2,588 research outputs found
Commitment and Dispatch of Heat and Power Units via Affinely Adjustable Robust Optimization
The joint management of heat and power systems is believed to be key to the
integration of renewables into energy systems with a large penetration of
district heating. Determining the day-ahead unit commitment and production
schedules for these systems is an optimization problem subject to uncertainty
stemming from the unpredictability of demand and prices for heat and
electricity. Furthermore, owing to the dynamic features of production and heat
storage units as well as to the length and granularity of the optimization
horizon (e.g., one whole day with hourly resolution), this problem is in
essence a multi-stage one. We propose a formulation based on robust
optimization where recourse decisions are approximated as linear or
piecewise-linear functions of the uncertain parameters. This approach allows
for a rigorous modeling of the uncertainty in multi-stage decision-making
without compromising computational tractability. We perform an extensive
numerical study based on data from the Copenhagen area in Denmark, which
highlights important features of the proposed model. Firstly, we illustrate
commitment and dispatch choices that increase conservativeness in the robust
optimization approach. Secondly, we appraise the gain obtained by switching
from linear to piecewise-linear decision rules within robust optimization.
Furthermore, we give directions for selecting the parameters defining the
uncertainty set (size, budget) and assess the resulting trade-off between
average profit and conservativeness of the solution. Finally, we perform a
thorough comparison with competing models based on deterministic optimization
and stochastic programming.Comment: 31 page
Genesis of Iron Pans in Bronze Age Mounds in Denmark
Genesis of Iron Pans in Bronze Age Mounds in Denmar
A novel bidding method for combined heat and power units in district heating systems
We propose a bidding method for the participation of combined heat and power
(CHP) units in the day-ahead electricity market. More specifically, we consider
a district heating system where heat can be produced by CHP units or heat-only
units, e.g., gas or wood chip boilers. We use a mixed-integer linear program to
determine the optimal operation of the portfolio of production units and
storages on a daily basis. Based on the optimal production of subsets of units,
we can derive the bidding prices and amounts of electricity offered by the CHP
units for the day-ahead market. The novelty about our approach is that the
prices are derived by iteratively replacing the production of heat-only units
through CHP production. This results in an algorithm with a robust bidding
strategy that does not increase the system costs even if the bids are not won.
We analyze our method on a small realistic test case to illustrate our method
and compare it with other bidding strategies from literature, which consider
CHP units individually. The analysis shows that considering a portfolio of
units in a district heating system and determining bids based on replacement of
heat production of other units leads to better results
- âŚ