19-03-2014, 12:04 PM
[b]Market-Based Generation and Transmission Planning With Uncertainties[/b]
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Abstract
This paper presents a stochastic coordination of
generation and transmission expansion planning model in a com-
petitive electricity market. The Monte Carlo simulation method
is applied to consider random outages of generating units and
transmission lines as well as inaccuracies in the long-term load
forecasting. The scenario reduction technique is introduced for
reducing the computational burden of a large number of planning
scenarios. The proposed model assumes a capacity payment mech-
anism and a joint energy and transmission market for investors’
costs recovery. The proposed approach simulates the decision
making behavior of individual market participants and the ISO.
It is an iterative process for simulating the interactions among
GENCOs, TRANSCOs and ISO. The iterative process might be
terminated by the ISO based on a pre-specified stopping criterion.
The case studies illustrate the applications of proposed stochastic
method in a coordinated generation and transmission planning
problem when considering uncertainties.
INTRODUCTION
WITH the advent of restructuring, there is a general
consensus that generation expansion can be driven by
prices but the same principle may not apply to the transmis-
sion expansion [1], [2]. However, power system constraints
such as network flow limits, load demands, and reliability
requirements have bundled the two planning problems when
considering practical and feasible planning solutions. The
generation and transmission planning problems are coordinated
by an independent entity (e.g., ISO) to assure the most reliable
and economical solutions. We proposed a model in [4] for
the coordination of the two planning problems by applying a
joint energy and transmission market and a capacity payment
mechanism for both transmission and generation facilities.
ISO’s Reliability Check Problem
The purpose of the reliability check problem is to evaluate
the reliability of the planning system and calculate capacity sig-
nals for promoting the addition of generating units and trans-
mission lines. In our model, loss of energy probability (LOEP)
is adopted to measure the system reliability. LOEP is defined
as the ratio of the expected unserved energy (EUE) to the total
energy demand of the system [14], [15].
ISO’s Optimal Operation Problem
In this problem, the ISO will forecast the expected LMPs and
FMPs by solving the dc optimal power flow model [17]. The
objective of the optimal power flow problem is to maximize the
revealed surplus based on submitted bids for generation, bids for
flowgates, and demand. The revealed surplus is defined as the
difference between consumption payments based on accepted
bids and production costs.
CONCLUSION
By applying Monte Carlo simulation and scenario reduction
techniques, we proposed a stochastic long-term generation
and transmission capacity planning formulation for repre-
senting uncertainties in the availability of generating units and
transmission lines, and inaccuracies in load forecasting. The
Benders decomposition and Lagrangian relaxation methods
are applied to simulate the interaction among market partici-
pants (GENCOs and TRANSCO), and the interaction between
the ISO and market participants in the long-term planning
process under competitive electricity market. This stochastic
market-based approach could provide signals to investors on
the location of new generation and transmission facilities and
help system planners, regulators, and local authorities concur
on transmission planning.