REDDY, MEEGADA INDEEVAR. "MATHEMATICAL MODELLING OF FINANCIAL MOVIVATED CYBER ATTACK BY FDI AND SECURITY CONSTRAINED OPTIMAL SCHEDULING OF VIRTUAL POWER PLANTS IN ELECTRICITY MARKET." Thesis, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18944.
Анотація:
Power system is a wide interconnected network of electricity generation,
transmission, and distribution systems. With the technical advancement, increase in day to-day demand from industrial, agricultural and residential consumers, and the
disadvantages of monopoly system demanded the power sector for disintegration and
deregulation. Power system deregulation and integrating communication devices are
advantageous for better monitoring and decision making by the system operator. At the
same time, it increases the risk of cyber intrusion. In 2003, the eastern United States and
Canada had major power system blackout due to the failure of grid. Despite of the fact
that the blackout was caused by factors that are other than cyber-attack, many academics
believed that similar catastrophe may occur with targeted cyber intrusion. In 2007, Idaho
National Lab researchers attempted to attack a synchronous generator. The attempt was
successful, and the generator got self-destructed within minutes. This incident alarmed
cyber-security decision-makers, prompting them to establish a critical infrastructure that
is vulnerable to prevent cyber-attack. The existing bad data detection procedure in state
estimation is incapable of detecting a certain sort of cyber-intrusion known as a stealth
attack. Stealth attacks can be used to influence state estimate results for financial gain or
to cause technical problems for the power system.
Unbundling of transmission lines, ensuring social welfare among the power
system utilities, promote investment in the electricity sector. The deregulated power
system has brought up power market as an efficient tool and has created an enabling
environment to accelerate the all-around development of power generation, transmission
and distribution systems. The effective monitoring and decision making is achieved with
the integration of communication lines and internet network. Cyber-Physical System
technology is utilized for more safer and secure grid operations.
In this dissertation, financially motivated false data attacks are investigated, by
injecting manipulated data into day-ahead and real-time electricity markets operation. For
determining the optimal attack vector, it is assumed that the attacker runs a bi-level
optimization problem that comprises the attacker's profit maximisation objective and the
market clearing problem. While manipulating measurement devices such as RTUs, the
attacker needs to take care of being identified by the ISO’s bad data detection (BDD)
mechanism. The proposed attacking model is implemented on the PJM-5 bus test system
to demonstrates the potential impact of financially motivated cyber intrusions in the
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power markets. During the attack, the relationship between market clearing power and
LMPs is established. The simulation results are deduced to demonstrate the effect on
locational Marginal pricing in achieving the attacker's goal of profit maximization.
Secondly, Renewable energy generation has become more prominent in the power
sector around the world. Large integration of RE sources into the electricity markets has
brought further complexities in the markets. Distributed energy sources (DE) have limited
participation in these markets. Considering uncertainties related to RE intermittence
nature, and market prices small-scale REs such as wind power, solar PV power, ESSs,
and utilities comprising CHPs, DG sets, flexible demands, etc., are aggregated in to single
entity in the name of (VPP) and participate in the electricity markets. Hence, it is
important to find out an optimal scheduling solution to these VPPs.
In this dissertation two-stage stochastic programming approach for optimal
scheduling of VPP in the electricity market is presented. The uncertainties are modelled
using scenario bounds and are formulated using stochastic programming approach.
Simulation results are carried out on 4-hour planning horizon.
Since, electricity markets are competitive in nature, each and every market
participant tries to maximize their profits through strategic bidding. Keeping in the view,
the uncertainties related to RE generation, market prices and reserve deployment requests,
VPP also tries to maximize its profit. It is necessary to take strategic decision to counter
the other market participants.
Therefore, a bi-level model is proposed for finding out optimal scheduling
solution in the electricity markets. Uncertainties are modelled using scenario realization
technique. VPP maximize its profit by making strategic decision on trading power in the
DA and reserve markets. To exercise the power of VPP in altering market decision, the
upper-level problem in the bi-level model address the VPP objective to maximize the
profits, while lower level addresses the market clearing problem of both DA and reserve
markets. The proposed model is then reformulated in to single level MILP problem using
KKT optimality conditions and strong duality theorem.
Finally, the proposed model is implemented on IEEE-24 reliability test bus
system. The results are analysed based on the profit acquired by the VPP with and without
flexible demands. The importance of the reserve market in balancing the system is
demonstrated through appropriate scenarios, additionally, demand-side flexibility
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smoothens the load curve and connects the generating and demand side curves, allowing
the VPPs to achieve the best profit. At the end, impact of strategic and non-strategic
decision making on VPP’s profit is also analysed.