Open AccessMaximising revenue via optimal control of a concentrating solar thermal power plant with limited storage capacity
Author(s) -
Cirocco Luigi Rocco,
Belusko Martin,
Bruno Frank,
Boland John,
Pudney Peter
Publication year - 2016
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2015.0244
Subject(s) - optimal control , thermal energy storage , maximum power principle , power (physics) , computer science , dynamic programming , mathematical optimization , power station , energy storage , pontryagin's minimum principle , revenue , power control , thermal power station , solar power , maximum principle , control (management) , control theory (sociology) , engineering , mathematics , electrical engineering , photovoltaic system , economics , ecology , physics , quantum mechanics , artificial intelligence , biology , accounting
Concentrating solar thermal power plants with thermal energy storage is a potential source of clean electrical power. This work has the same four optimal control modes established in a previous paper where Pontryagin's principle demonstrated that to maximise revenue from a plant with unlimited storage the optimal modes were to: (i) store all collected power, without generating; (ii) generate using collected power only; (iii) generate at maximum capacity using both collected and stored power; (iv) generate a maximum capacity, storing any surplus power. This paper presents an expanded analysis to cover a more realistic case where there is limited storage capacity, introducing 2 differences. First, it is sometimes necessary to discard power if the store is full. Second, the critical prices used to determine the optimal control can change whenever the store becomes full or empty. Again we use Pontragin's principle to derive necessary conditions for an optimal control and present an algorithm to find the sequence of critical prices required to construct it. The analysis gives more insight into the nature of the optimal control than mathematical programming or probabilistic search techniques, and the calculation is fast‐finding the optimal control for a yearlong operation in about 30 seconds.