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Abstract: This paper proposes a transmission and wheeling pricing method based on the monetary flow tracing along power flow paths: the monetary flow–monetary path method. Active and reactive power flows are converted into monetary flows by using nodal prices. The method introduces a uniform measurement for transmission service usages by active and reactive powers. Because monetary flows are related to the nodal prices, the impacts of generators and loads on operation constraints and the interactive impacts between active and reactive powers can be considered. Total transmission service cost is separated into more practical line-related costs and system-wide cost, and can be flexibly distributed between generators and loads. The method is able to reconcile transmission service cost fairly and to optimize transmission system operation and development. The case study on the IEEE 30 bus test system shows that the proposed pricing method is effective in creating economic signals towards the efficient use and operation of the transmission system. [Copyright &y& Elsevier]

Abstract: Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes, which may be tens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far, most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply–demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour, electricity demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. [Copyright &y& Elsevier]

• A novel under-voltage load shedding (UVLS) scheme is developed using dynamic voltage stability analysis. • Detailed static and dynamic load modeling are considered, and load compositions are included for a more realistic, reliable, and effective UVLS design. • A new formulation of dynamic voltage active power sensitivity (DVPS) is formulated to determine location and amount of load shedding. This manuscript recommends an under-voltage load shedding scheme based on the sensitivity of dynamic voltage curves to mitigate voltage collapse in highly stressed power systems. The developed method can be used to determine the minimum amount and proper locations of load curtailment by considering power system dynamics including dynamic load modeling. The selected Indonesian regional system has a large number of dynamic loads in form of air conditioning and water pump loads whose dynamics contribute considerably to the complexity of the power system stability. Loss of the transmission line in the system caused by the impact of the composite load after major disturbance is studied. The proposed scheme involves an iterative procedure based on the sensitivity analysis of the dynamic voltage curve to solve the problem of load shedding. Furthermore, this work developed a new index named dynamic voltage-active power sensitivity (DVPS). The DVPS is calculated in all load buses to give information about the bus that has a predominant influence on improving system voltage stability through load shedding. Dynamic simulations are carried out with an Indonesian power system, the South Sulawesi interconnection power system with the proposed load shedding scheme. The results of this work show a noteworthy improvement in the magnitude of the voltage level as well as the voltage stability margin. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a frequency response analysis approach suitable for a power system control area in a wide range of operating conditions. The analytic approach uses the well-known system frequency response model for the turbine–governor and load units to obtain the mathematical representation of the basic concepts. Primary and supplementary frequency controls are properly considered and the effect of emergency control/protection schemes is included. Therefore, the proposed analysis/modeling approach could be gainfully used for the power system operation during the contingency and normal conditions. Time-domain nonlinear simulations with a power system example showed that the results agree with those predicted analytically. [Copyright &y& Elsevier]

• An operational reliability assessment approach of photovoltaic inverters considering voltage/VAR control function is proposed. • An inverter based voltage/VAR control optimization model considering uncertainties of photovoltaic power generation and loads is developed for further inverter reliability assessment. • The power loss model considering the voltage/VAR control results is developed and a modified lifetime model based on coffin-manson model and manufacturing information is proposed to assess the inverter reliability. • In some cases, the implementation of voltage/VAR control function may decrease the junction temperature variations of power devices inside inverters, which leads to positive impact on inverter reliability. • The lifetime of photovoltaic inverters utilized for voltage/VAR control function has high correlation with their locations in the distribution network as well as their oversizing rates. This paper proposes an operational reliability assessment approach of photovoltaic (PV) inverters considering a voltage/VAR control (VVC) function. The approach aims to quantify the reliability degradation and estimate the lifetime of PV inverters when they are utilized for the VVC function. Firstly, an inverter based VVC model considering uncertain profiles of PV power generation and loads is developed and it is solved by a stochastic optimization method. Then, a long-term reliability assessment procedure of the inverters utilized in the VVC model is proposed. To assess the reliability, a power loss model considering the VVC results is developed and a modified lifetime model based on Coffin-Manson model and manufacturing information is proposed. The proposed VVC model and inverter reliability assessment approach are verified on a 33-bus distribution network. The simulation results reveal the long-term impacts of additional utilization in the VVC function on operational reliability and lifetime of PV inverters. [ABSTRACT FROM AUTHOR]

