A rolling-horizon algorithm is proposed for optimizing the operating schedule of a given cogeneration energy system while taking into account time-variable loads, tariffs and ambient conditions, as well as yearly fiscal incentives. The presented algorithm is based on the Mixed Integer Linear Programming (MILP) model developed by the authors for optimizing the daily schedule of cogeneration systems and networks of heat and power plants. First the MILP model is extended to optimize the weekly operation schedule to better manage the heat-cold storage systems. However, in order to account for the European qualification framework for high efficiency cogeneration, as well as for country-specific incentive policies, it is necessary to consider average yearly-basis energy saving indexes, thus requiring to tackle the problem for the whole year. Since the extension of the MILP model from one day to seven days already increases remarkably the computational requirements, a simple application of the same optimization approach to a whole year would be practically unfeasible; therefore, this work proposes a rolling-horizon algorithm in which a sequence of weekly MILP submodels is solved, while considering production and consumption estimates based on demand profiles from historical data. The results obtained for a real-world test case are reported and discussed.
- Combined heat and power (CHP)
- Fiscal incentives
- Heat storage
- Optimal scheduling
- Predictive strategy