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Real-time monitoring of the power system by phasor measurement units (PMUs) leads to the development of such devices in a wide area measurement system (WAMS). However, the power system observability cannot be obtained by employing only PMUs. The communication infrastructure (CI) is a significant part of the WAMS that has to be optimally designed and implemented to collect data from PMUs and deliver them to control centers. In this paper, a novel hybrid wireless sensor network is proposed for the connection of PMUs throughout the system to enable convenient and low-cost communication media. The problem of observability in the communication system is checked along with the optimal placement of PMUs in the power system to reach full observability. A hybrid wireless sensor network including plug-in powered sensor nodes (PPSNs) and energy harvesting sensor nodes (EHSNs) is utilized for increasing the reliability of the communication system. In the proposed co-optimal PMU-sensor placement problem, the main objective is to minimize the total cost of PMU placement and the related communication system, considering full observability of the power system and CI. To achieve better results, the zero-injection bus (ZIB) effect and system observability redundancy index (SORI) are considered as a constraint in the objective function. A binary-coded genetic algorithm is used for solving the proposed mixed-objective optimization problem subject to different technical operating constraints. The proposed method is examined on IEEE 13-bus and IEEE 37-bus test feeder systems. The results show the applicability and effectiveness of the proposed method compared with the conventional methods in this subject area.

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.