Sep 15, 2017
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Why do we need Intra-grid Sensors to effectively manage our distribution grids?
Because times have changed IMMENSELY; with no end in sight.
1. Through solar and wind renewables, we are introducing Reverse Energy onto the distribution grids, for which the grids and the transformers were never even conceived, let alone designed to handle. While renewables are beneficial, Reverse Energy can produce unstable, and unsafe grid conditions. (Note: the entire distribution grid was never conceived to experience two-way power flow, yet renewables are indeed creating this never conceived impact)
2. Reverse Energy also creates new instances of unknown and unplanned voltage fluctuations/conditions which further contributes to unstable and unsafe grid conditions.
3. Electric Vehicle charging stations create a new, unplanned load on transformers. Each charging station has the capability of adding up to one additional home worth of power load on a transformer, for which the transformer was never properly sized to handle when it was deployed, likely years ago.
4. Illegal marijuana production is rampant. Illegal marijuana grow houses commonly steal significant levels of power from the grid via thieves simply tapping power lines in front of their meters. No endpoint meter (including AMI smart meters) can effectively detect this power theft. This means thieves steal as much power as they want, and they steal it indefinitely without fear of detection. Not only does this result in stolen power that is commonly amortized across law-abiding rate payer’s bills, but it also presents yet another unplanned, significant load on transformers, and therefore the grid. (Note: the US power theft estimates are $6 Billion PER YEAR, or higher…yet this power loss goes virtually unchecked by most grid operators today)
5. Legalized marijuana production is increasing. When jurisdictions legalize weed, significant unplanned loading hits the transformers and the grid via those who now begin to grow weed using power-intense hydroponic resources. This causes additional strain onto the existing transformers, and the grid. While there are increased tax revenues being generated for jurisdictions via legalized weed, the grid is bearing the burden of this unplanned, significant loading impact.
6. By most measures, including the US Department of Energy, the average age of distribution grid transformers is presently 38-42 years of actual service. Yet, the average projected life span of transformers is 40 years. Simply, today’s power grids are significantly aged….many transformers are nearing or have eclipsed their intended life span, yet we continue to demand even more performance, more reliability and unintended service from these same aged transformers.
7. Outages cause serious problems to societies... from lifestyle inconveniences, to lost economic productivity, to serious health/medical/security impacts, to food spoilage, to sewage impacts, to water availability impacts, etc… Outages result in massive ‘loss’. Intra-grid sensors accelerate outage location detection, and therefore accelerate power restoration which is superior to AMI smart meter capabilities. By focusing on transformer-level outages, crews locate the source of outages faster. And, intra-grid sensors actually reduce outage occurrences (aka, increase reliability) by revealing weak and failing transformers in advance of costly, unplanned outages.
8. Excessive Voltages are pervasive throughout grids. This means that utilities are delivering more power through the grid than is required to service rate payer’s needs. But, utility operators typically have no idea how much, and where the excessive voltages are occurring in their grid. This means that ratepayers simply bear the cost burden of over-servicing the grid by operators, versus operators improving their power delivery efficiency.
9. Loss is pervasive throughout all distribution grids on the planet. The US reports over $19.5 Billion of unknown, unmetered power loss in 2015 alone. Loss in this case is defined at the total amount of power that departed from distribution substations, but was never registered at the downstream endpoint meters. In essence, the power was injected into the grid at substations, but over $19.5Billion of that power vanished inside the grid. This type of massive power loss inside the grid occurs annually, and ratepayers presently bear the financial burden even though they did not consume the vanished power. Loss is typically due to a) excessive voltages, b) power theft, c) improper transformer sizing, and other factors. Until intra-grid sensors emerged, utilities had no reliable method to locate the ongoing massive Power Loss that wastes natural and financial resources. Now, intra-grid sensors provide operators with a cost-effective solution.
10. Reactive versus Proactive grid management capability. Throughout the history of electricity grid management, operators have relied upon customer complaints, and reported outages to address ‘problems’ within the grid. In essence, operators have managed the grid “blindly”, by having no reliable access to perpetually changing intra-grid information; nor did they have a way to understand perpetually changing intra-grid conditions. Now, intra-grid sensors resolve the inefficient, costly, reactive grid management process by creating a cost efficient, energy efficient, grid efficient, proactive grid management system. This is a massive paradigm shift for grid management of the future.
