Generic Market Modelling for Future Grid Scenario Analysis

Power systems worldwide are moving away from being dominated by large-scale synchronous generation and passive consumers. Instead, in the future, new actors on both the generation and the load side will play an increasingly significant role. On the generation side, there are renewable energy resources (RES) such as wind generation (WG), photovoltaic (PV) and concentrated solar thermal (CST). On the load side, there are demand response (DR), energy storage and price responsive users equipped with a small-scale PV-battery system (called prosumers). The two sides will together shape future grids. However, if connected at a large scale without proper consideration of their effect, they can also jeopardise the reliability and security of electricity supply. For example, the addition of non-synchronous RES will jeopardise the frequency response of the future grids, while the intermittency and variability of RES threats the existing model of electricity supply (supply following demand), complicating balancing and stressing future grids’ ramping capabilities. On the other hand, the inclusion of DR, prosumers and storage without proper consideration of the implications can cause significant changes to the demand profiles and may result in new stresses such as secondary peaks or excessive ramps. In summary, balancing, stability (frequency, voltage, transient) and ultimately reliability are affected by the changes introduced to the future grids’ technology mix. Given that the lifespan of power system assets is well over fifty years, laying out a roadmap to future grid development in an economical fashion without risking its security is a challenging task. The uncertainty of cost, availability and quality of new technologies requires power system planners and policy-makers to evaluate the feasibility and viability of future grids for a diverse range of technology options. To this end, a rigorous and systematic approach is developed in this dissertation to analyse the implications of prosumers, storage and CST on the balancing and stability of future grids. The best features of all these approaches are combined and presented in a single coherent framework. Computation time improvement techniques are then deployed to improve the computational efficiency and solution accuracy. Taken as a whole, the tool will fill the gap to explore the validity of emerging technologies to tackle balancing, stability, security and reliability issues, over a diverse scope of uncertain premises. The tool is developed for an approach to future grids studies called scenario analysis. Traditionally, power systems are planned based on a handful of the most critical scenarios with an aim to find an optimal generation and/or transmission plan. In contradistinction, scenario analysis involves analysing possible evolutionary pathways to facilitate informed decision making by policy-makers and system planners. Specifically, the primary aim of future grids studies is to deal with the uncertainty of long-term decision making and providing outcomes that are technically possible, although explicit costing might be considered. To this end, for any future grids stability framework, the market model is a critical bottleneck. Existing future grids studies mostly look at simple balancing, ignore network constraints and include most of the emerging technologies in an ad hoc fashion. These simplifications are made to combat the high computation time requirement of accurate approaches. Against this backdrop, this dissertation presents: i) a novel optimisation-based models to capture the effects of prosumers (Chapter 2, 3); ii) co-optimise dispatch of PV and CST aggregation to reduce ramping stress on the conventional generators (Chapter 4); iii) efficiently implemented market-based dispatch (Chapter 5); iv) framework for frequency performance assessment of future grids (Chapter 6). In more detail, first, Chapter 2 and 3 develop a novel approach to explicitly model prosumers’ demand in market dispatch (production cost) models. The key novelty of the method is its ability to capture the impact of prosumers without going into specific market structure or control mechanisms, which are computationally expensive. The model is formulated as a bi-level program in which the upper-level unit commitment (UC) problem minimises the total generation cost and the lower-level problem maximises prosumers’ aggregate self-consumption. Unlike the existing bi-level optimisation frameworks that focus on the interaction between the wholesale market and an aggregator, the coupling is through the prosumers’ demand, not through the electricity price. That renders the proposed model market structure agnostic, making it suitable for future grids studies where the market structure is potentially unknown. This model addresses some critical questions such as, How much flexibility can prosumer provide to help with large-scale RES integration? Flexibility is the key to achieve a high RES penetration. One of the major problem in the integration of RES is their intermittent and variable nature. Concentrated solar thermal (CST) presents an excellent resource with inherent flexibility. In contrast to Chapter 2 and 3 (exploring flexibility through DSM), Chapter 4 examines flexibility options from a generation end. In particular, it proposes an RES aggregation (REA) scheme aiming to co-optimise the dispatch of intermittent and dispatchable RES. The principal aim is to keep in check the ramping stress imposed on the conventional generators due to the RES integration. A Stackelberg game is used to capture the interaction between an independent system operator (ISO) and the REA when the ISO tries to minimise the generation cost, while REA seeks to maximise its revenue. This approach also highlights the potential of a ramping market, as proposed by some US studies. In Chapter 5, the utility storage proposed in Chapter 2, prosumers model proposed in Chapter 3, the dispatch model of CST developed in Chapter 4 and inertia constraint detailed in Chapter 6 are combined into a single coherent framework. The addition of these emerging technologies in the energy market model significantly increases the computation burden. Also, to allow for a subsequent stability assessment, an accurate representation of the number of online generation units is required, which affects the power system inertia and the reactive power support capability. This renders a fully-fledged market model computationally intractable, so in Chapter 5 we deploy unit clustering, a rolling-horizon optimisation approach and constraint clipping to improve the computational efficiency. Together, these comprise a computationally efficient market simulation tool (MST) suitable for future grid stability analysis. Finally, developed MST is used in Chapter 6 for a comprehensive frequency performance assessment of the Australian National Electricity Market (NEM). First, an assessment of minimum inertia requirements is presented, followed by a framework for frequency performance assessment of future grids. The maximum non-synchronous instantaneous range from a frequency performance point of view is established for the NEM. Also, to alleviate the deteriorating effects of the high RES penetration on frequency performance, different technical solutions are proposed and discussed. These efforts will empower policy-makers and system planners with the information on safe penetration levels of different technologies while ensuring reliability and security of future grids

