Search

Curtailable loads (CLs) are regarded as one of the last lines of defence to maintain the security and stability of power systems. Nevertheless, if organised carefully, they can also be exploited as preventive security procurement measures for power systems. This is especially true for heavily loaded power systems in which the normal control schemes are already exhausted. In this study, a new power market approach is proposed to utilise CLs' potential in ensuring voltage stability margin (VSM) for heavily-loaded power systems. The proposed method aims to provide a mechanism to engage CLs as active players in the power market, and hence, minimise the disruptive effect of the load curtailment. Next, CLs participation in the power market is utilised to minimise the cost of achieving a desired level of VSM, at normal and N - 1 contingency conditions, in a preventive manner. The most efficient load curtailment and power generation pattern are determined, using a modified particle swarm optimisation algorithm, to minimise the system's total cost, while meeting grid's VSM requirements. The simulation results verify that the desired level of VSM can be effectively obtained using the proposed approach, with much less operational cost compared to the established methods. [ABSTRACT FROM AUTHOR]

Curtailable loads (CLs) are regarded as one of the last lines of defence to maintain the security and stability of power systems. Nevertheless, if organised carefully, they can also be exploited as preventive security procurement measures for power systems. This is especially true for heavily loaded power systems in which the normal control schemes are already exhausted. In this study, a new power market approach is proposed to utilise CLs' potential in ensuring voltage stability margin (VSM) for heavily‐loaded power systems. The proposed method aims to provide a mechanism to engage CLs as active players in the power market, and hence, minimise the disruptive effect of the load curtailment. Next, CLs participation in the power market is utilised to minimise the cost of achieving a desired level of VSM, at normal and N − 1 contingency conditions, in a preventive manner. The most efficient load curtailment and power generation pattern are determined, using a modified particle swarm optimisation algorithm, to minimise the system's total cost, while meeting grid's VSM requirements. The simulation results verify that the desired level of VSM can be effectively obtained using the proposed approach, with much less operational cost compared to the established methods. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable-rich distribution systems, and the prohibitive cost of upgrading the system infrastructure, has rendered voltage instability a real concern for heavily loaded systems. The voltage instability of distribution systems can spread to the corresponding transmission grid, as proven by real-life incidents. Recent advances in energy storage systems (ESSs), however, have offered a viable means of enhancing the reliability and robustness of power systems. In this paper, the optimal placement, sizing, and operation of ESS devices in wind-intensive distribution power systems are studied. The objectives of this paper are to minimize the ESS size (power and energy), required to ensure a desired voltage stability margin (VSM), and to minimize the reactive power loss and reactive power import from the upstream network. Wind uncertainty has been accounted for through a risk-based stochastic optimization framework. Besides, active network management (ANM) tools, such as the tap position of on-load tap changers, modelled by using a new method, and reactive power capabilities of both ESS devices and wind farms, are used as additional means to reduce the required ESS size. The results show that the required ESS significantly increases with increase in the desired VSM. Nevertheless, the increase can be considerably curtailed by using risk-based VS constraints and ANM tools. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable-rich power systems, and the prohibitive cost of upgrading the network infrastructure along with the load growth, has rendered voltage instability an imminent threat for many power systems. This necessitates faster and more efficient ways of identifying the voltage stability (VS) limits, associated with specific bifurcation points of power system model, which are suitable for real-time applications. To date, continuation power flow (CPF) has conventionally been used to identify bifurcation points of power systems, through plotting power-voltage (P-V) curves. However, existing CPF methods are complex and computationally demanding. To tackle this issue, in this study, accurate identification of both saddle-node and limit-induced bifurcation points of power systems is carried out by using a new and efficient continuous power flow algorithm, in which all the complexities associated with the existing CPF methods are relaxed. Low execution time (as compared to the existing CPF methods), ease of implementation, and automated applicability, make the proposed algorithm highly suitable for fast and accurate VS assessment of renewable-rich, uncertain, power systems. Experiments, carried out on several different size power systems, verify that the proposed method can be effectively used to identify the VS limits of practical real-life power systems, despite its ease of implementation and lower computational burden. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable‐rich power systems, and the prohibitive cost of upgrading the network infrastructure along with the load growth, has rendered voltage instability an imminent threat for many power systems. This necessitates faster and more efficient ways of identifying the voltage stability (VS) limits, associated with specific bifurcation points of power system model, which are suitable for real‐time applications. To date, continuation power flow (CPF) has conventionally been used to identify bifurcation points of power systems, through plotting power–voltage (P –V) curves. However, existing CPF methods are complex and computationally demanding. To tackle this issue, in this study, accurate identification of both saddle‐node and limit‐induced bifurcation points of power systems is carried out by using a new and efficient continuous power flow algorithm, in which all the complexities associated with the existing CPF methods are relaxed. Low execution time (as compared to the existing CPF methods), ease of implementation, and automated applicability, make the proposed algorithm highly suitable for fast and accurate VS assessment of renewable‐rich, uncertain, power systems. Experiments, carried out on several different size power systems, verify that the proposed method can be effectively used to identify the VS limits of practical real‐life power systems, despite its ease of implementation and lower computational burden. [ABSTRACT FROM AUTHOR]

Depleting fossil fuels and the pollution resulting from their consumption indicate an urgent need for clean and dependable alternatives such as renewable energies. Biomass is a free and abundant source of renewable energy. Municipal solid waste (MSW) as one of the main categories of biomass has always been an issue for metropolitan cities. It has, however, a high potential for biogas production. In this study, the technical and economic aspects of generating electrical power through solid oxide fuel cells (SOFCs) powered by injecting biogas derived from Tehran's MSW, as a case study, are investigated. The main objectives of the current study are to identify the power generation capability of the process and find out if it can result in a competitive energy resource. The total amount of obtainable methane through anaerobic digestion of MSW and then the achievable power generation capacity by using the obtained biogas are computed using the electrochemical relations inside the SOFC. The economic calculations are carried out to estimate the final price of the generated electricity, taking into account the major capital and ongoing costs of the required equipment. The effect of variations of MSW composition on the power generation capability and final electricity price is also studied. Moreover, the application of a gas turbine (GT) with the SOFC as a hybrid SOFC-GT system to recover the produced heat by SOFC and its effect on the power generation capability and the final electricity price are investigated. Results indicate that around 997.3 tons day−1 biomethane can be generated using Tehran's MSW. By using the SOFC, the produced biogas can generate 300 MWAC electrical power with a final cost of $0.178 kWh−1. By using the hybrid SOFC-GT, the electrical power capacity is increased to 525 MWAC, and the final electricity cost drops to $0.11 kWh−1, which indicates its competitiveness with other common energy resources in the near future, especially by considering different governmental subsidy policies that support renewable energy resources. The considerable environmental benefits of the proposed procedure, from both MSW management and CO2 emission reduction points of view, make it a promising sustainable energy resource for the future. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]