Summer is here and the heat has hit. As our Air Serv® technicians enter into our busy season, we wanted to make you aware of a number of problems that can affect your AC unit, from overheating to turning on and off frequently. Kevin Cargile with Aire Serv of Omaha explains that facing AC problems in the summer can be easier than you think, and that when it comes to keeping your AC unit running through the summer, there are a number of things you can do to keep it maintained on your own. Aire Serv: What are some of the top AC problems people face in the summer? Kevin Cargile: The number one problem I have found is keeping the air filter clean. you should check it once a month, maybe when you pay your electric bill, to remind yourself to go downstairs and check it. Aire Serv has a link on their website that you can sign up for and it will send you a reminder every month to check your filter. Aire Serv: How can I tell if my AC is overheating?

Kevin Cargile: The temperature inside will start to go up. You can look at the coil outside and see if it has dirt or debris on it to make sure it is in good shape. Aire Serv: What should I do if my AC unit turns on or off too frequently? Kevin Cargile: That is a sign that the AC unit is typically oversized and the AC unit is cooling your house too quickly. Aire Serv: How often should I check my AC unit? Kevin Cargile: Have it maintained at least one a year, and then check the filter for debris once a month. Sometimes when the grass is mowed it may push grass into the unit, and that will cause some problems as well. Aire Serv: Do you have any other tips for keeping your AC running in good condition Kevin Cargile: Make sure everything stays clean and have it maintained at the beginning of the year or sometime during the year to make sure that everything is running at optimal parameters. No matter what problem you may be having with your AC unit, you can count

on your Comfort Company to keep you cool this summer.Spot Coolers and Portable Air Conditioners: Key Specifications Temporary Cooling: Plan for an Emergency Part 3: Ceiling-Mounted AC Units Solve Space Issues By Thomas A. Westerkamp HVAC   Article Use Policy Managers face challenges in attempting to ensure proper cooling because many facilities are in a constant state of flux. Problems can arise from equipment added after the original HVAC system is installed, creating a cooling demand the system cannot handle.how to turn ac unit off A common example is adding a data center or remote computer room, sometimes no larger than a closet. ac unit repair costsAfter the computer equipment’s installation, computer system crashes begin to occur because air conditioning cannot handle the increased heat load. ac units in house

In many instances, the room also is closed off for security reasons, and the building HVAC is not able to reach it. This situation can be a major problem for several reasons. First, the problem is not temporary. Second, the heat load not only causes computer crashes. It also eventually can destroy delicate components, which are expensive to replace, and the resulting downtime is unacceptable. Third, no room is available to add air conditioning because of limited floor space. A ceiling-mounted air conditioning unit might offer a solution to all of these problems. This packaged system requires only a fresh-air intake and hot-air exhaust connection through the ceiling, and mounting bolts make for efficient installation. It also is relatively easy to provide electricity to the unit because it runs on 120-volt A/C power, and a 20-amp breaker usually is sufficient. The unit provides the needed cooling, it runs only as long as needed without overloading the existing building system, and it does not use floor space.

Part 1: Spot Coolers and Portable Air Conditioners: Key Specifications Part 2: Temporary Cooling: Plan for an Emergency Part 3: Ceiling-Mounted AC Units Solve Space Issues The unit commitment problem (UC) in electrical power production is a large family of mathematical optimization problems where the production of a set of electrical generators is coordinated in order to achieve some common target, usually either match the energy demand at minimum cost or maximize revenues from energy production. This is necessary because it is difficult to store electrical energy on a scale comparable with normal consumption; hence, each (substantial) variation in the consumption must be matched by a corresponding variation of the production. Coordinating generation units is a difficult task for a number of reasons: Because the relevant details of the electrical system greatly vary worldwide, there are many variants of the UC problem, which are often very difficult to solve.

This is also so because, since some units require quite a long time (many hours) to start up or shut down, the decisions need be taken well in advance (usually, the day before), which implies that these problems have to be solved within tight time limits (several minutes to a few hours). UC is therefore one of the fundamental problems in power system management and simulation. It has been studied for many years,[1][2] and still is one of the most significant energy optimization problems. Recent surveys on the subject[3][4] count many hundreds of scientific articles devoted to the problem. Furthermore, several commercial products comprise specific modules for solving UC,[5] or are even entirely devoted to its solution. There are many different UC problems, as the electrical system is structured and governed differently across the world. The decisions that have to be taken usually comprise: While the above features are usually present, there are many combinations and many different cases.

