THE CASE FOR SCUC SOFTWARE

Transcription

1 Created by the content marketing team at Utility Sponsored by 2014

2 SCUC SOLUTION SNAPSHOT Problem Utilities and grid operators face a growing number of variable challenges in delivering electricity to customers as efficiently and economically as possible. Solution Siemens security constrained unit commitment software optimizes the commitment and dispatch of generation in order to maintain grid reliability at the lowest possible cost. According to Siemens, utilities have seen a full payback of its SCUC software solution within a matter of weeks. The algorithms determine the best scenario. Ravi Pradhan Chief Technology Officer Siemens Smart Grid Division Siemens answers On the surface, it appears that California has some of the easiest access to the cleanest and cheapest fuel in the country: hydropower from the Bonneville Power Administration, which is pumped from the northwestern region to the state s municipalities. But upon closer look, California s transmission network has difficulty handling such a massive influx of capacity. So, what happens next? Through a sophisticated set of algorithms encapsulated in a software program, California s transmission system operators can find the next-best alternative that would not overload lines and potentially cause brownouts. To avert such a possibility, the new tools may point to generators in Southern California, which can then send the electricity north and help avoid energy traffic jams. To that end, the analyses will reveal if any part of the network is congested, enabling the grid operator to redirect flows to keep the electricity humming. Today, electricity system operators can apply security constrained unit commitment (SCUC) software to examine thousands of constraints in a system and project exactly how much PAGE 2

3 generation will be needed, allowing power supply to be accurately matched with demand. The same algorithms can tell operators which units to run and where to avoid trouble spots, both in real time and looking forward. The software is about using energy in the most optimal way. While snapshots into how the electricity load may look at any given point are helpful, it is even more beneficial to understand the ebbs and flows of such usage throughout the day and even the week. That gives system operators better insight into which generators should remain ready to ramp up to meet demand as well as those it could ramp down to save money. Such efficiencies could help avoid the construction of expensive infrastructure such as new lines and plants. Siemens, for example, says its software can save 5% to 7% of a utility s energy costs. Given that business and residential consumers spend billions each year on electricity, the value of the technology quickly adds up, paying for itself within just a matter of weeks. The added intelligence of Siemens SCUC software can go a long way towards generating these savings, especially because jurisdictions are spending billions of dollars buying electricity each year in the case of California, an estimated $60 billion a year. throughout the course of day, or longer. With numerous types of generators standing ready to serve, the question becomes which ones to dispatch and over which set of wires: what is the most efficient and economical combination of resources to dispatch? Siemens SCUC software answers those questions. GOOD MODELING Siemens SCUC software involves a mathematical formulation in combination with plain physics. Big machines take time to fire up and, as they do, they rotate faster and faster, burning up energy. At the point in which the generator is fully ready but still idle, it is consuming energy or incurring the high cost of operation a concept that holds true for each stage of its preparedness. All that is modeled in our software, says Pradhan. The algorithm knows how long it takes the generator to gear up and how much energy it will burn in the process. Based on fuel costs, Siemens SCUC software knows how much a utility will spend, all of which can be multiplied not just by the number of generators that a We are putting in the physical characteristics and letting the algorithms determine the best scenario, says Ravi Pradhan, chief technology officer for Siemens Smart Grid. A utility, for example, may have multiple generating units within one facility and Siemens SCUC software can calculate the best combination to dispatch at any given time, which will save a lot of money if measured PAGE 3

4 utility has, but by the number of variables that can be factored into play. In short, the software takes into account any number of constraints to dispatch generation resources and punches out the most economical answer. Historical precedence may suggest that electricity demand will decline during a certain period before it will gradually pick back up. Siemens SCUC software would then tell a system operator to slow down the most expensive generation, but to prepare the cheaper units to kick in when demand resumes. The software can precisely tell system operators the level of electricity that they will need to keep in reserve to meet a worst-case scenario, such as those occurring on extremely hot days. Some utilities, for example, are domiciled in states that have limits on greenhouse gas emissions. That means the tools must be programmed to run certain units at the most optimal times, when the harmful releases could be minimized. Others are in states that have renewable portfolio standards that require a set amount of electricity to be generated from sustainable sources. As such, Siemens SCUC software can tell grid operators the most likely times those generating facilities will be available and when other types of generators must be used as back up. Even though the variables can run into the thousands, Siemens SCUC software provides answers quicker than other options. Beyond the ability to incorporate such a wide range of possibilities into the equation, the software measures the true losses by alternating current-based solutions instead of direct current-based approximations calculating the loss of electricity as it is sent along the wires. Other software programs evaluate system optimization using direct current and do not contemplate those inefficiencies. There are numerous solutions, but I need the answer right away, says Sankaran Rajagopal, senior manager, development and operations in energy markets management systems for Siemens. An effective solution must consider thousands of variables while ensuring an efficient and optimal use of the transmission grid. So, if a system operator has committed a generator to begin producing power while an electrical storm has taken out a transmission line, the software can handle the variation and redirect the power to where it is needed, he adds. It s about generating an accurate amount of energy, and doing so in the most cost-effective manner. PAGE 4

5 THINKING IT THROUGH Given the clear promise of software, what s stopping the widespread adoption of those solutions? Generally speaking, it s the inherently conservative nature of utilities, which are understandably slow to move on new technologies. At the same time, these companies have large and complex energy systems that require a fair degree of analysis in terms of applying new information technologies. All that takes work including time away from everyday operational issues. It takes some effort on their part to come up with accurate data, says Pradhan. But if they do this, the algorithm will do the job of finding the best solution. Understanding the nuances of a utility s generation and transmission network is one issue, but dealing with the regulatory requirements is another. Some utilities may feel that if they save money by running their systems more productively, then their local public utility commissions may tell them to reduce their retail rates to customers effectively washing out any potential financial savings. But an investment in software would mean that both generating plants and transmission lines could be more efficiently operated. That could mean the avoidance of certain infrastructure projects some of the most capital intensive deals that a utility can take on. demand. That s what the software can calculate, using an infinite number of possibilities, or in technical parlance, the commitment aspect. Energy must ultimately reach those residential, commercial and industrial customers that need it, which is done through the transmission lines. Optimizing such flows to meet capacity constraints is therefore necessary, while avoiding congestion and circumventing downed lines is also critical. That is the security part of the software solution. Our formulation will lead to the best solution in all cases, meaning it will reduce the cost of energy and it will be the most economic choice, while also optimizing the flow of electricity through the transmission system, notes Pradhan. Older algorithms and software programs have been unable to consider the range of variables that the Siemens solutions can the gravy is that the answer it gives is both economical and instantaneous. It s an investment in time and money. But in relatively short order, it delivers results that improve utilities bottom lines and the services that they are providing to their customers. At the same time, getting those plants and wires built can be among the most contentious regulatory issues that any power company will endure. Making better use of the assets that they currently have online is the low-hanging fruit. Because electrons cannot be stored in most cases, the supply of electricity must match the PAGE 5