Advanced building energy management based on a two-stage receding horizon optimization

Status of Social Competencies of Power Engineers in the Context of Forming the Concept of an Intelligent Network or Smart Grid

“…Getting important opportunities for consumers means also a certain level of responsibility [3,4,5,6]. Therefore, it is obvious that power grids (power supply networks) become intelligent not so much due to the technical equipment, as due to a man and his willingness to organize his behavior accordingly (so that the society could only benefit from it).…”

Load forecasting and dispatch optimisation for decentralised co-generation plant with dual energy storage

“…Based upon extensive experiments, the results indicate that the introduction of separate horizons for economic dispatch and unit commitment is more effective in terms of costs and solution structure than considering heuristics over a longer horizon. The suggested approach provides a useful alternative to [13] when considering trade-offs between complexity and horizon length in rolling-horizon energy optimisation problems, and provides a useful contribution to this area. In addition, the results obtained suggest that the optimisation problem is significantly harder to solve during Summer months than in Winter months due to the increased chance of the plant being uncommitted.…”

“…The main decision variables considered in the optimisation are controllable loads (both deferrable and proportionally controllable), dispatchable generation, battery storage and grid power exchange. A novel feature of Gruber's [13] work is the separation of the optimisation problem into two distinct phases and timescales to enable consideration of a longer horizon (24 hour) with high temporal resolution (5 minutes). In the first phase a rough-grained optimisation is solved over a 24 hour ahead period using an hourly time resolution.…”

“…The two-stage approach are shown to be an effective means to consider longer optimisation horizons with relatively high temporal resolutions, and the computational overheads are shown to be low (< 1 second per phase) using a modern numerical solver on a modern PC. Gruber [13] states that prediction accuracy has an impact on the quality of the optimisation, but does not provide a solution as to how to obtain the required demand predictions.…”

“…Gruber [13] describe and test a two-stage receding horizon optimisation problem for building energy management. The focus here is principally upon electrical energy management in the building.…”