• Energy Research

This paper introduces a new method for allocating losses in a power system using a loop-based representation of system behaviour. Using the new method, network behaviour is formulated as a series of presumed power transfers directly between market participants. In contrast to many existing loss allocation methods, this makes it easier to justify the resulting loss distribution. In addition to circumventing the problems of non-unique loss allocations, a formalised process of loop identification, using graph theory concepts, is introduced. The proposed method is applied to both the IEEE 14-bus system and a modified CIGRE Nordic 32-bus system. The results provide a demonstration of the capability of the proposed method to allocate losses in the hybrid market, and demonstrate the approach's capacity to link the technical performance of the network to market instruments.

This paper introduces a new method for allocating losses in a power system using a loop-based representation of system behaviour. Using the new method, network behaviour is formulated as a series of presumed power transfers directly between market participants. In contrast to many existing loss allocation methods, this makes it easier to justify the resulting loss distribution. In addition to circumventing the problems of non-unique loss allocations, a formalised process of loop identification, using graph theory concepts, is introduced. The proposed method is applied to both the IEEE 14-bus system and a modified CIGRE Nordic 32-bus system. The results provide a demonstration of the capability of the proposed method to allocate losses in the hybrid market, and demonstrate the approach's capacity to link the technical performance of the network to market instruments.

Power system low frequency oscillations influence dynamic behaviour of a complex power system and threaten its security. The dynamic performance of power system can be improved by damping low frequency oscillation with the help of supplementary controllers. This paper presents the design of supplementary controller for Static Var Compensator (SVC) to damp low frequency, in particular inter-area oscillations. The controller is designed based on H ∞ loop-shaping technique in which the robust stabilization of the normalised coprime factor plant is formulated into a generalized H ∞ problem. Moreover, the selection of proper feedback signal from the available measurements of the system plays vital role in designing the controller. The residue analysis is used to select the suitable locally available signal as an input signal to the proposed controller. Two power systems with varying sizes and complexities are used to test with the design of the proposed controller. The power systems include the benchmark, two-area system for low frequency oscillation studies and a modified version of a practical system. Both eigenvalue analysis and time domain simulations are used to study the performance of the proposed H ∞ controller.

Power system low frequency oscillations influence dynamic behaviour of a complex power system and threaten its security. The dynamic performance of power system can be improved by damping low frequency oscillation with the help of supplementary controllers. This paper presents the design of supplementary controller for Static Var Compensator (SVC) to damp low frequency, in particular inter-area oscillations. The controller is designed based on H ∞ loop-shaping technique in which the robust stabilization of the normalised coprime factor plant is formulated into a generalized H ∞ problem. Moreover, the selection of proper feedback signal from the available measurements of the system plays vital role in designing the controller. The residue analysis is used to select the suitable locally available signal as an input signal to the proposed controller. Two power systems with varying sizes and complexities are used to test with the design of the proposed controller. The power systems include the benchmark, two-area system for low frequency oscillation studies and a modified version of a practical system. Both eigenvalue analysis and time domain simulations are used to study the performance of the proposed H ∞ controller.

This paper introduces a new power flow tracing and subsequently loss allocation method based on loop analysis. The knowledge of the loop paths aids in the visualisation of presumed transfer of power throughout the transmission network. A formalised process of loop identification, based on graph theory, is introduced to ensure that each loop contains at least one active source. This way, the system losses can be readily and justifiably allocated to the active sources in the network without involving any approximations. The proposed method is applied to both a small test system and the IEEE 14-bus test system, demonstrating the features and limitations of the proposed methodology.

This paper introduces a new power flow tracing and subsequently loss allocation method based on loop analysis. The knowledge of the loop paths aids in the visualisation of presumed transfer of power throughout the transmission network. A formalised process of loop identification, based on graph theory, is introduced to ensure that each loop contains at least one active source. This way, the system losses can be readily and justifiably allocated to the active sources in the network without involving any approximations. The proposed method is applied to both a small test system and the IEEE 14-bus test system, demonstrating the features and limitations of the proposed methodology.

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

During the ascending phase of solar cycle 24 concern in the power industry regarding space weather has increased significantly. This is driving the development of software tools to estimate GIC distributions in power networks for a given uniform geoelectric field. Typically, geoelectric fields induced during space weather disturbances are spatially non-uniform. This paper shows that for accurate planning and development of mitigation strategies, GIC analysis software needs to allow for specification of non-uniform geoelectric fields. Further, the notion held by power utilities in mid and low-latitude locations that space weather does not pose any risk to their systems is questionable. In this paper a methodology is developed to estimate the distribution of GICs in a specified power network during a significant geomagnetic event at mid-latitudes.