• • Compressed air storage alone can firm up wind and solar variability in California. • • Increased penetration of renewable energy can decrease CAES storage requirements. • • Type of renewable energy strongly affects the required CAES capacity. • • Bulk CAES deployment has limited applications due to real-world constraints. Bulk energy storage can play an important role in the decarbonization of renewable-dominant electricity system. It can offer a solution to the grid balancing problem caused by the variability in the output of renewable power generation. This paper explores the requirement for compressed air energy storage (CAES) capacity as the penetration of renewable energy increases to compensate for the variability of wind and solar. A case study for California using parsimonious macro energy model with real-world historical demand and hourly weather data has been utilized to do this analysis. In the least-cost model, with no excess wind and solar power generation, required CAES capacity is 3.71TWh in 100% decarbonized scenario. If a strict rule of net-zero curtailment was in place, the storage capacity required would be 3.2% higher (3.83TWh) with 9.8% increased cost of electricity. However, the required CAES capacity decreases with the excess solar and wind power generation. In case of 2 times increase in the wind and solar potential the required CAES capacity with strict zero curtailment would be 19.2% less (3.10TWh) and the corresponding cost would decrease up to 29.7%. The study also revealed that the type of renewable energy mix (wind, solar or both) has strong effect on the required energy storage capacity for deep decarbonization. The presented results demonstrate that excess wind and solar power generation can be used to significantly reduce the required storage needs for a fully renewable power system at reduced cost. In California, building of a large battery energy storage (up to 3 TWh) is limited by societal, geographical, and economic constraints. This study suggests that in addition to the battery energy storage California may need to look for other dispatchable power sources (or the equivalent in load flexibility) for 100% wind and solar based fully decarbonized power system. [Display omitted] [ABSTRACT FROM AUTHOR]

• An algorithm for power flow analysis considering high renewable penetration. • Regionalization of distribution system into conventional & renewable dominant regions. • Load flow investigations for both type of regions. • Minimization of power losses and less computational burden are major benefits. To harmonize the operation of renewable and conventional generation, an approach of regionalized microgrid is proposed. Regionalization has been adopted for islanded microgrid in which the distribution system has been sectionalized into conventional generation-based regions (CGRs) operating with droop control and renewable generation-based regions (RGRs) operating with constant frequency de-coupled PQ control method. Back-to-back converters have been installed between the regions for bi-directional power exchange. In this paper, a novel load flow algorithm has been proposed for a regionalized microgrid in an islanded mode that aims to solve the power flow problem for both types of the regions. The algorithm considers the uncertainty of renewable distributed generators (RDGs) and loads. The approach focuses on the frequency regulation in both types of regions. Case studies have been carried out for IEEE 15, 33 and 69-bus distribution systems by converting them into regionalized microgrids (RMG). Results have demonstrated the strength of proposed load flow approach with a fast convergence speed. [Display omitted] [ABSTRACT FROM AUTHOR]

Security-constrained optimal power flow (SCOPF) is an important tool to optimize power system's operating state while satisfying security requirements with respect to credible contingencies. As a necessary extension to conventional SCOPFs, the recently proposed preventive–corrective SCOPF (PCSCOPF) aims to achieve the best coordination between the preventive control (PC) and corrective control (CC) considering the probabilistic nature of the contingencies and the cost of CC as well as other binding constraints. However, PCSCOPF renders a large-scale, multi-stage, non-linear programming problem which is difficult to directly solve. This paper proposes a novel and improved approach to the PCSCOPF problem. We aim to partition the contingencies into two exclusive sets: one is secured in the PC stage and the other in the corrective control CC stage. The PC corresponds to an ordinary SCOPF model and solved by the Benders decomposition method; the CC corresponds to an ordinary OPF model. The optimal partitioning of the contingencies is determined using an evolutionary algorithm (EA). Compared with the existing methods, the proposed approach is advantageous in that its searching dimension only depends on the number of insecure contingencies, hence tends to lead to a much higher solution speed. The proposed method is verified on the IEEE 118-bus system and compared with other two existing methods. Simulation results show that the proposed method can provide high-quality solutions with much higher computation speed. [ABSTRACT FROM AUTHOR]

