1,201 research outputs found
Risk Limiting Dispatch with Ramping Constraints
Reliable operation in power systems is becoming more difficult as the
penetration of random renewable resources increases. In particular, operators
face the risk of not scheduling enough traditional generators in the times when
renewable energies becomes lower than expected. In this paper we study the
optimal trade-off between system and risk, and the cost of scheduling reserve
generators. We explicitly model the ramping constraints on the generators. We
model the problem as a multi-period stochastic control problem, and we show the
structure of the optimal dispatch. We then show how to efficiently compute the
dispatch using two methods: i) solving a surrogate chance constrained program,
ii) a MPC-type look ahead controller. Using real world data, we show the chance
constrained dispatch outperforms the MPC controller and is also robust to
changes in the probability distribution of the renewables.Comment: Shorter version submitted to smartgrid comm 201
Recommended from our members
An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Efficient Decentralized Economic Dispatch for Microgrids with Wind Power Integration
Decentralized energy management is of paramount importance in smart
microgrids with renewables for various reasons including environmental
friendliness, reduced communication overhead, and resilience to failures. In
this context, the present work deals with distributed economic dispatch and
demand response initiatives for grid-connected microgrids with high-penetration
of wind power. To cope with the challenge of the wind's intrinsically
stochastic availability, a novel energy planning approach involving the actual
wind energy as well as the energy traded with the main grid, is introduced. A
stochastic optimization problem is formulated to minimize the microgrid net
cost, which includes conventional generation cost as well as the expected
transaction cost incurred by wind uncertainty. To bypass the prohibitively
high-dimensional integration involved, an efficient sample average
approximation method is utilized to obtain a solver with guaranteed
convergence. Leveraging the special infrastructure of the microgrid, a
decentralized algorithm is further developed via the alternating direction
method of multipliers. Case studies are tested to corroborate the merits of the
novel approaches.Comment: To appear in IEEE GreenTech 2014. Submitted Sept. 2013; accepted Dec.
201
Recommended from our members
Increasing thermal plant flexibility in a high renewables power system
Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability.
This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified
An Efficient Primal-Dual Approach to Chance-Constrained Economic Dispatch
To effectively enhance the integration of distributed and renewable energy
sources in future smart microgrids, economical energy management accounting for
the principal challenge of the variable and non-dispatchable renewables is
indispensable and of significant importance. Day-ahead economic generation
dispatch with demand-side management for a microgrid in islanded mode is
considered in this paper. With the goal of limiting the risk of the
loss-of-load probability, a joint chance constrained optimization problem is
formulated for the optimal multi-period energy scheduling with multiple wind
farms. Bypassing the intractable spatio-temporal joint distribution of the wind
power generation, a primal-dual approach is used to obtain a suboptimal
solution efficiently. The method is based on first-order optimality conditions
and successive approximation of the probabilistic constraint by generation of
p-efficient points. Numerical results are reported to corroborate the merits of
this approach.Comment: Appeared in 2014 North American Power Symposiu
- …