Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization. In particular, the proposed tool has been developed for scenarios, where photovoltaic generators and storage units (compressed-air-energy-storage and super-capacitors) are used to supply energy demands in a region characterized by different house-holds considering different times and seasons. The constructed tool has been used to test impact of several factors (e.g. demand growth, efficiencies in PV panel and storage techniques) on the total cost of the system. Initial results look quite promising. An increase in the concentrations of greenhouse gases is believed to be a major cause for climate changes in temperature (global warming), storm severity, and sea level. And, greenhouse gas emissions come primarily from the combustion of fossil fuels. For example, energy-related carbon dioxide (CO 2 ) emissions, resulting from the combustion of petroleum, coal, and natural gas, represented 82 percent of the total U.S. greenhouse gas emissions in 2006 <http://www.eia.doe.gov/bookshelf/brochures/greenhouse/Chapter1.htm>. To avoid damaging climate change, there is worldwide agreement on the need to reduce greenhouse emissions. For example, European Union (EU) has agreed to reduce greenhouse gases by 30% by 2020 (Freris and Infield 2008) . Similarly, in March 2009, the US House of Delegates voted for the measure, which would require the state to cut greenhouse gases by 25 percent by 2020, and the Senate approved it. To reduce greenhouse gas emissions from the combustion of fossil fuels, providing an energy share from renewable sources such as sunshine, wind, water, and bio-fuel is critical. Furthermore, energy potential from these renewable resources is enormous. For example, on average, the rate of solar radiation intercepted by the earth's surface amounts to a staggering average power of 20MW per person considering the present world population (Freris and Infield 2008). However, unlike fossil-fueled generation, renewable energy resources are geographically distributed and highly dependent (intermittent) on the location, changing weather and climate conditions, which makes their direct control extremely challenging and requires storage units as an additional concern. Energy storage transforms an intermittent, renewable energy resource into one that has firm capacity value, and provides us with several benefits. First, excess energy stored when renewable energy resources (e.g. sun's rays) are strong can be used when the generated energy is insufficient (i.e., the sun is not shining or obscured by clouds) or sold to the grid in accordance with market prices for energy. Second, with energy storage, renewable dispatch can be controlled to reduce or avoid congestion, relieving pressure on transmission systems and reducing the need for traditional wires infrastructure. Third, many storage technologies can provide other services, such as 1511 978-1-4244-5771-7/09/$26.00 ©2009 IEEE
A hybrid simulation model for photovoltaic generators and storage units is presented in REF ).
Hybrid simulation and optimization-based capacity planner for integrated photovoltaic generation with storage units
Proceedings of the 2009 Winter Simulation Conference (WSC)
Proceedings of the 2009 Winter Simulation Conference (WSC)
Computer Science