Flexibility provision by combined heat and power plants – An evaluation of benefits from a plant and system perspective

Variable renewable electricity generation is likely to constitute a large share of future electricity systems. In such electricity systems, the cost and resource efficiency can be improved by employing strategies to manage variations. This work investigates combined heat and power (CHP) plant flexibility as a variation management strategy in an energy system context, considering the operation and cost-competitiveness of CHP plants. An energy system optimization model with detailed representation of CHP plant flexibility is applied, covering the electricity and district heating sectors in one Swedish electricity price area. The results show that investments in CHP plants are dimensioned based on the demand for district heating rather than electricity. In the system studied, this implies that CHP plant capacity is small relative to electricity system variations, and variation management using CHP plants has a weak impact on the total system cost of supplying electricity and district heating. However, flexibility measures increase CHP plant competitiveness in scenarios with low system flexibility (assuming low availability of hydropower or no thermal energy storage) although investments in CHP capacity are sensitive to fuel cost. It is found that while district heating is the dominant CHP product (constituting 50%–90% of the annual CHP energy output), the dispatchable electricity supply has a high value and comprises around 60% of the annual CHP plant revenue. In all scenarios, operational flexibility of the boiler is more valuable than a flexible steam cycle power-to-heat ratio

Model predictive control for microgrid functionalities: review and future challenges

ABSTRACT: Renewable generation and energy storage systems are technologies which evoke the future energy paradigm. While these technologies have reached their technological maturity, the way they are integrated and operated in the future smart grids still presents several challenges. Microgrids appear as a key technology to pave the path towards the integration and optimized operation in smart grids. However, the optimization of microgrids considered as a set of subsystems introduces a high degree of complexity in the associated control problem. Model Predictive Control (MPC) is a control methodology which has been satisfactorily applied to solve complex control problems in the industry and also currently it is widely researched and adopted in the research community. This paper reviews the application of MPC to microgrids from the point of view of their main functionalities, describing the design methodology and the main current advances. Finally, challenges and future perspectives of MPC and its applications in microgrids are described and summarized.info:eu-repo/semantics/publishedVersio