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North American Power is a retail energy provider founded in 2009 to help consumers save on electricity while doing its part to provide cleaner energy options for the future. Each customer that switches to North American Power automatically chooses 25% renewable energy and has the choice to upgrade to 100% renewable energy for a slightly higher rate than the standard rate. North American Power’s ongoing charitable initiative, Mission to Millions, allows customers to direct company funds to charities each month when they pay their bill.
A customer of North American Power can become Independent Representative for the company by enrolling one new customer, completing and signing an Independent Representative Agreement, taking and passing an online training program and providing the required compensation plan payment information.
North American Power Representatives earn a $7 bonus for each personally referred residential or small commercial customer with historical Kilowatt usage between 250 and 5,000 and every American Wind customer they acquire. Reps and Rep interested in offering North American Power products or working with you to build a business list on Npros.
Put your information in front of thousands of prospects looking for home business opportunities. North American Power has agreed to pay $2.6 million into Connecticut's fuel assistance program to settle a two-year investigation by the state's attorney general into the company's marketing practices.
North American Power, which admitted no wrongdoing in the settlement, will make "charitable donations" to the nonprofit Operation Fuel in equal payments of $100,000 over 26 months.
Sunday, 16 December 2012 -- North American Power, a New England energy company that has saved hundreds of thousands of customers money on their electric bills, is introducing their retail electricity supply service to the 400,000-plus customers of PSNH. SOUTH NORWALK, Conn., June 19, 2012 -- North American Power, the energy company that has saved its customers millions of dollars on their electric bills while greening the power grid, was presented with two Gold Stevie® Awards in The 10th Annual American Business Awards last night in New York City. Efficient power transmission and distribution would benefit from synchronized near–real-time measurements of voltage and current phasors at widely dispersed locations in an electric power grid. A phasor measurement unit (PMU), also known as a synchrophasor, is a device capable of measuring power system voltage and current phasors at a rate of thousands of samples per second. Unfortunately, low-received-power, unencrypted civil GPS signals have proven to be vulnerable to jamming and spoofing attacks. In a future scenario where PMU data play a significant role in power system operations, an attacker might disturb or bring down the system by attacking the GPS receivers attached to PMUs.
Even without being jammed or spoofed, a GPS receiver does not always yield correct position and time solutions due to accidental receiver malfunctions.
So far, a variety of countermeasures have been proposed to enhance civil GPS receivers’ robustness against jamming and spoofing attacks and accidental receiver errors.
The first group of proposed solutions uses information from sensors external to the GPS subsystem, such as accelerometers, gyroscopes, odometers, and cellular networks. Most of these proposed methods were designed for stand-alone kinematic receivers, and their primary objective was reliable positioning but not necessarily reliable timing.
In this article, we present a multi-layered multi-receiver architecture that hardens GPS-based timing against jamming, spoofing, and receiver errors. In describing this security architecture, we begin with a formal definition of threat models and design goals. The GPS receiver uses trilateration (also referred to as multilateration) to determine its position and clock bias. This article is concerned with the threats that render any of these two prerequisites unavailable or incorrect. Figure 1 (see inset photo, above right, for all figures and tables) shows our proposed multi-layered, multi-receiver architecture that enables reliable GPS-based timing. Although the P(Y) code is encrypted and thus unknown to non-military receivers and although its received versions are noisy and may be distorted by narrow-band RF front-ends, when conducting cross-correlation, the P(Y) code components in the two snippets are similar enough to create a high correlation peak if neither receiver is spoofed.
Therefore, this anti-spoofing method has proven effectiveness against synthesized spoofing attacks, including threat models [S1] and [S2]. To implement the P(Y)-code cross-correlation countermeasure, the receiver must be able to output baseband samples, and these samples need to be transmitted over a data network.
Additionally, the PIA vector tracking approach allows for a natural defense against threat [S3].
Multi-receiver vector tracking loops collaboratively process information from multiple receivers.
The main downside of multi-receiver vector tracking is the intensive computation that it requires. Similar to countermeasure [C2], multi-receiver processing requires receivers to output baseband samples. Furthermore, under jamming attacks (threat model [J]), a receiver may be able to track satellites but cannot correctly decode navigation messages. Reverse-calculated satellite positions match the satellite positions calculated from the navigation data only when both the navigation data and the pseudorange measurements are correct.
However, this countermeasure is effective against threat models [S1] and [S2] when multiple receivers are deployed in close vicinity and the position solutions from the receivers are cross-checked. If all receivers are spoofed by the same spoofer, although they generate the same clock bias, they output identical position solutions despite being at different locations because the position solution is controlled by the spoofer and does not depend on the receivers’ locations.
