TY - GEN
T1 - Optimal resource allocation and load scheduling for a multi-commodity smart energy system
AU - Blaauwbroek, N.
AU - Nguyen, H.P.
AU - Shi, H.
AU - Kamphuis, I.G.
AU - Kling, W.L.
AU - Konsman, M.J.
PY - 2015
Y1 - 2015
N2 - The increasing introduction of district heating systems together with hybrid energy appliances as heat pumps and micro-combined heat and power installations, results in new opportunities for optimizing the available resources in multi-commodity smart energy systems, including electricity, heat and gas. By `converting' forms of energy using hybrid energy appliances, and exploiting flexibility from local production and consumption, energy efficiency can be improved significantly. This paper introduces a multi-commodity smart energy system incorporating both heat and electricity and integrating various types of flexible appliances as well as hybrid energy appliances. A management strategy optimally allocates the available resources and flexibility, aiming to perform optimal supply and demand matching as well as to flatten out the net remaining supply or demand over time. The proposed method is applied to a test case, where simulation results confirm that the method forms a suitable solution for the management of the multi-commodity smart energy system.
AB - The increasing introduction of district heating systems together with hybrid energy appliances as heat pumps and micro-combined heat and power installations, results in new opportunities for optimizing the available resources in multi-commodity smart energy systems, including electricity, heat and gas. By `converting' forms of energy using hybrid energy appliances, and exploiting flexibility from local production and consumption, energy efficiency can be improved significantly. This paper introduces a multi-commodity smart energy system incorporating both heat and electricity and integrating various types of flexible appliances as well as hybrid energy appliances. A management strategy optimally allocates the available resources and flexibility, aiming to perform optimal supply and demand matching as well as to flatten out the net remaining supply or demand over time. The proposed method is applied to a test case, where simulation results confirm that the method forms a suitable solution for the management of the multi-commodity smart energy system.
U2 - 10.1109/PTC.2015.7232271
DO - 10.1109/PTC.2015.7232271
M3 - Conference contribution
BT - Proceedings of the IEEE PowerTech 2015 Conference, 29 June - 2 July 2015, Eindhoven, The Netherlands
ER -
