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Abstract
This paper presents a modified and novel form of the conventional short-term hydrothermal scheduling problem by incorporating the effects of adding the photovoltaic energy source to the conventional grid. A photovoltaic energy source is intermittent in nature, therefore, to determine the optimal power contribution of the photovoltaic source towards the economic dispatch problem, a detailed strategy is presented in this paper. The proposed design method includes the forecasting of the photovoltaic system’s parameters using the Auto-Regressive Integrated Moving Average (ARIMA) model. The analytical model is developed based on the fractional integral polynomials for studying the characteristics of the single photovoltaic module. The optimization of power allocation in the system consisting of conventional and non-conventional energy sources is highly non-linear and classical deterministic methods can not be guaranteed to determine the optimal solution for economic power dispatch. The global optima of such non-linear and non-convex problems can be determined using swarm-based intelligence techniques. This paper presents accelerated particle swarm optimization and the firefly algorithm to determine a solution for short-term non-linear scheduling problems. The multiple test cases have been presented to demonstrate the effectiveness of the proposed solution over classical methods. The overall generation cost of the selected hybrid system is reduced using the proposed methods while meeting the generation constraints of each energy source. Moreover, due to the stochastic nature of the meta-heuristic techniques, a comprehensive statistical comparison, based on the independent T-test results, is also presented to highlight the algorithm which performs better for selected scheduling problems. It has been demonstrated that accelerated particle swarm optimization gives lower mean generation cost of the system whereas the execution time of the firefly algorithm is better compared to its counterpart.
Highlights
The addition of the renewable energy resources to the conventional scheduling problem demands the up gradation of the objective function and the certain constraints related to the solar power
This section covers the detailed discussion of the short term hydrothermal scheduling problem (STHTS), TABLE 5
The forecasting of the PV input parameters and the mathematical modeling of the PV module give accurate results regarding the solar share towards the dispatch problem incorporating the effect of the atmospheric conditions on the output power of the PV source
Summary
All the above mentioned work contributes effectively towards solution of the conventional short term hydrothermal scheduling problem by using the different algorithms but with the increasing number of the distributed generation systems being integrated to the grid, the problem of adjusting these renewable energy sources with the conventional ones is of the special interest and the research is still in progress to develop the certain scenarios in order to compensate the inclusion of these renewable energy resources to the existing systems. The work in [21] uses the robust optimization technique to solve the dispatch problem and uses the hybrid energy system which consists of the conventional (thermal and hydro) and non conventional sources (wind and solar) as the test case. We have to optimally select the value of γabs with in these two extremes to optimize the behavior of the algorithm for the given optimization problem [33]
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