The only way to spoof multiple receivers without being detected is to employ multiple spoofers, each of which must fine-tune the transmit power so as to spoof just one receiver.
The table shows that our multi-layered multi-receiver approach provides at least two effective countermeasures against each threat. Countermeasures [C1]-[C4] in the signal conditioning layer and the tracking loop layer require modification of the current GPS time reference receivers used in PMUs.
Because countermeasures [C5]-[C8] utilize the output already available from current GPS time reference receivers, these can be implemented in current power girds with minimal modification.
The previous section showed that a position-information-aiding tracking loop is an effective countermeasure against jamming and replay spoofing. Our PIA tracking loop design incorporates predicted clock bias, together with the known receiver position and satellite positions calculated from broadcast ephemerides, to generate the local code and carrier replicas. In implementing the PIA vector tracking algorithm, we actively drew on the previous vector tracking research completed by S.
Scalar tracking was able to produce decodable navigation bits until we increased the noise past four decibels. The PIA vector tracking loop continued operating until we increased the noise past nine decibels (Figure 6), at which point the maximum time errors were close to 20 nanoseconds. The experimental results show that, in comparison to scalar tracking, PIA tracking gains at least a five-decibel advantage in tolerating jamming signals. This article presents a reliable and robust GPS-based timing mechanism that supports power system applications such as the PMU.
Most of the countermeasures exploit the static and networked nature of time reference receivers. In our discussion in this article, we further implemented one of the countermeasures: the PIA tracking loop.
Accurate timing is a critical element for many economic activities around the world, including not only power grids but also communication systems and financial networks. This work was supported in part by the Trustworthy Cyber Infrastructure for the Power Grid (TCIPG) under U.S. Electric power transmission or "high voltage electric transmission" is the bulk transfer of electrical energy, from generating power plants to substations located near population centers. Transmission lines mostly use three-phase alternating current (AC), although single phase AC is sometimes used in railway electrification systems.


Electricity is transmitted at high voltages (110 kV or above) to reduce the energy lost in long distance transmission.
A key limitation in the distribution of electricity is that, with minor exceptions, electrical energy cannot be stored, and therefore must be generated as needed. Since North American Power is an energy supplier that works with local utilities, customers who switch to North American Power have no interruption in service and continue to be billed by their local utility. Representatives are also eligible to earn residual commissions on the first 5 levels of their organization. Click on the links for information on specific excecutive for their biography with North American Power and other companies and executives they have been associated with. Such measurements also could enable effective real-time system monitoring and control, which are considered to be the key to preventing wide-scale cascading outages like the 2003 Northeast Blackout. The samples are time-stamped with one-microsecond or better accuracy to a common absolute time reference provided by the GPS receivers attached to PMUs. A jammer emits a high-power interfering signal at the GPS frequency in order to deny nearby GPS receivers access to the GPS signal.
These methods can be generally categorized into four groups: external assistance, signal features, redundant measurements, and cryptography.
The second group makes use of the features inherent in GPS signals, including angle-of-arrival (spatial sparsity), time-frequency sparsity, signal quality, signal power, and multipath. There is still a dearth of countermeasures designed for static, networked GPS time reference receivers in power systems.
Our architecture integrates eight countermeasures in all layers of receiver signal and data processing. A stand-alone GPS Standard Positioning Service receiver must meet two prerequisites for generating a correct real-time position and time solution: correct pseudorange measurements from at least four satellites and valid navigation messages so that the receiver can correctly calculate satellite positions and clock biases. For the other threat models, our goal is to detect the threat with a high confidence in a timely manner. Our architecture employs comprehensive countermeasures in all layers of receiver signal and data processing. In a spoofing attack, the counterfeit signal must overpower the authentic signal so that a victim receiver will lock onto the more powerful counterfeit signal.
Advantages of this countermeasure include very low computational complexity and independence (not relying on other receivers).
