Simulation and comparison of pricing strategies for electricity markets

• Main Author: Goh, Yu Xuan
• Other Authors: Hu Guoqiang
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering; DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/75360
• Institution: Nanyang Technological University

In this paper, I compare the traditional fixed pricing strategy with dynamic pricing strategy, which arose from the introduction of Smart Grids. This involves the simulation of the different pricing models under the strategies - for fixed pricing strategy: Flat-rate pricing model; for dynamic pricing strategy: Time-of-use pricing model and real-time pricing model. A power system, which consists of several power consumers and a power provider is considered. Each consumer has an electricity consumption controller (ECC) unit in their smart meter. This allows a two-way communication between consumers and the provider through the transmission of data stored in the smart meter. By referencing the existing algorithms from previous studies, coupled with using particle swarm optimization (PSO) to produce optimal decision variables, thus allowing instantaneous matching of supply and demand of electricity, I simulate the optimal consumption levels for each consumer. The simulation results are then obtained and the effectiveness of each pricing strategy is observed and compared. Simulation results confirm that Real-Time pricing is the most optimal pricing model among the three as it generates a price based on the consumption level in real time. This allows consumers to adapt by changing their consumption as price changes, thus improving the utility of electricity. This reduces costs for the producers, and at the same time increases the welfare of the consumers, thus maximizing the aggregate welfare of all stakeholders.