Among these we mention: The objectives of UC depend on the aims of the actor for which it is solved. For a MO, this is basically to minimize energy production costs while satisfying the demand; reliability and emissions are usually treated as constraints. In a free-market regime, the aim is rather to maximize energy production profits, i.e., the difference between revenues (due to selling energy) and costs (due to producing it). If the GenCo is a price maker, i.e., is has sufficient size to influence market prices, it may in principle perform strategic bidding[11] in order to improve its profits. This means bidding its production at high cost so as to raise market prices, losing market share but retaining some because, essentially, there is not enough generation capacity. For some regions this may be due to the fact that there is not enough grid network capacity to import energy from nearby regions with available generation capacity.[12] While the electrical markets are highly regulated in order to, among other things, rule out such behavior, large producers can still benefit from simultaneously optimizing the bids of all their units to take into account their combined effect on market prices.

[13] On the contrary, price takers can simply optimize each generator independently, as, not having a significant impact on prices, the corresponding decisions are not correlated. In the context of UC, generating units are usually classified as: There are three different ways in which the energy grid is represented within a UC: When the full AC model is used, UC actually incorporates the optimal power flow problem, which is already a nonconvex nonlinear problem. Recently, the traditional "passive" view of the energy grid in UC has been challenged. In a fixed electrical network currents cannot be routed, their behavior being entirely dictated by nodal power injection: the only way to modify the network load is therefore to change nodal demand or production, for which there is limited scope. However, a somewhat counter-intuitive consequence of Kirchhoff laws is that interrupting a line (maybe even a congested one) causes a global re-routing of electrical energy and may therefore improve grid performances.

This has led to defining the Optimal Transmission Switching problem,[10] whereby some of the lines of the grid can be dynamically opened and closed across the time horizon. Incorporating this feature in the UC problem makes it difficult to solve even with the DC approximation, even more so with the full AC model[22] A troubling consequence of the fact that UC needs be solved well in advance to the actual operations is that the future state of the system is not known exactly, and therefore needs be estimated. This used to be a relatively minor problem when the uncertainty in the system was only due to variation of users' demand, which on aggregate can be forecasted quite effectively,[23][24] and occurrence of lines or generators faults, which can be dealt with by well established rules (spinning reserve). However, in recent years the production from intermittent renewable production sources has significantly increased. This has, in turn, very significantly increased the impact of uncertainty in the system, so that ignoring it (as traditionally done by taking average point estimates) risks significant cost increases.

[21] This had made it necessary to resort to appropriate mathematical modeling techniques to properly take uncertainty into account, such as: The combination of the (already, many) traditional forms of UC problems with the several (old and) new forms of uncertainty gives rise to the even larger family of Uncertain Unit Commitment[4] (UUC) problems, which are currently at the frontier of applied and methodological research. ^ A study of the economic shutdown of generating units in daily dispatchTransactions of the American Institute of Electrical Engineers Power Apparatus and Systems ^ Short-term scheduling of thermal-electric generators using Lagrangian relaxationOperations Research ^ Unit commitment – a bibliographical surveyIEEE Transaction On Power Systems ^ a b M. Tahanan, W. van Ackooij, A. Frangioni, F. Lacalandra. Large-scale Unit Commitment under uncertainty, 4OR 13(2), 115–171, 2015. ^ PLEXOS® Integrated Energy Model ^ Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management

^ Electricity markets: Pricing, structures and Economics ^ Mathematical programming and electricity marketsTOP ^ a b Optimal transmission switchingIEEE Transactions on Power Systems ^ Strategic bidding in competitive electricity markets: a literature surveyProceedings IEEE PES Summer Meeting ^ Congestion influence on bidding strategies in an electricity marketIEEE Transactions on Power Systems ^ Optimal response of an oligopolistic generating company to a competitive pool-based electric power marketIEEE Transactions on Power Systems ^ Optimal response of a thermal unit to an electricity spot marketIEEE Transactions on Power Systems ^ Daily scheduling with transmission constraints: A new class of algorithmsIEEE Transactions on Power Systems ^ Tight and Compact MILP Formulation of Start-Up and Shut-Down Ramping in Unit CommitmentIEEE Transactions on Power Systems ^ Solving Nonlinear Single-Unit Commitment Problems with Ramping ConstraintsOperations Research

^ Solving the hydro unit commitment problem via dual decomposition and sequential quadratic programmingIEEE Transactions on Power Systems ^ Solving the hydrothermal scheduling problem considering network constraints.Electric Power Systems Research ^ A MILP approach for short-term hydro scheduling and unit commitment with head-dependent reservoirIEEE Transactions on Power Systems ^ a b Integration of Green and Renewable Energy in Electric Power Systems ^ Co-optimization of generation unit commitment and transmission switching with − 1 reliabilityIEEE Transactions on Power Systems ^ Load ForecastingApplied Mathematics for Restructured Electric Power Systems ^ Electric load forecasting methods: Tools for decision makingEuropean Journal of Operational Research Vikram Kumar Kamboj, S. K. Bath, J. S. Dhillon, “Solution of non-convex economic load dispatch problem using Grey Wolf Optimizer”, Neural Computing and Applications (ISSN: 1433-3058), Vol.25, No. 5, July 2015.