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

Evaluation of concentrated solar-thermal generation for provision of power system flexibility

Including a large amount of renewable energy sources (RES) in future power systems will not be possible without flexibility. Concentrated solar power (CSP) presents an excellent resource with inherent flexibility. This paper purposes aggregation of inflexible RES, such as utility-scale photovoltaic, with CSP to achieve the required flexibility. The aim is to keep in check the ramping stress induced on conventional generators due to the integration of RES. For this purpose, a Stackelberg game is used to capture the interaction between an independent system operator (ISO) and purposed RES aggregation (REA). In cost minimisation analysis, the ISO tries to minimise generation cost, whereas REA seeks to maximise revenue. In this setting optimising power dispatch from REA with total energy and ramp rate limitations is a challenging task. Case studies benchmark the effect of purposed REA against business as usual scenario for the Australian National Electricity Market