*4.2. Scenario 2: Incremental Attack on Load*

Sometimes the attacker tries to break the market and disrupt the power supply for various reasons. One of these types of attacks is the false data injection attack on the smart power network components, such as loads, measurements, detectors, and sensors.

In Scenario 2, it is assumed that the attacker has access to the loads of one hour from the day ahead of the market and by virtually changing the loads by 1.8 times of the main load, the attacker can change the production conditions and profit of the units in the market and create congestion in the network. In this case, LMPs increase in all buses, so this price in bus 1 is different from other buses, in which case it can be said that there is congestion in the network. According to Figure 6, as the load increases, according to Table 5, all units increase their production. DGSs generate electricity at their maximum capacity, and cheap and even expensive generators are on the production line. Given that in reality there has been no increase in load and the attacker has changed the network load information, additional production takes place in the network, which will lead to serious damage to the network and also increase production costs and reduce social welfare. In this case, social welfare is 3148.

**Figure 6.** LMPs at different buses in the case of an incremental load attack.

## *4.3. Scenario 3: Decreasing Attack on Load*

In scenario 3, it is assumed that the attacker has access to the loads of one hour from the day ahead of the market and by virtually reducing the loads by 0.5 times of the main load, the attacker can change the production conditions and profit of the units in the market.

The LMPs have dropped, as shown in Figure 7, but because this is not the case in reality and the load has not been reduced, generators have minimized their production and DGSs have very little production (according to Table 6), which causes failure to provide real loads and a large reduction in unit profits, especially production units, will be dispersed. Additionally, due to the imbalance of load and production in the network, blackouts occur in various sections of the grid. Social welfare in this case is 2536, which is a decrease compared to the normal state.

**Figure 7.** LMPs at different buses in the case of a reduced load attack.


**Table 6.** Status of units in incremental load attack mode.

## *4.4. Scenario 4: Attacking Generator Bid Prices*

It is supposed that the attacker has access to the generator's suggested prices. The attacker can change the suggested prices of the generators (in this scenario, the prices of cheap and expensive production units were shifted together). In this case, according to Table 7, cheap generators and even DGSs have no production, and this will seriously damage the interests of these units. In this case, the power supply of the network will only be the responsibility of expensive generators and will disrupt the financial balance of the market. Table 8 provides the status of units in attack mode at generator prices.


**Table 7.** Status of units in the case load reduction attack mode.


**Table 8.** Status of units in attack mode at generator prices.

#### *4.5. Scenario 5: Attack on Distributed Generation Prices*

In this case, also, the attacker manipulates the proposed prices of DGSs (price increases by 1.4 times the original prices). As a result, according to Table 9, the generation of DGSs reaches zero and does not benefit them. Thus, operating costs increase and social welfare decreases (3320).



#### *4.6. Generation of Units in Different Scenarios*

Figure 8 shows the production of generators in different scenarios. This figure shows that all generators in scenario 2 due to increased load are on the network production line. The lowest generator output was related to the load reduction data attack scenario. Figure 9 also shows the production of DGSs in different scenarios. In this case, the highest production is related to scenario 1.

**Figure 8.** Production of generators in different scenarios.

**Figure 9.** Production of distributed generation sources (DGSs) in different scenarios.