Unfortunately, it is ineffective against threat [S3] because a replay spoofer rebroadcasts the authentic GPS signals, which contain the correct P(Y) code. Due to the high sampling rate (usually greater than two Msps), we recommend performing this spoofing detection periodically rather than continuously. Our proposed approach of PIA tracking loops aims to take advantage of the static nature of GPS receivers used in PMUs to enhance tracking performance. Because the receivers in a PMU must remain static, the parameters of the tracking loops can be adaptively chosen to narrow the loop filter bandwidth. In addition to the PIA tracking loops that leverage the static nature of PMU GPS receivers, in the code and carrier tracking layer we use multi-receiver vector tracking loops to explore the benefit from the networked nature of GPS-timed PMUs either within a substation or across an electrical grid. The high-sampling-rate data need to be continuously transmitted among receivers (or to a central processing server). This countermeasure cross-checks the navigation messages collected by one PMU GPS receiver with those collected by others. Using navigation data from other receivers helps the receiver under attack continue operating. Because the PMU GPS receivers are static and their positions are known, we propose using the pseudorange measurements from multiple receivers to reverse-calculate satellite positions via trilateration.
Therefore, this countermeasure can easily detect replay spoofing attacks (threat model [S3]) and receiver errors (threat model [E]). For a single GPS receiver, checking the position solution against its a priori known location can detect a replay spoofer (threat model [S3]).
Figure 2 shows three receivers deployed in a substation with a distance of 20 to 50 meters between two neighboring receivers. The spoofers would also need to be synchronized to ensure that the clock biases output by all receivers are the same. For each threat model, markers *, ?, and • denote whether a countermeasure is effective, auxiliary, or ineffective, respectively.
Taking auxiliary countermeasures into account, at least five countermeasures are available against spoofing attacks and receiver errors. As can be seen from Table 1, countermeasures [C5]-[C8] still provide redundant protection against spoofing attacks and receiver errors.
This section presents one of our designs for a PIA tracking loop along with experimental results. The early, late, and prompt code replicas are used to create correlations with the signal from the GPS front-end.
In the experiments, we used an off-the-shelf low-cost GPS sampler as the front-end to collect raw GPS signals. During data collection the antenna had full view of an open sky with up to 10 satellites with clear line of sight. To determine the performance of the PIA vector-tracking algorithm, we added 1–10 decibels of simulated Gaussian noise to the raw GPS signal and processed the resulting data. However, with every decibel of additional noise, the number of channels that experienced a loss-of-lock increased.
We designed the PIA vector-tracking algorithm to function with the known true position as the reference point. Due to the fixed-position nature of the PIA vector-tracking loop, the algorithm fails to converge as soon as the meaconing attack begins.
We have designed a multi-layered multi-receiver architecture that incorporates eight countermeasures in all layers of signal and data processing. We have defined five threat models and qualitatively analyzed the effectiveness of each countermeasure against each threat model. Our experiments show that PIA tracking can improve the receiver’s robustness against jamming attack and can detect replay spoofing attacks.
Through long-term cooperation with customers, We will provide them with our products, systems and services, as well as our customers contacts. This is distinct from the local wiring between high voltage substations and customers, which is typically referred to as electric power distribution. A sophisticated system of control is therefore required to ensure electric generation very closely matches the demand. A spoofer broadcasts a counterfeit GPS signal that overpowers the authentic signal so as to manipulate a victim receiver’s reported position, time, or both.
Heng et alia (2012b) showed that 0.34 percent of the navigation messages collected by the geodetic-grade GPS receivers in the International GNSS Service (IGS) network during the year 2009 were incorrect. The third group exploits the redundancy of pseudorange measurements and the correlation among multiple cooperative receivers.
Finally, we present our implementation of a key countermeasure, a position-information-aiding tracking loop, along with experimental results. The next section describes our multi-layered multi-receiver architecture and how it achieves these goals.


Therefore, an ascent of received signal power implies the possibility of a spoofing attack. A major disadvantage is the low detection confidence due to the stochastic nature of signal power.
The knowledge of the true position of GPS receivers used in PMUs helps predict the code and carrier phases by projecting the relative position and velocity between satellites and the receiver in the line-of-sight (LOS) direction. The narrowband tracking loop limits receiver noise, which reduces the effective radius of any jamming attacks (threat [J]).
As the PIA vector-tracking approach depends on its knowledge of the true position of the GPS receiver, then the PIA tracking loop will fail to function in the case of a replay spoofing attack, therefore being able to detect meaconing. Soloviev et alia showed that multi-receiver signal accumulation improves acquisition and tracking performance under low signal-to-noise ratio (SNR) conditions.
In practice, we recommend choosing receivers near to one another and transmitting the data over a local area network. This method can easily detect data-level spoofing attacks (threat model [S1]) in which the navigation data are modified. This countermeasure also makes the synthesized spoofing attacks (threat models [S1] and [S2]) much more difficult because it imposes more constraints on “valid” spoofing signals.
