23,126 research outputs found
A New Approach to Electricity Market Clearing With Uniform Purchase Price and Curtailable Block Orders
The European market clearing problem is characterized by a set of
heterogeneous orders and rules that force the implementation of heuristic and
iterative solving methods. In particular, curtailable block orders and the
uniform purchase price (UPP) pose serious difficulties. A block is an order
that spans over multiple hours, and can be either fully accepted or fully
rejected. The UPP prescribes that all consumers pay a common price, i.e., the
UPP, in all the zones, while producers receive zonal prices, which can differ
from one zone to another.
The market clearing problem in the presence of both the UPP and block orders
is a major open issue in the European context. The UPP scheme leads to a
non-linear optimization problem involving both primal and dual variables,
whereas block orders introduce multi-temporal constraints and binary variables
into the problem. As a consequence, the market clearing problem in the presence
of both blocks and the UPP can be regarded as a non-linear integer programming
problem involving both primal and dual variables with complementary and
multi-temporal constraints.
The aim of this paper is to present a non-iterative and heuristic-free
approach for solving the market clearing problem in the presence of both
curtailable block orders and the UPP. The solution is exact, with no
approximation up to the level of resolution of current market data. By
resorting to an equivalent UPP formulation, the proposed approach results in a
mixed-integer linear program, which is built starting from a non-linear integer
bilevel programming problem. Numerical results using real market data are
reported to show the effectiveness of the proposed approach. The model has been
implemented in Python, and the code is freely available on a public repository.Comment: 15 pages, 7 figure
A compensation-based pricing scheme in marketswith non-convexities
A compensation-based pricing scheme is a market clearing mechanism that may be applied when a uniform, linear pricing scheme cannot support equilibrium allocations in the auction markets. We analyze extensions of our previously proposed pricing scheme [14] to include various possible representations of bids that reflect some non-convex costs and constraints. We conclude with a discussion on directions for future research.auction design, electricity market, non-convex bids, minimum profit condition, unit commitment constraints
Comments on the RGGI Market Design
Auctions, carbon auctions, greenhouse gas auctions
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
figure
Probabilistic Model and Solution Algorithm for the Electricity Retailers in the Italian Market
The paper considers the problem of maximizing the profits of a retailer operating in the Italian electricity market. The problem consists in selecting the contracts portfolio and in defining the bidding strategy in the wholesales market while respecting the technical and regulatory constraints. A novel solution method based on a enhanced discovery of the search domain in the simulated annealing technique has been developed for its solution and a set of realistic test problems have been generated for its validation. The experimental results show that our method outperforms the standard simulated annealing by an improvement gap of 20,48% in average
Scenario-based Economic Dispatch with Uncertain Demand Response
This paper introduces a new computational framework to account for
uncertainties in day-ahead electricity market clearing process in the presence
of demand response providers. A central challenge when dealing with many demand
response providers is the uncertainty of its realization. In this paper, a new
economic dispatch framework that is based on the recent theoretical development
of the scenario approach is introduced. By removing samples from a finite
uncertainty set, this approach improves dispatch performance while guaranteeing
a quantifiable risk level with respect to the probability of violating the
constraints. The theoretical bound on the level of risk is shown to be a
function of the number of scenarios removed. This is appealing to the system
operator for the following reasons: (1) the improvement of performance comes at
the cost of a quantifiable level of violation probability in the constraints;
(2) the violation upper bound does not depend on the probability distribution
assumption of the uncertainty in demand response. Numerical simulations on (1)
3-bus and (2) IEEE 14-bus system (3) IEEE 118-bus system suggest that this
approach could be a promising alternative in future electricity markets with
multiple demand response providers
FlexAuc: Serving Dynamic Demands in a Spectrum Trading Market with Flexible Auction
In secondary spectrum trading markets, auctions are widely used by spectrum
holders (SHs) to redistribute their unused channels to secondary wireless
service providers (WSPs). As sellers, the SHs design proper auction schemes to
stimulate more participants and maximize the revenue from the auction. As
buyers, the WSPs determine the bidding strategies in the auction to better
serve their end users.
In this paper, we consider a three-layered spectrum trading market consisting
of the SH, the WSPs and the end users. We jointly study the strategies of the
three parties. The SH determines the auction scheme and spectrum supplies to
optimize its revenue. The WSPs have flexible bidding strategies in terms of
both demands and valuations considering the strategies of the end users. We
design FlexAuc, a novel auction mechanism for this market to enable dynamic
supplies and demands in the auction. We prove theoretically that FlexAuc not
only maximizes the social welfare but also preserves other nice properties such
as truthfulness and computational tractability.Comment: 11 pages, 7 figures, Preliminary version accepted in INFOCOM 201
- …