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The convolution-superposition dose calculation algorithm utilized by theRayStation Treatment Planning System (TPS) necessitates that a model of the beam becreated for every linac energy during the TPS commissioning process. This is achievedwith the user measuring depth dose curves and beam profiles for a variety of beamgeometries for each energy; the acquired dataset is then imported into the TPS. TheRayStation beam commissioning process involves generation of a set of values for anumber of adjustable parameters with the main objective of creating a model thatprovides a close match between the measured and calculated PDD curves and beamprofiles. The resulting photon energy spectrum, deduced from the PDD data, representsone of such adjustable parameters. While directly affecting dose calculations, it can onlybe verified through comparison of the measured and calculated PDD curves obtained in auniform medium of the water phantom.Verification of the dose calculation algorithm accuracy in heterogeneous mediumis a required part of the treatment planning system (TPS) commissioning process. Apartfrom validation of the dose calculation algorithm, it is also a test of the beam model accuracy. ArcCheck QA phantom equipped with inserts representative of materials withvarious densities, including those significantly different from that of water, were utilizedfor this purpose. The sensitivity of this test to change the modeled beam spectrum wasinvestigated for multiple configurations of the inserts, characterizing changes to theprimary beam attenuation and those affecting both the primary and scatteredcontributions.The photon beam spectra were adjusted in the TPS commissioning module toyield effective energies below or above the effective energy of the TPS modeled beam of2MV. For the homogeneous phantom errors >2% were detected only when the spectrumchanged significantly, beyond the clinically acceptable variations in PDD curves.Similarly, for heterogenous phantom configurations, errors >2% were detected for spectramodeled with effective energy of 1.6 MeV and above 2.5 MeV. Furthermore, thepresence of high-density inserts was shown to be more sensitive to change in beamspectra than that of low density inserts. These effects were due to significant change inabsorption of the correspondingly softened or hardened photon beams.In configurations investigating the combined attenuation and scatter effects, theion chamber signal did change with the beam spectrum but was fairly impervious to thespecific scattering material. Practically speaking, for relatively small changes in spectranot leading to drastic changes to the calculated PDDs, these small deviations would notbe detectable with the investigated test of a point dose measurement, with variousconfigurations of heterogeneous ArcCheck inserts.

Solar energy is a good alternative in remote microgrids because it is readily available in remote area and also reduces pollution due to conventional sources of energy. However, due to the presence of clouds, the solar energy available is intermittent in nature and therefore, it is not completely reliable. The variation of solar energy is compensated using conventional sources such as diesel generator. The operation of diesel generator is not economical when it needs to operate to compensate the variation. Therefore, forecasting of renewable energy of day ahead helps to schedule the generation economically. Different forecast technologies currently available utilize different weather information and satellite information for day ahead forecasting which is not readily available in remote areas. Therefore, an easy to implement forecasting method for day ahead forecasting in remote areas for remote microgrids is required. The objective of this thesis was to develop a forecasting method for utilization in remote microgrid. The Markov Switching Model considers the past solar irradiance data available, clear sky irradiance and Fourier basis functions to create linear models which consider three regimes for a day. Those three regimes are high energy regime when there is no cloud interrupting the sun, medium energy regime when the cloud is medium and low energy regime when the sky is highly cloudy. The transition from one energy regime to another regime is dependent upon the probability transition matrix which shows high probability xiv of the solar irradiance remaining in the same energy level. Therefore, considering the beginning four hours of sunlight, the solar irradiance for the day ahead was determined. This forecasted value of solar irradiance was utilized for energy management in the remote microgrid. The cost of operation of energy management for a year using forecasted solar data was compared against a baseline energy management. The cost of operation of energy management using forecasted solar irradiance was found to be less than the energy management without solar irradiance forecasting. This shows that the irradiance forecasting can be done using freely available resources using the Markov Switching Model. And forecasted irradiance could decrease the cost of operation of the microgrids by economical operation of the generation units.