Multi-objective optimisation of community battery energy storage capacity exploitation
Alizadeh, Marjan (2017)
Diplomityö
Alizadeh, Marjan
2017
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2017121255754
https://urn.fi/URN:NBN:fi-fe2017121255754
Tiivistelmä
Utilizing battery energy storage systems (BESS) in power systems can elevate the efficiency, reliability, stability and security of the system, and simultaneously can provide economic benefits for the battery operator. Profitability of allocating battery capacity to different electricity markets is a critical factor which should be evaluated precisely. Determining of the optimal battery capacity via an optimal bidding strategy for allocation to different electricity markets in Finland, i.e. Nord Pool day-ahead and intra-day markets and Fingrid frequency containment reserve markets is investigated in this thesis.
The bidding model for the Nord Pool day-ahead and intra-day markets are developed as a stochastic profit maximization model. The optimization problem is formulated with the objective of maximizing the total expected value of battery system’s profit subjected to various technical linear and non-linear constraints. Two Matlab® optimization algorithms are examined to solve the optimization problem effectively: interior-point algorithm and genetic algorithm. The optimization results indicate that employing the battery system in Elspot day-ahead and Elbas intraday markets is not profitable for battery owner due to high amount of battery costs.
The capacity allocation of battery system to Fingrid frequency containment reserve markets for normal operation (FCR-N) and disturbances (FCR-D) are studied by applying two methods: optimization method and fixed power method. In the optimization method, an optimal model for battery system is formulated and solved by Matlab®. The purpose of optimization is to maximize the profit with observing the market prices, battery costs, technical constraints of battery system and requirements of market. The optimization results show that the battery system is profitable in both FCR-N and FCR-D markets. In the fixed-power method a constant amount of battery power is supposed to be dedicated to Fingrid frequency markets for all hours of the day. The results of applying fixed-power method show that utilizing the battery system in FCR-N market is not profitable due to the high amount of battery costs and the penalty that should be paid to Fingrid for the hours that the declared power could not be provided to market. On the other hand, the results of applying this method show that utilizing the battery system in FCR-D market is profitable with considering the battery costs and penalty payments. The results are based on the frequency data of May 2016.
The bidding model for the Nord Pool day-ahead and intra-day markets are developed as a stochastic profit maximization model. The optimization problem is formulated with the objective of maximizing the total expected value of battery system’s profit subjected to various technical linear and non-linear constraints. Two Matlab® optimization algorithms are examined to solve the optimization problem effectively: interior-point algorithm and genetic algorithm. The optimization results indicate that employing the battery system in Elspot day-ahead and Elbas intraday markets is not profitable for battery owner due to high amount of battery costs.
The capacity allocation of battery system to Fingrid frequency containment reserve markets for normal operation (FCR-N) and disturbances (FCR-D) are studied by applying two methods: optimization method and fixed power method. In the optimization method, an optimal model for battery system is formulated and solved by Matlab®. The purpose of optimization is to maximize the profit with observing the market prices, battery costs, technical constraints of battery system and requirements of market. The optimization results show that the battery system is profitable in both FCR-N and FCR-D markets. In the fixed-power method a constant amount of battery power is supposed to be dedicated to Fingrid frequency markets for all hours of the day. The results of applying fixed-power method show that utilizing the battery system in FCR-N market is not profitable due to the high amount of battery costs and the penalty that should be paid to Fingrid for the hours that the declared power could not be provided to market. On the other hand, the results of applying this method show that utilizing the battery system in FCR-D market is profitable with considering the battery costs and penalty payments. The results are based on the frequency data of May 2016.