Schedule for: 18w2217 - 10th Seminar for Next Generation of Researchers in Power Systems

Note: the Lecture rooms are available after 16:00.

A buffet dinner is served daily between 5:30pm and 7:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building. All meal costs will be covered by the symposium organizers.

Beverages and a small assortment of snacks are available in the lounge on a cash honour system.

A buffet breakfast is served daily between 7:00am and 9:00am in the Vistas Dining Room, the top floor of the Sally Borden Building. All meal costs will be covered by the symposium organizers.

Welcome, intros, and logistics by Profs. Claudio Canizares and Kankar Bhattacharya and BIRS staff

Chaired by Claudio Canizares

Modern power systems are facing major operational challenges, driven by the rapid deployment of renewable energy based new generation technologies, increasing power consumption and limited investments in transmission level, leading to system operation close to its limits. The arising complexity necessitates more sophisticated tools of assessing the system operational status and security margins. This presentation focuses on the importance of capturing unknown dynamics in the context of power system monitoring, and deals with dynamic state estimation techniques for partly known models, as well as observer based anomaly detection schemes.

Developing new approach and technologies in a wide area would require a lot of in advance studies and ex-ante verification of various proposals. In this regard, representing the behavior of real world implementations implies scientific evidence-based modeling and simulations. Similar to the widely dispersed real power system, its virtual model could be also built and executed in a distributed simulation framework. In the presentation, two novel distributed simulation platforms integrating digital real-time simulators will be introduced as “Internet-of-Things based distributed infrastructure for smart grid co-simulation” and “geographically distributed real-time simulation of power systems".

Power systems are becoming increasingly vulnerable to disturbances. Whether a system is able to recover from a particular disturbance depends upon the system parameters. Therefore, it is valuable for system operators to be able to identify critical parameter values which form the boundary in parameter space between recovery and failure to recover from a particular disturbance. An efficient algorithm is presented for numerically computing critical parameter values by exploiting the structure of the region of attraction. The algorithm is demonstrated on a test case to find critical values of machine parameters.

The research topic is decentralized voltage stability monitoring and protection in power transmission networks. Long-term dynamics are considered. Measurement-based methods are developed aiming to detect the onset of voltage instability areas along a stressed transmission corridor. The developed method can be implemented either in PMUs located on transmission buses or digital distance relays located on transmission lines. Both methods are tracking a sensitivity indicator, which is related to the maximum power transfer point. The proposed method has been successfully tested on a medium-size test system by monitoring a power transfer corridor toward a load area. Further investigations include generalization of the method and performance evaluation on large-scale realistic transmission networks.

A recently developed formula that relates linearly local bus frequencies and synchronous machine rotor speeds, based on the system augmented admittance matrix will be presented. The applications of such a formula includes i) ideal estimation of local bus frequencies based on the variations of the machines rotor speeds in a simulation environment; ii) definition of the frequency participation factors of the machines to each local bus frequency; iii) model-agnostic online estimation of generator rotor speeds based on local frequency measures; iv) identification of the number and location of the optimal set of measures required in the estimation.

Chaired by Prof. Kankar Bhattacharya

In this presentation, a mathematical model of diabatic Compressed Air Energy Storage (CAES) is introduced, which considers independent generator/motor machines as interface with the electrical grid. The model is suitable for a diversity of power system steady-state and dynamic analyses. The main model components are: compressor, synchronous motor, cavern, turbine, synchronous generator, and associated controls. As an application, the operation of a CAES facility to provide frequency regulation in a power system with high penetration of wind generation is examined. It is demonstrated that the simultaneous operation of the compressor and turbine enhances the frequency regulation of the system.

A novel control algorithm for the introduction of BESS into the automatic regulation control (AGC) is proposed. The BESS control follows the goal to enhance the regulation service by minimizing the rate of non-compliance, which is related to how well a zone follows the control signal of the Spanish system operator. To verify the effectiveness of the control various BESS sizes have been simulated for 400 hours of real AGC operation data. The results show that a BESS is able to minimize the rate of non-compliance of a regulation zone by up to 50% depending on the employed BESS size.

The declining cost of residential energy storage and photovoltaic systems will soon make it possible for many customers to significantly reduce their grid imports. Customers willing to further benefit from their investment could also opt-in to use these systems for the provision of services. This, however, requires not only the development of adequate control strategies that maximize customer benefits, but also understanding the impacts that such operation brings in distribution networks. These aspects are quantified and demonstrated based on an Australian case study utilizing real smart meter demand, generation, pricing and network data.

Battery participants in performance-based frequency regulation markets must consider the cost of battery aging in their operating strategies to maximize market profits. We solve this problem by proposing an optimal control policy and an optimal bidding policy based on realistic market settings and an accurate battery aging model. The proposed control policy has a threshold structure and achieves near-optimal performance with respect to an offline controller that has complete future information. The proposed bidding policy considers the optimal control policy to maximize market profits while satisfying the market performance requirement through a chance-constraint. It factors the value of performance and supports a trade-off between higher profits and a lower risk of violating performance requirements. We demonstrate the optimality of both policies using simulations. A case study based on the PJM regulation market shows that our approach is effective at maximizing operating profits.

