A Markov model of solar energy space and hot water heating systems

This paper presents a Markov model approach to the generalized solar energy space heating performance analysis problem. Specifically, Markov chain models are developed to represent ambient temperature, insolation, hot water load and system performance. From the Markov transition probability matrices for these variables, long-term expected performance is calculated. The theoretical development is implemented in FORTRAN IV on a Control Data 6400 Computer System. Computational experience gained, using STOLAR 3.1 (STOchastic soLAR energy systems model), indicates the stochastic approach requires approximately five per cent of the time necessary for standard dynamic simulation approaches with comparable performance results. The method also compared favorably with FCHART, a simplified design procedure.