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Micropower System Modeling with Homer CHAPTER 15 MICROPOWER SYSTEM MODELING WITH HOMER TOM LAMBERT Mistaya Engineering Inc. PAUL GILMAN and PETER LILIENTHAL National Renewable Energy Laboratory 15.1 INTRODUCTION The HOMER Micropower Optimization Model is a computer model developed by the U.S. National Renewable Energy Laboratory (NREL) to assist in the design of micropower systems and to facilitate the comparison of power generation technol- ogies across a wide range of applications. HOMER models a power system’s phy- sical behavior and its life-cycle cost, which is the total cost of installing and operating the system over its life span. HOMER allows the modeler to compare many different design options based on their technical and economic merits. It also assists in understanding and quantifying the effects of uncertainty or changes in the inputs. A micropower system is a system that generates electricity, and possibly heat, to serve a nearby load. Such a system may employ any combination of electrical generation and storage technologies and may be grid-connected or autonomous, meaning separate from any transmission grid. Some examples of micropower sys- tems are a solar–battery system serving a remote load, a wind–diesel system serving an isolated village, and a grid-connected natural gas microturbine providing elec- tricity and heat to a factory. Power plants that supply electricity to a high-voltage transmission system do not qualify as micropower systems because they are not Integration of Alternative Sources of Energy, by Felix A. Farret and M. Godoy Simooes~ Copyright # 2006 John Wiley & Sons, Inc. 379 380 MICROPOWER SYSTEM MODELING WITH HOMER dedicated to a particular load. HOMER can model grid-connected and off-grid micropower systems serving electric and thermal loads, and comprising any com- bination of photovoltaic (PV) modules, wind turbines, small hydro, biomass power, reciprocating engine generators, microturbines, fuel cells, batteries, and hydrogen storage. The analysis and design of micropower systems can be challenging, due to the large number of design options and the uncertainty in key parameters, such as load size and future fuel price. Renewable power sources add further complexity because their power output may be intermittent, seasonal, and nondispatchable, and the availability of renewable resources may be uncertain. HOMER was designed to overcome these challenges. HOMER performs three principal tasks: simulation, optimization, and sensitivity analysis. In the simulation process, HOMER models the performance of a particular micropower system configuration each hour of the year to determine its technical feasibility and life-cycle cost. In the optimization process, HOMER simulates many different system configurations in search of the one that satisfies the technical con- straints at the lowest life-cycle cost. In the sensitivity analysis process, HOMER performs multiple optimizations under a range of input assumptions to gauge the effects of uncertainty or changes in the model inputs. Optimization determines the optimal value of the variables over which the system designer has control such as the mix of components that make up the system and the size or quantity of each. Sensitivity analysis helps assess the effects of uncertainty or changes in the variables over which the designer has no control, such as the average wind speed or the future fuel price. Figure 15.1 illustrates the relationship between simulation, optimization, and sensitivity analysis. The optimization oval encloses the simulation oval to represent the fact that a single optimization consists of multiple simulations. Similarly, the sensitivity analysis oval encompasses the optimization oval because a single sensi- tivity analysis consists of multiple optimizations. Sensitivity Analysis Optimization Simulation Figure 15.1 Conceptual relationship between simulation, optimization, and sensitivity analysis. SIMULATION 381 To limit input complexity, and to permit fast enough computation to make opti- mization and sensitivity analysis practical, HOMER’s simulation logic is less detailed than that of several other time-series simulation models for micropower systems, such as Hybrid2 [1], PV-DesignPro [2], and PV*SOL [3]. On the other hand, HOMER is more detailed than statistical models such as RETScreen [4], which do not perform time-series simulations. Of all these models, HOMER is the most flexible in terms of the diversity of systems it can simulate. In this chapter we summarize the capabilities of HOMER and discuss the ben- efits it can provide to the micropower system modeler. In Sections 15.2 through 15.4 we describe the structure, purpose, and capabilities of HOMER and introduce the model. In Sections 15.5 and 15.6 we discuss in greater detail the technical and economic aspects of the simulation process. A glossary defines many of the terms used in the chapter. 