11. The distribution grid space occurring between substations and endpoint meters is undeniably the most volatile, most vulnerable, and most dynamic segment of the entire electricity delivery system. Yet, operators have been required to manage this critical grid segment without proper technology to assist them. Now, intra-grid sensors provide operators with clear vision into this “black hole” segment of the grid. No longer do operators have to manage blindly, nor cause ratepayers to continue subsidizing inefficient utility operations, and inefficient power flows through the grid space.
12. AMI smart meters have been unable to provide accurate intra-grid information. Because of perpetually inaccurate meter to transformer association (i.e., inaccurate GIS mapping), and because of pervasive pre-meter tapping which has escalated since AMI deployments, AMI intra-grid data is unreliable. Intra-grid sensors remedy this problem with AMI smart meters by creating a critical data reconciliation point inside the grid, upstream from the AMI smart meters, at the transformer level. By combining intra-grid sensors with AMI smart meters, operators achieve maximum data value, and maximum grid management control capability. With AMI smart meters alone, operators remain blind to intra-grid conditions which cause documented energy inefficiency, and elevated operating costs.
13. Decrease electricity provider’s Operating Expenses, and increase Capital Expense Return on Investment. Intra-grid sensors provide proactive, unique, timely, accurate, granular intra-grid data which allows operators to reduce unplanned power outages, to reduce costly truck rolls, to reduce premature transformer replacement costs, to lessen transformer oil spills/fires/hazardous material cleanup costs. While also reducing excessive voltage costs being paid by operators and passed along to ratepayers.
14. Greenhouse Gasses (GHG) Reduction. Intra-grid sensors uniquely allow operators to proactively identify annual Power Loss (e.g., > $19.5 Billion in the US alone in 2015), to identify excessive voltages which equates to wasted power, to identify improperly sized transformers which run inefficiently, etc… Collectively the energy efficiency gains created by intra-grid sensors allows distribution operators to reduce their purchase demand of power, which transcends upstream to reduced generation costs, and therefore reduced GHG from the reduced generation demand.
15. Increased Metered Revenues for utility operators. By identifying the significant unmetered Power Loss within the grid, identifying meter clerical/billing errors, by reducing power outages which results in more consistent power delivery to endpoint meters, operators actually increase their metered revenues, while simultaneously reducing their Operating Expenses and increasing their Capital Expense ROI as noted above. Intra-grid sensors create improved financial stewardship of the grids.
16. Monitor, maintain, and support the Clean Tech SuperGridTM. Approximately 65-100 years ago, the distribution grid was conceived and designed to be a one-way delivery system of electricity; and operators were primarily tasked with simply “keeping everyone’s lights on”. Those days are swiftly vanishing.
In summary, today and increasingly as the future unfolds, the one-way simple electricity grid of the past is rapidly evolving into a complex bi-directional, multi-purpose network that is capable of driving genuine energy efficiency, increasing energy conservation, supporting commercial transactions such as block chain and Conservation Emission Reduction (CER) credits, and facilitating increased tax revenues through the legalization of marijuana, the adoption of Distributed Energy Resources (DER), Electric Vehicle sales, etc... This is the dawn of the Clean Tech SuperGrid™. Where reliability, energy efficiency, bi-directional energy flow, commercial transactions, increased renewables, battery storage, electric vehicle charging stations, and reduced GHG will all simultaneously originate, reside, and travel.
Intra-grid sensors are required to ensure that a stable, reliable Clean Tech SuperGrid™ is operating at maximum capability and capacity. And societies will demand and expect leadership to provide and maintain a healthy Clean Tech SuperGrid™ to support our future. Otherwise, if our focus simply remains on creating burdensome demands upon the grid and grid-edge without proper monitoring and reliability enhancements, we are then setting the stage for serious, and potentially harmful grid pressures that will undoubtedly result in excessive outages, decreased reliability, heightened cost burdens on societies, and increased grid safety concerns.