Deterministic and Stochastic Economic Modeling of Hybrid Power Supply System with Photovoltaic Generators

Relevance of research. Due to the rapid deployment of the non-dispatchable (intermittent) generation sources in the smart grid, such as integration of the photovoltaic power plants and wind turbines in the distribution systems; this caused a problem of the uncertainty increase of simulation results for decision-making for power supply systems, these uncertainties of power systems are getting more and more notice. At the same time, the classical power systems models cannot give accurate simulation results. Wherein; it became necessary to define new models to represent the specific parameters of power system. wherein; this research reveals to the benefits of using probabilistic mathematical approaches to define and calculate the specific economic parameters, as well as the technical parameters for power supply system with the integration renewable energy generators, which are characterising by randomness and uncertainty due to the high penetration to the renewables. Monte Carlo Method, and Point Estimation Method are used to handle the uncertainties of renewable energy resources. The standard functions to represent the stochastic parameters of the model are analyzed with the use of three-point estimation technique for the distribution functions of their probable values. A synthetic skewed probability density function was analytically constructed basing on the standard normal distribution, which is suitable for analytic representation of the predicted and/or statistical random sampling of the uncertain model parameters of energy system with renewables, and analytical expressions were obtained to compute the moments of proposed synthetic probability function. Relationship of work with scientific programs, plans, themes. is to demonstrate the possibility of describing the input parameters of the simulation Deterministic and Stochastic Modeling by probability Density Functions by the use of three-point approximation techniques and to obtain analytical expressions for the characteristics of such distributions, suitable for non-iterative (as opposed to Monte Carlo Method) probabilistic method applications, namely the Point Estimation Method. Purpose and tasks of the research. Increasing the simulation accuracy results for estimation economic and technical parameters characterising photovoltaic power plant based on based on the life cycle model; as well as development of different algorithms based on deterministic and stochastic modeling of power system with non-dispatchable sources and minimize the computation time. Object of research. Processes of determining the estimated technical and economic parameters characterising a photovoltaic power plant located in Ukraine basing on stochastic modeling. Subject of research. Use of the Monte Carlo Method and Point Estimation Method to estimate the various economic and technical information characteristic of alternative power plants in order to obtain accurate simulation results. Practical value of the results. Practical techniques of the three-point approximation are used to construct the probability density function of the model uncertain (stochastic) parameter, which dominantly influences the modeling result: an event occurrence probability, the result attainability, whatsoever. This technique is an effective tool for the practical evaluating of an uncertain value of a technological or economic factor of material and/or economic object, and widely used for overall Levelized Energy Cost (LCOE – LEC) which is directly or indirectly engaged into analytic representation of the power systel model. Usually, the model of a kind is designed to solve technical and/or economic problem by means of Deterministic and Stochastic Modeling. Scientific novelty of the obtained results is the development of algorithms and mathematical solutions using a probabilistic approach basing Point Estimation Method instead of Monte Carlo Melthod to obtain more accurate estimation simulation results, as well as to obtain computational results in less time for useful decision-making in alternative power plant projects

Northport 100% Renewable Energy Feasibility Study

Situated in northern Michigan, Northport and Leelanau Township comprise a small community with a significant tourist industry, agricultural presence and natural beauty. A local non-profit, Northport Energy Action Taskforce (NEAT) has articulated a goal to transition their community to 100% locally-generated renewable energy. This feasibility study focused on electricity and included research on the disposition of the community as well as technical analyses of renewable energy systems that would be suitable for attaining the goal. The team created a household survey, followed by resource assessments for wind and solar power, as well as site identification for renewable energy systems. The survey results showed that the community is open to the possibility of increasing the share of renewable energy in the Township, with 71% of respondents expressing support to the initiative. Based on the resource assessment results, we concluded that the resource availability in the location is enough to provide the required electricity to meet the 100% goal. Land availability makes feasible the deployment of large-scale systems needed for the plan. Additional analyses of energy-efficiency potential and energy policies were conducted to inform the development of three scenarios for achieving 100% local renewable energy.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/111054/1/Northport Report_2015.pd

On using Lazard's projection in CAD construction

In 1994 Lazard proposed an improved projection operation for cylindrical algebraic decomposition (CAD). For the proof he introduced a certain notion of valuation of a multivariate Puiseux series at a point. However a gap in one of the key supporting results for the improved projection was subsequently noticed. In this paper we show that Lazard's projection is valid for CAD construction for so-called well-oriented polynomial sets. Our proof does not make use of Lazard's notion of valuation, however.17 page(s