15,101 research outputs found
Distributed Market Clearing Approach for Local Energy Trading in Transactive Market
This paper proposes a market clearing mechanism for energy trading in a local
transactive market, where each player can participate in the market as seller
or buyer and tries to maximize its welfare individually. Market players send
their demand and supply to a local data center, where clearing price is
determined to balance demand and supply. The topology of the grid and
associated network constraints are considered to compute a price signal in the
data center to keep the system secure by applying this signal to the
corresponding players. The proposed approach needs only the demanded/supplied
power by each player to reach global optimum which means that utility and cost
function parameters would remain private. Also, this approach uses distributed
method by applying local market clearing price as coordination information and
direct load flow (DLF) for power flow calculation saving computation resources
and making it suitable for online and automatic operation for a market with a
large number of players. The proposed method is tested on a market with 50
players and simulation results show that the convergence is guaranteed and the
proposed distributed method can reach the same result as conventional
centralized approach.Comment: Accepted paper. To appear in PESGM 2018, Portland, OR, 201
Disaggregated Bundle Methods for Distributed Market Clearing in Power Networks
A fast distributed approach is developed for the market clearing with
large-scale demand response in electric power networks. In addition to
conventional supply bids, demand offers from aggregators serving large numbers
of residential smart appliances with different energy constraints are
incorporated. Leveraging the Lagrangian relaxation based dual decomposition,
the resulting optimization problem is decomposed into separate subproblems, and
then solved in a distributed fashion by the market operator and each aggregator
aided by the end-user smart meters. A disaggregated bundle method is adapted
for solving the dual problem with a separable structure. Compared with the
conventional dual update algorithms, the proposed approach exhibits faster
convergence speed, which results in reduced communication overhead. Numerical
results corroborate the effectiveness of the novel approach.Comment: To appear in GlobalSIP 201
Distributed Stochastic Market Clearing with High-Penetration Wind Power
Integrating renewable energy into the modern power grid requires
risk-cognizant dispatch of resources to account for the stochastic availability
of renewables. Toward this goal, day-ahead stochastic market clearing with
high-penetration wind energy is pursued in this paper based on the DC optimal
power flow (OPF). The objective is to minimize the social cost which consists
of conventional generation costs, end-user disutility, as well as a risk
measure of the system re-dispatching cost. Capitalizing on the conditional
value-at-risk (CVaR), the novel model is able to mitigate the potentially high
risk of the recourse actions to compensate wind forecast errors. The resulting
convex optimization task is tackled via a distribution-free sample average
based approximation to bypass the prohibitively complex high-dimensional
integration. Furthermore, to cope with possibly large-scale dispatchable loads,
a fast distributed solver is developed with guaranteed convergence using the
alternating direction method of multipliers (ADMM). Numerical results tested on
a modified benchmark system are reported to corroborate the merits of the novel
framework and proposed approaches.Comment: To appear in IEEE Transactions on Power Systems; 12 pages and 9
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Chain: A Dynamic Double Auction Framework for Matching Patient Agents
In this paper we present and evaluate a general framework for the design of
truthful auctions for matching agents in a dynamic, two-sided market. A single
commodity, such as a resource or a task, is bought and sold by multiple buyers
and sellers that arrive and depart over time. Our algorithm, Chain, provides
the first framework that allows a truthful dynamic double auction (DA) to be
constructed from a truthful, single-period (i.e. static) double-auction rule.
The pricing and matching method of the Chain construction is unique amongst
dynamic-auction rules that adopt the same building block. We examine
experimentally the allocative efficiency of Chain when instantiated on various
single-period rules, including the canonical McAfee double-auction rule. For a
baseline we also consider non-truthful double auctions populated with
zero-intelligence plus"-style learning agents. Chain-based auctions perform
well in comparison with other schemes, especially as arrival intensity falls
and agent valuations become more volatile
Revisiting minimum profit conditions in uniform price day-ahead electricity auctions
We examine the problem of clearing day-ahead electricity market auctions
where each bidder, whether a producer or consumer, can specify a minimum profit
or maximum payment condition constraining the acceptance of a set of bid curves
spanning multiple time periods in locations connected through a transmission
network with linear constraints. Such types of conditions are for example
considered in the Spanish and Portuguese day-ahead markets. This helps
describing the recovery of start-up costs of a power plant, or analogously for
a large consumer, utility reduced by a constant term. A new market model is
proposed with a corresponding MILP formulation for uniform locational price
day-ahead auctions, handling bids with a minimum profit or maximum payment
condition in a uniform and computationally-efficient way. An exact
decomposition procedure with sparse strengthened Benders cuts derived from the
MILP formulation is also proposed. The MILP formulation and the decomposition
procedure are similar to computationally-efficient approaches previously
proposed to handle so-called block bids according to European market rules,
though the clearing conditions could appear different at first sight. Both
solving approaches are also valid to deal with both kinds of bids
simultaneously, as block bids with a minimum acceptance ratio, generalizing
fully indivisible block bids, are but a special case of the MP bids introduced
here. We argue in favour of the MP bids by comparing them to previous models
for minimum profit conditions proposed in the academic literature, and to the
model for minimum income conditions used by the Spanish power exchange OMIE
Simulating interbank payment and securities settlement mechanisms with the BoF-PSS2 simulator
The simulation technique provides a new means for analysing complex interdependencies in payment and securities settlement processing. The Bank of Finland has developed a payment and settlement system simulator (BoF-PSS2) that can be used for constructing simulation models of payment and securities settlement systems. This paper describes the main elements of payment and settlement systems (system structures, interdependencies, processing steps, liquidity consumption, cost and risk dimensions) and how these can be treated in simulation studies. It gives also examples on how these elements have been incorporated in the simulator, as well as an overview of the structure and the features of the BoF-PSS2 simulator.simulations; simulator; payment systems; clearing/settlement; liquidity
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