Risk-based maintenance scheduling of generating units in the deregulated environment considering transmission network congestion

Abstract

In restructured power systems, the traditional approaches of unit maintenance scheduling (UMS) need to undergo major changes in order to be compatible with new competitive structures. Performing the maintenance on generating units may decrease the security level of transmission network and result in electricity shortage in power system; as a result, it can impose a kind of cost on transmission network as called security cost. Moreover, taking off line a generating unit for performing maintenance can change power flow in some transmission lines, and may lead to network congestion. In this study, generating unit maintenance is scheduled considering security and congestion cost with N-1 examination for transmission lines random failures. The proposed UMS approach would lead to optimum operation of power system in terms of economy and security. To achieve this goal, the optimal power flow (OPF) compatible with market mechanism is implemented. Moreover, the electricity price discovery mechanism as locational marginal pricing (LMP) is restated to analyze the impacts of UMS on nodal electricity price. Considering security and congestion cost simultaneously, this novel approach can reveal some new costs which are imposed to transmission network on behalf of generation units; as a result, it provides a great opportunity to perform maintenance in a fair environment for both generating companies (GenCo) and transmission companies (TransCo). At the end, simulation results on nine-bus test power system demonstrate that by using this method, the proposed UMS can guarantee fairness among market participants including GenCos and TransCo and ensure power system security.

Security-constrained model for integrated power and natural-gas system

“…Prevailing constraints of a SCUC model based on DC power flows are: the power system balance, spinning reserve requirements, generating capacity limits, ramp rates, logic constraints, minimum up/down times, startup and shutdown trajectories, and power flows for pre-and post-contingency states. Since this problem has been widely studied, the reader is referred to [3] and [18][19][20][21] for detailed formulations.…”

“…This problem optimizes gas production, storage, and compression taking into account gas network constraints in pre- (20) and postcontingency (21).…”

“…The dual variables from (20) are denoted as l, and from (21) as k. The coupling constraints from which l and k are calculated correspond to the nodal balances (8) in pre-(l ¼ 0) and post-contingency (l ! 1) respectively.…”

Composite System Maintenance Coordination in a Smart Grid Considering Demand Response

“…Computing flows on transmission lines after optimal power flow (OPF) and fitting the flows against unacceptable security level yield cumulative probability of transmission network usage as [35]: (14) Taking offline a generation unit/transmission line, congestion cost is defined as follows:…”

Deterministic-based power grid planning enhancement using system well-being analysis

“…In some generation deficit areas that rely heavily on inter-tie lines to access remote generation from neighboring areas, a stringent deterministic security rule such as the N-1-G criterion in which a loss of single transmission component together with a loss of critical local generating unit is considered [12,13]. Another example of N-1-G application is when considering system security under the generating unit maintenance scheduling along with the N-1 contingency condition of the transmission system [14]. The utilization of the N-1-G security criterion in transmission planning, on one hand, could improve the system reliability.…”