An Energy Sharing Game with Generalized Demand Bidding: Model and Properties

This paper proposes a novel energy sharing mechanism for prosumers who can produce and consume. Different from most existing works, the role of individual prosumer as a seller or buyer in our model is endogenously determined. Several desirable properties of the proposed mechanism are proved based on a generalized game-theoretic model. We show that the Nash equilibrium exists and is the unique solution of an equivalent convex optimization problem. The sharing price at the Nash equilibrium equals to the average marginal disutility of all prosumers. We also prove that every prosumer has the incentive to participate in the sharing market, and prosumers' total cost decreases with increasing absolute value of price sensitivity. Furthermore, the Nash equilibrium approaches the social optimal as the number of prosumers grows, and competition can improve social welfare.Comment: 16 pages, 7 figure

Smart Grid for the Smart City

Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users

Frequency Performance Assessment of Future Grids

Future grids security will be challenged by the increasing penetration of non-synchronous renewable energy sources (NS-RES). Studies of future grids with high penetration of NS-RES suggest that along with other issues, system frequency control will become a challenging task. Therefore, this thesis first, studies the impact of high penetration of NS-RES and different penetration levels of prosumers on the performance and frequency stability of the Australian national electricity market (NEM). By doing this, the connection between the NS-RES and the system frequency performance, as well as different penetration levels of prosumers and the system frequency performance are quantified. Second, we propose a frequency performance assessment framework based on a timeseries approach that facilitates the analysis of a large number of scenarios. This framework is utilised to assess the frequency performance of the Australian future grid by considering a large number of future scenarios and sensitivity of different parameters. By doing this, we identify a maximum non-synchronous instantaneous penetration range for the system from the frequency performance point of view. Then, to improve the frequency performance of the system with high penetration levels of NS-RES, we evaluate the contribution of different resources, such as synchronous condensers, wind farm’s synthetic inertia and a governor-like response from the de-loaded wind farms, on frequency control. The results show that the last one adds more flexibility to the system for frequency control. Finally, a coordinated operation strategy for wind farms is proposed. It is shown that by operating the wind farm in a coordinated way, we can increase both the output power and the rotational kinetic energy of the wind farm. Time-domain simulations show that the proposed operation strategies noticeably improve the wind farm’s performance in frequency control

Techno-economic analysis of residential thermal flexibility for demand side management

The continuing rise in solar and wind production leads to an increasing demand of flexibility to stabilize the electricity grid. Furthermore, we can assume a gradual but intensive rise in the use of electrical heatpumps for household spatial heating, for different reasons. Therefore, this paper investigates the feasibility and viability of entering the flexibility market by aggregating residential thermal loads. For this research, a dataset of 200 dwellings in the Netherlands, equipped with a heatpump and smart metering infrastructure, is analysed. By means of a greybox modeling approach, a thermal model and control framework have been set up for every house, in order to identify the load shift potential and the accompanying cost of providing flexibility for the houses. We find that thermal flexibility is asymmetric: downwards flexibility is, apart from much more dependent on outdoor temperature than upwards flexibility, strictly lower than upwards flexibility. The cost for downwards flexibility is strictly negative in terms of the prosumer. Concerning upwards flexibility, the cost is most of the time positive. Moreover, it can be concluded that there is a potentially viable business case for the flexibility aggregator

SALSA: A Formal Hierarchical Optimization Framework for Smart Grid

The smart grid, by the integration of advanced control and optimization technologies, provides the traditional grid with an indisputable opportunity to deliver and utilize the electricity more efficiently. Building smart grid applications is a challenging task, which requires a formal modeling, integration, and validation framework for various smart grid domains. The design flow of such applications must adapt to the grid requirements and ensure the security of supply and demand. This dissertation, by proposing a formal framework for customers and operations domains in the smart grid, aims at delivering a smooth way for: i) formalizing their interactions and functionalities, ii) upgrading their components independently, and iii) evaluating their performance quantitatively and qualitatively.The framework follows an event-driven demand response program taking no historical data and forecasting service into account. A scalable neighborhood of prosumers (inside the customers domain), which are equipped with smart appliances, photovoltaics, and battery energy storage systems, are considered. They individually schedule their appliances and sell/purchase their surplus/demand to/from the grid with the purposes of maximizing their comfort and profit at each instant of time. To orchestrate such trade relations, a bilateral multi-issue negotiation approach between a virtual power plant (on behalf of prosumers) and an aggregator (inside the operations domain) in a non-cooperative environment is employed. The aggregator, with the objectives of maximizing its profit and minimizing the grid purchase, intends to match prosumers' supply with demand. As a result, this framework particularly addresses the challenges of: i) scalable and hierarchical load demand scheduling, and ii) the match between the large penetration of renewable energy sources being produced and consumed. It is comprised of two generic multi-objective mixed integer nonlinear programming models for prosumers and the aggregator. These models support different scheduling mechanisms and electricity consumption threshold policies.The effectiveness of the framework is evaluated through various case studies based on economic and environmental assessment metrics. An interactive web service for the framework has also been developed and demonstrated