Receiver errors (threat model [E]) can also be detected if the errors result in an incorrect position solution. If no receivers are spoofed, all receivers yield the same time solutions, and each receiver’s position solution is close to its actual position.
Based on this fact, we propose monitoring the behavior of receiver clocks and learning the statistics. The redundancy in countermeasures guarantees highly reliable GPS-based timing even if some of the countermeasures fail. After initialization, the tracking loop first predicts the navigation solution and errors for the next time epoch.
We choose to use carrier frequency discriminators from each channel to form the Kalman filter measurement matrix. Akos (Additional Resources) as well as the open source software-defined radio (SDR) code created by K. At four decibels of additional noise (Figure 5), the scalar tracking loop was only able to lock onto four satellites while the original data could lock onto all nine. In a replay spoofing attack, also known as the meaconing attack, the position solution calculated would be equal to the position of the attacker. Therefore, this shows that our proposed PIA vector tracking is capable of detecting meaconing attacks. Our analysis demonstrates that the redundant, independent but complementary countermeasures provide high reliability and robustness. Our multi-layered multi-receiver architecture, although developed in the context of power systems, is also applicable to these other systems. Business reputation inhigh standard is our company's principle, and the good credit makes us get the trust andsupport from our customers. Transmission lines, when interconnected with each other, become high voltage transmission networks.
Underground power transmission has a significantly higher cost and greater operational limitations but is sometimes used in urban areas or sensitive locations.
If supply and demand are not in balance, generation plants and transmission equipment can shut down which, in the worst cases, can lead to a major regional blackout, such as occurred in California and the US Northwest in 1996 and in the US Northeast in 1965, 1977 and 2003. Shepard et alia have shown that an attacker could cause a generator trip by spoofing a GPS time reference receiver. Another relevant event occurred on July 31, 2006, when 29 out of 245 GPS receivers in the IGS network missed or misinterpreted a navigation message. The fourth group uses cryptographic, unpredictable information carried by the GPS signal to ensure its authenticity. In GPS receivers that use two or more bits for sampling, automatic gain control (AGC) is used to adjust the front-end gain to a level suitable for the analog-to-digital converter (ADC). Therefore, the signal-power check is considered as an auxiliary countermeasure against all spoofing threats [S1]-[S3].
Psiaki et alia (see Additional Resources) have demonstrated the efficacy of this method using one user receiver and one reference receiver. This type of receiver architecture is referred to as vector tracking and has been shown to increase immunity to interference and jamming. Cross-checking also ensures that a receiver does not miss or misinterpret a navigation message (threat model [E]). However, this method cannot detect the synthesized spoofing attacks (threat models [S1] and [S2]) because, when formulated properly, these attacks ensure unaltered position solutions. If a fraction of the receivers are spoofed by a spoofer, the victim receivers yield time solutions that are different from those of the innocent receivers. The Kalman filter then estimates the new errors, and, based on the updated errors, we can estimate the new navigation solution and create a prediction for the next time epoch.
It uses a sampling frequency from 4 to 16 megahertz and a quantization resolution of two bits.
With no added noise, the maximum time errors for the scalar results were close to 45 nanoseconds whereas the time errors for the PIA results were around 10 nanoseconds. The time errors also increased as the noise increased: scalar results showed close to 60 nanoseconds of maximum errors and PIA results showed maximum errors of only 13 nanoseconds.
PIA vector tracking will instantly detect the attack if the attacker is sufficiently far (greater than 10 meters) from the receiver.
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To reduce the risk of such failures, electric transmission networks are interconnected into regional, national or continental wide networks thereby providing multiple redundant alternate routes for power to flow should (weather or equipment) failures occur. As a result, the 29 receivers miscalculated their positions and clocks for more than one hour. Some of the key papers and articles describing these various types of spoofing defenses can be found in the Additional Resources section. In addition, multi-receiver signal processing helps detect receiver errors (threat model [E]) because a malfunctioning receiver’s performance is usually inconsistent with other receivers.
Because the quality of GPS receivers used in PMUs is generally higher than this kind of front-end, the results we obtain using data collected employing the low-cost sampler will provide a conservative, lower-bound estimate of results produced by PMU receivers applying our PIA tracking loop design.
Akos (see Additional Resources) have shown that AGC level is a low-computational-complexity, low-cost means to detect potential spoofing attacks. A key conclusion of this research was that, respectively, the probability of detection errors decreases exponentially with the length of the P(Y)-code snippet (preferably one second or longer) and with the number of reference receivers. Due to the stochastic volatility of receiver clocks, this countermeasure is considered auxiliary in our architecture.



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