Most heating demands are fulfilled by coal and natural gas. Heating with electricity and biofuels are other alternatives available for possible improved operations. With the advent of hybrid heating system (HHS), heating operation costs can be reduced by utilizing the diverse choices of HHS for input energies such as natural gas, electricity and renewable biofuels. In this paper, strategic operation of HHS is proposed in which the HHS and electricity market are formulated with a bi-level optimization problem. The method is tested by the IEEE 14-bus system to verify the strategic operation of HHS against varying electricity prices supported by alternative energy resources.

A buffet lunch is served daily between 11:30am and 1:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building. All meal costs will be covered by symposium organizers.

As you progress through your graduate program, what awaits upon graduation.  If you want to find a career in academics, what should you do now to increase your opportunities.  How can you best leverage your graduate experiences if you seek career opportunities outside of a university environment.  In this session, we will explore trends both inside and outside of academia for new graduates.

Chaired by Prof. Claudio Canizares

Today electric power systems and district heating networks are physically coupled. The installation of heat pumps and micro combined heat and power plants enhances this development. Nevertheless, both networks are operated separately these days neglecting the possible synergy effects as storage capacities of the district heating networks. As the strong increase of renewable energy sources raise the need for flexibility options for the electric power system, coordinated network operation approaches are developed in recent research. For optimization based operation approaches models of electric power systems and district heating networks are setup comprising storages, consumers, sources and energy converters.

The water-energy nexus is a common phrase describing the critical interdependencies between the water delivery system (WDS) and the electric power system. This presentation will show some recent research with regards to the optimization of the operation of both systems via extended period, time-domain simulations. In addition, some results from a developed stochastic generation and transmission expansion modeling tool with environmental considerations related to water availability within a long-term, system planning length time frame will be shown.

The research presents the problem of re-planning the electric urban distribution network of Milano. Due to historical reasons, the distribution network of Milano is operated at several different voltages, substations with different schemes and practices, different design criteria. Thus, the goal is merging as much as possible the different areas in a coordinated and efficient way, minimizing capital and operational costs and taking into account operating practices and regulatory constraints. The problem is tackled by means of an integrated GIS-based procedure consisting of a series of Mixed-Integer Linear Programming (MILP) approaches.

To alleviate global climate crisis, focus is on increasing the share of renewable energy in electricity markets. The challenge is to address short-term flexibility requirements in long- term planning of power systems. To address this challenge, a novel linear time-invariant methodology is presented that bridges the gap between long-term capacity planning, while including challenges associated with short-term intra-hourly operational problems. The advantage of this approach is that it drastically reduces the computational complexity of problem, and it presents as a simple tool for capacity planners who are looking for an economical and robust solution for designing future decarbonized power systems.

Chaired by Prof. Kankar Bhattacharya

Power systems are being transformed from a thermal-dominated system into a renewable-dominated one. We are interested in exploring what the future high renewable penetrated power system looks like and how such a power system keeps power balance. This study is performed using a realistic large-scale case study. A stochastic generation and transmission co-planning model is proposed, in which a simplified unit commitment model is incorporated. Finally, some conclusions are summarized. 

Given the increased penetration of smart grid technologies, distribution system operators (DSOs) are expected to consider in all their stages both the increased uncertainty introduced by non-dispatchable distributed energy resources (DERs), as well as the operational flexibility provided by new real-time control schemes. This presentation will revise the planning (years - ahead), operational planning (days - ahead) and real-time operation stages of active DSOs in presence of DERs. Not only centralized and decentralized approaches will be presented, but emphasis will be put also on recent hybrid methods which employ off-line centralized calculations to derive optimized local control approaches.

In my presentation, I will talk about operation and sizing of energy storage systems in competitive electricity markets and show how an energy storage system can make a profit by shifting energy over time and providing ancillary services products. I will further focus on large-scale energy storage systems which their operation can impact the market outcomes and prices. Then, I will explain how the strategic behavior of large-scale energy storage systems in the electricity market can help them maximize their profit and justify their high capital cost.

To assess and exploit the available flexibility of the demand, an advanced monitoring of, at least some, customers’ electricity use is necessary. With the use of the artificial intelligence tools, it is possible to estimate/forecast aggregate end-users’ demand composition, and the size of the controllable demand, with a very limited number of monitors, i.e., smart meters. Reliable and timely information about short-term flexibility of the demand reduces uncertainty of the outcome of demand response (DR) programs, catering not only for the increase or decrease of demand at given point in time but also for the improvement of network performance indicators (e.g. voltage, angular and frequency stability). Hence, DR can be “tailored” to optimise between the distribution and transmission network flexibility requirements and availability of flexible demand.

This presentation introduces a technique for identifying the worst contingencies to be used in a security-constrained optimal power flow (SCOPF) problem. A bilevel max-min optimization model is proposed to find the worst contingencies while representing AC power flow equations and considering corrective actions. The objective is to minimize the total generation cost while satisfying operation constraints. The upper-level problem allows representing contingencies using binary variables. The lower-level problem represents the ACOPF problem using a second-order cone relaxed formulation. Duality is then used to merge the upper- and lower-level problems into a single-level one. The resulting mixed-integer second-order conic problem can be efficiently solved.

A buffet dinner is served daily between 5:30pm and 7:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building. All meal costs will be covered by the symposium organizers.

A buffet breakfast is served daily between 7:00am and 9:00am in the Vistas Dining Room, the top floor of the Sally Borden Building. All meal costs will be covered by the symposium organizers.

Sightseeing, trekking, lunch.