1,533 research outputs found
Achieving an optimal trade-off between revenue and energy peak within a smart grid environment
We consider an energy provider whose goal is to simultaneously set
revenue-maximizing prices and meet a peak load constraint. In our bilevel
setting, the provider acts as a leader (upper level) that takes into account a
smart grid (lower level) that minimizes the sum of users' disutilities. The
latter bases its decisions on the hourly prices set by the leader, as well as
the schedule preferences set by the users for each task. Considering both the
monopolistic and competitive situations, we illustrate numerically the validity
of the approach, which achieves an 'optimal' trade-off between three
objectives: revenue, user cost, and peak demand
A Community Microgrid Architecture with an Internal Local Market
This work fits in the context of community microgrids, where members of a
community can exchange energy and services among themselves, without going
through the usual channels of the public electricity grid. We introduce and
analyze a framework to operate a community microgrid, and to share the
resulting revenues and costs among its members. A market-oriented pricing of
energy exchanges within the community is obtained by implementing an internal
local market based on the marginal pricing scheme. The market aims at
maximizing the social welfare of the community, thanks to the more efficient
allocation of resources, the reduction of the peak power to be paid, and the
increased amount of reserve, achieved at an aggregate level. A community
microgrid operator, acting as a benevolent planner, redistributes revenues and
costs among the members, in such a way that the solution achieved by each
member within the community is not worse than the solution it would achieve by
acting individually. In this way, each member is incentivized to participate in
the community on a voluntary basis. The overall framework is formulated in the
form of a bilevel model, where the lower level problem clears the market, while
the upper level problem plays the role of the community microgrid operator.
Numerical results obtained on a real test case implemented in Belgium show
around 54% cost savings on a yearly scale for the community, as compared to the
case when its members act individually.Comment: 16 pages, 15 figure
Evaluating Resilience of Electricity Distribution Networks via A Modification of Generalized Benders Decomposition Method
This paper presents a computational approach to evaluate the resilience of
electricity Distribution Networks (DNs) to cyber-physical failures. In our
model, we consider an attacker who targets multiple DN components to maximize
the loss of the DN operator. We consider two types of operator response: (i)
Coordinated emergency response; (ii) Uncoordinated autonomous disconnects,
which may lead to cascading failures. To evaluate resilience under response
(i), we solve a Bilevel Mixed-Integer Second-Order Cone Program which is
computationally challenging due to mixed-integer variables in the inner problem
and non-convex constraints. Our solution approach is based on the Generalized
Benders Decomposition method, which achieves a reasonable tradeoff between
computational time and solution accuracy. Our approach involves modifying the
Benders cut based on structural insights on power flow over radial DNs. We
evaluate DN resilience under response (ii) by sequentially computing autonomous
component disconnects due to operating bound violations resulting from the
initial attack and the potential cascading failures. Our approach helps
estimate the gain in resilience under response (i), relative to (ii)
Bilevel aggregator-prosumers' optimization problem in real-time:A convex optimization approach
This paper proposes a Real-Time Market (RTM) platform for an aggregator and its corresponding prosumers to participate in the electricity wholesale market. The proposed energy market platform is modeled as a bilevel optimization problem where the aggregator and the prosumers are considered as self-interested agents. We present a convex optimization problem which can capture a subset of the set of global optima of the bilevel problem as its optimal solution
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