15.2 SIMULATION HOMER’s fundamental capability is simulating the long-term operation of a micro- power system. Its higher-level capabilities, optimization and sensitivity analysis, rely on this simulation capability. The simulation process determines how a parti- cular system configuration, a combination of system components of specific sizes, and an operating strategy that defines how those components work together, would behave in a given setting over a long period of time. HOMER can simulate a wide variety of micropower system configurations, com- prising any combination of a PV array, one or more wind turbines, a run-of-river hydro-turbine, and up to three generators, a battery bank, an ac–dc converter, an electrolyzer, and a hydrogen storage tank. The system can be grid-connected or autonomous and can serve ac and dc electric loads and a thermal load. Figure 15.2 shows schematic diagrams of some examples of the types of micro- power systems that HOMER can simulate. Systems that contain a battery bank and one or more generators require a dis- patch strategy, which is a set of rules governing how the system charges the battery bank. HOMER can model two different dispatch strategies: load-following and cycle-charging. Under the load-following strategy, renewable power sources charge the battery but the generators do not. Under the cycle-charging strategy, whenever the generators operate, they produce more power than required to serve the load with surplus electricity going to charge the battery bank. The simulation process serves two purposes. First, it determines whether the sys- tem is feasible. HOMER considers the system to be feasible if it can adequately serve the electric and thermal loads and satisfy any other constraints imposed by the user. Second, it estimates the life-cycle cost of the system, which is the total cost of installing and operating the system over its lifetime. The life-cycle cost is a convenient metric for comparing the economics of various system configurations. Such comparisons are the basis of HOMER’s optimization process, described in Section 15.3. Figure 15.2 Schematic diagrams of some micropower system types that HOMER models: (a)a diesel system serving an ac electric load; (b)aPV–battery system serving a dc electric load; (c)a hybrid hydro–wind–diesel system with battery backup and an ac–dc converter; (d)awind–diesel system serving electric and thermal loads with two generators, a battery bank, a boiler, and a dump load that helps supply the thermal load by passing excess wind turbine power through a resistive heater; (e)aPV–hydrogen system in which an electrolyzer converts excess PV power into hydrogen, which a hydrogen tank stores for use in a fuel cell during times of insufficient PV power; (f) a wind-powered system using both batteries and hydrogen for backup, where the hydrogen fuels an internal combustion engine generator; (g) a grid-connected PV system; (h) a grid-connected combined heat and power (CHP) system in which a microturbine produces both electricity and heat; (i) a grid-connected CHP system in which a fuel cell provides electricity and heat. 382 SIMULATION 383 Figure 15.2 (Continued) HOMER models a particular system configuration by performing an hourly time series simulation of its operation over one year. HOMER steps through the year one hour at a time, calculating the available renewable power, comparing it to the elec- tric load, and deciding what to do with surplus renewable power in times of excess, or how best to generate (or purchase from the grid) additional power in times of deficit. When it has completed one year’s worth of calculations, HOMER deter- mines whether the system satisfies the constraints imposed by the user on such quantities as the fraction of the total electrical demand served, the proportion of power generated by renewable sources, or the emissions of certain pollutants. HOMER also computes the quantities required to calculate the system’s life-cycle cost, such as the annual fuel consumption, annual generator operating hours, expected battery life, or the quantity of power purchased annually from the grid. The quantity HOMER uses to represent the life-cycle cost of the system is the total net present cost (NPC). This single value includes all costs and revenues that occur within the project lifetime, with future cash flows discounted to the present. The total net present cost includes the initial capital cost of the system components, the cost of any component replacements that occur within the project lifetime, the cost of maintenance and fuel, and the cost of purchasing power from the grid. Any revenue from the sale of power to the grid reduces the total NPC. In Section 15.6 we describe in greater detail how HOMER calculates the total NPC. For many types of micropower systems, particularly those involving intermittent renewable power sources, a one-hour time step is necessary to model the behavior 384 MICROPOWER SYSTEM MODELING WITH HOMER of the system with acceptable accuracy. In a wind–diesel–battery system, for exam- ple, it is not enough to know the monthly average (or even daily average) wind power output, since the timing and the variability of that power output are as impor- tant as its average quantity.
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