://portfolio.katiegirl.net/2018/08/07/genco-investment-strategies-by-simulation/
This project will present an applied and game-like approach to simulating the load growth, investment decisions by two types of generation technologies, demand-price responsiveness, and reliability, of a test-case power system. The simulation begins as a 9-bus system with existing generation (3 generators) and transmission lines (8 lines). System topology can be viewed in a figure throughout the game with the yearly generation and load at each bus. In addition, dynamic color-coding is used to highlight transmission lines that exceed MVA ratings and highlight bus voltages that violate any limits. The winning objective of the player company (you) is to maximize his profit. Reliability can be tracked by viewing the N-1 generator and line contingencies every year, but this does not influence profits. There are two generation technologies used: coal and gas turbine. Each technology will have a similar competitor in the simulation. The competitor can bring down the market price and reduce the player’s profits significantly. The clock starts at T=0 in the investment game with a historical record of past prices and projected prices based on lack of investment. As time moves forward in yearly increments, the load, prices, investment costs, and other variables are adjusted to that of the player’s performance. The player has the opportunity to study various profitable and unprofitable investment alternatives each year of the simulation. If he invests at the right location, and in the right planning year, his company can make windfall profits. Competitors randomly participate in adding extra generation in random areas of the system based on the competition level settings. The challenge for the user is to study the effects of his investment decisions on market prices, reliability, and his profitability.
Overview of Project
Power system reliability, at the transmission level, combined with unit commitment optimal power flow, have been common topics in many of my graduate courses. However, economics and present value analysis studied in this course have opened a new perspective into the past, present, and future infrastructure of the electric grid. My project goal was to combine these three perspectives and to see the effects that individual investors may have on prices, scarcity, reliability, and demand-response. I spent several weeks developing a sophisticated C-based program in MATLAB to simulate investments, competition, load growth, price response, optimal investment strategies, reliability, and profit analysis all based on user direction. The user of course, is you, or anyone who so desires to execute the program. Based on initial settings, many of which can be changed by a simple submenu, the program progresses through a certain period of planning years. During the simulation, the user is given load and price forecasts along with a detailed analysis of investment alternatives. Reliability can be tracked via the contingency analysis option. There will be two main decisions the player (user) can make every year through each time period: invest in new generation, or do not invest in new generation. Competitors, which can be customized in the settings submenu, may invest in new generation decreasing the price forecasts and your profits. The objective for the company players is to, of course, maximize profits. However, if an investment decision is precarious, the player risks losing millions of dollars.
The paper will discuss the simulation process and program functions in detail. High-level flow charts along with pseudo code and tables, will explain the program components. An example simulation will then be presented to illustrate the simulation process. A few different scenarios based on customized settings in the submenus will be presented along with summaries. Applicable uses, enhancements, and other possible program functions will be discussed. Lastly, some concluding remarks will summarize the project work. Appendices contain all applicable code.
Requirements
To run the Power Sim Investment program correctly the following are required:
• MATLAB Student Version v13 or greater (developed on v14) • Optimization Toolbox • Matpower • Computer running at least 512 MB RAM (1 GB recommended)
To install the program, create a directory in your MATLAB workspace directory called “PowerSimInvestor”. Copy and paste the project files to this directory. Open the MATLAB program and set a path to the “PowerSimInvestor” folder.
On the command prompt type “mainmenu” >>mainmenu
If MATLAB fails to recognize this command, you need to review installation and documentation for further assistance
PowerSim.zip contains all the files
V. Conclusions
The power simulation project was definitely a challenge to achieve and took many days of development and testing. The results have been a success to the purpose of the project: to study the effects of investments, demand-price responsiveness, competition, and reliability in a power system. A small 9-bus system with 8 transmission lines was choosen as the test case. The program can further be modified to include a larger system. Furthermore, the program could also be upgraded to allow investments on new transmission lines in the system.
Two types of generation technologies were considered: coal steam and gas turbine. The user can choose the type of technology to study investments. The competitor in the simulation is always of the same type of the generation technology being studied. Coal steam plant investments were priced the same as existing generation in the system, whereas gas turbine was expensive and took years to reach a profitable investment. Coal steam technologies faired more amiable investment alternatives, however, the gas turbines allowed more possible windfalls in profits if the market prices were increased high enough.
Load on the system was modeled as the total demand. Supply was modeled as the total capacity of all the generation in the system. Scarcity, the ratio of demand and supply, determined market prices. If there was excess generation in the system, the market price would trend downward, and vice versa. However, the demand did not reduce in response to high prices, which could be an enhancement for the program. Load increased every year as a percentage of the load growth level setting (default low) applied at the beginning of the simulation. The load growth was distributed randomly to each bus throughout the system. Each bus contained a random load growth amount in each simulation year and a forecast of future load growth.
Investment alternatives were analyzed and printed to the simulation per the user’s request. Each alternative considered adding a generator at a specific bus, the future load forecasts, the future optimal power flow based on the new load, and calculated yearly revenue for the investment alternative. This analysis, without consideration of competition, educated the user of possibile short-term profits, loses, and present value analysis.
Different scenarios have been applied to study varying load, competition, and investment on the system. Some conclusions have been made regarding the energy-only market system studied in the simulation. Under a highly competitive environment, market prices decrease towards marginal costs. Whereas in a less competitive system, investor market power becomes apparent in the increases in market prices, and windwall profits for the investor. A balance and diversity of generation is needed to keep market prices sensible and offer a reasonable return of investment (profit) for the investors involved in providing the energy for this electric power system. Furthermore, the decentralized generation planning studied in this simulation was inefficient for supplying energy to meet the demand.