• Study the vision of engaging networked data centers into distributed energy markets. • Propose a decision-making model to optimize the bidding decisions and energy resource operations of networked data centers in multiple geo-distributed local energy markets. • Conduct comprehensive numerical simulations to validate the benefit the cloud service provider can obtain from local energy markets. Active distribution network Internet Data Centers (IDCs) are large energy consumers in modern distribution networks. The integration of renewable energy and energy storage systems transforms IDCs into proactive energy prosumers, and enables them to participate in the energy trading in regional local energy markets. This paper proposes an energy management framework for a Cloud Service Provider (CSP) that manages multiple geographically distributed IDCs. The framework provides decision-making support for the CSP to optimally schedule the IDCs' cyber-energy resources (computing requests, on-site battery energy storage systems, and on-site renewable energy sources). In this way, the proposed framework facilitates the CSP to proactively participate in the local energy markets situated in the regions that host the IDCs, with the objective to minimize the CSP's total cost over a finite operation horizon. We use an effective evolutionary computation algorithm to solve the proposed energy management model and design extensive numerical simulations to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• Proposing an energy-function-based approach to assess the transient stability of the economic operating point of the power system. • Developing a transient stability criterion to solve system swing equations only until the fault clearing time, that improves the computational efficiency of the transient stability constrained OPF problem significantly. • Utilizing Benders decomposition technique to handle the transient stability constraints as parallel and separate sub-problems. • Promoting the transient stability constrained Optimal Power Flow to estimates the system critical clearing time with an acceptable level of accuracy without any network reduction. Security Constrained Optimal Power Flow (SCOPF) is traditionally performed to obtain the optimal generation levels to achieve the minimum generation cost under operational constraints in normal and contingency conditions. In this paper the SCOPF problem with DC load flow equations is extended to consider the transient stability margin of the generating units as a heuristic decomposition algorithm. However, the proposed algorithm is compatible with any SCOPF formulation. Due to computational complexities of security constraints and transient stability assessment, Benders decomposition algorithm is utilized to handle the transient stability margin of generating units as separate sub-problems. A transient energy function is developed to assess the transient stability of generating units under credible faults using the cut-set energy function criterion. In case of violation of the required transient stability margin, Benders cuts are constructed and added to the master problem. The proposed decomposed Transient Stability Constrained OPF (TSCOPF) is converged in few iterations. The developed TSCOPF algorithm is implemented on the IEEE 39-bus dynamic test system to validate its accuracy and efficiency. [ABSTRACT FROM AUTHOR]

• Consensus-based control of distributed generators to minimize frequency deviation. • Consensus-based control of interlinking converters to align AC subgrid frequencies. • Modifications on Backward/Forward Sweep-based three-phase AC-DC power flow analysis. • Accurate, scalable and generic method for networked islanded hybrid microgrids. This paper proposes the incorporation of distributed and decentralized control models of generators and converters into the power flow analysis of islanded hybrid microgrids (IHMG). The absence of a slack bus in an islanded microgrid presents challenges to its frequency and voltage regulation as well as power flow calculation. While droop mechanism as the primary control has been well incorporated into load flow analysis, distributed secondary control has only recently been developed for islanded microgrids. This paper proposes a distributed secondary control for a) generators in an AC subgrid of an IHMG and b) interlinking converters in networked IHMGs. Both the distributed and droop control are incorporated into a three-phase power flow calculation based on a modified Backward Forward Sweep method. The algorithm has been tested on several case studies, and the power flow results have been verified against a time-domain simulation. The proposed method proves to be accurate and useful for the planning and design of three-phase networked IHMGs. [ABSTRACT FROM AUTHOR]