This research work and associated case studies were conducted with two main objectives in focus: (I) determine ESS operations that being sensitive to markets and system conditions would deliver maximum benefits to the electricity industry in the form of a single or multiple services and (II) develop novel operational policies for ESS commercial strategies that maximise utilisation of its resources and would enhance its economics. The former was addressed in Chapter 2 and Chapter 3 and the later addressed in Chapter 4 and Chapter 5.
In Chapter 2, a novel modelling framework for distributed ESS was developed, which considers provision of multiple services - aggregated in a single business model - to various stakeholders and designed to maximise ESS economics while being sensitive to services value and system operating conditions. Likewise, Chapter 3 expanded the mathematical model in order to determine ESS long term commercial strategies - within the multiple services business model framework - and select portfolio of services that maximise ESS revenues in typical markets and system conditions. A computationally efficient model was developed to cope with the problem size and be able to achieve optimum (or near optimum) solutions within appropriate operational time frames. Among the various studies and associated results that addressed the proposed objective, the contributions that emerged from the research conducted in those chapters were as follows:
- Validated the efficient coordination of multiple services being delivered, simultaneously, to various stakeholders by determining optimum ESS active and reactive power outputs. This will allow ESS owners to contract multiple services and thereby enhance the investment economics opportunities by collecting multiple revenue streams with a single ESS device improving not only the revenue obtained but also enabling hedging strategies to be put in place against services volatility, i.e. by providing more than one service. ESS owners can hedge against volatility or expected low revenue on a particular service.
- Determined ESS operations that deliver maximum benefits to the various stakeholders while being sensitive to market and system operating conditions and different sets of services should be provided, particularly in summer and winter months
A key contribution from the research conducted is the insight that ESS business models should not be implemented based on a fit and forget approach for the entire life span of the ESS. The business model should be dynamic and sensitive to market and system operating conditions in order to achieve maximum benefits for the stakeholders. So as shown in Chapter 3, different seasons in the year are associated with different sets of services and different volumes.
- Coordinated ESS operation of active and reactive power is fundamental to efficiently provide DNO service and supports provision of active power services only (such as energy arbitrage and balancing services).
It has been shown that coordination of active and reactive power can be exploited to support revenue with active power services only and therefore should be considered in ESS sitting and sizing decisions. Recent studies typically address investment decisions in ESS devices by determining energy and active power capacities (i.e. MWh and MW capacities), although the research conducted has shown that reactive power is essential to provide DNO service and support revenue in energy arbitrage and balancing services. In this context, future sizing decisions for ESS should consider reactive power capacity and thus determining apparent power capacity for ESS (i.e. MVA capacity rather than just MW capacity) is fundamental to ensuring efficient investment decisions.
The research in Chapter 4 and Chapter 5 was conducted to address ESS operating policies and increase utilization of ESS resources for further improvement of its economics. Chapter 4 focused on operating policies which are current practice among network system operators - either for voltage control or post-fault contingency actions - and develop a similar operating framework for ESS to provide DNO service. Similarly, Chapter 5 focused on adapting current practices in other industries (such as airline and hospitality industries) to ESS business model in order to improve utilization of its resources and ensure that these are allocated to the most valuable service. The contributions to emerge from this research were:
- Developed ESS corrective control operating strategies that achieve same levels of security of supply when providing DNO service.
Corrective control strategies have been shown to ensure the same levels of security of supply while providing other benefits to the DNO and ESS stakeholders. During post-fault conditions ESS robust energy levels have been shown to ensure security of supply as with preventive control.
- Enhanced ESS economics with novel operating policies and the benefits for DNOs with reduced cost for DNO service.
Adopting corrective control strategies not only enhances distribution network utilization levels but also resolves the ESS conflicts between DNO and other services, thereby enhancing ESS economics. In this context, with corrective control strategies, the cost for providing DNO service with an ESS is reduced and thus bringing benefits to DNOs and ESS stakeholders. This also supports the development of new market mechanisms to efficiently reward ESS for peak shaving services.
- Demonstrated that oversell operating policies are cost efficient and can potentially enhance ESS economics in the long term.
In Chapter 5 it was demonstrated that oversell operating policies are economically viable and potentially cost efficient for ESS investments, although the risks of such operating policies may undermine the stability of the electricity system and potentially result in severe damages to the electricity system which are not easily quantifiable. In this context, the results can inform regulators and policy makers and support the development of regulatory framework in order to dissuade such practices. Note that if ESS owners are purely driven by economic reasons, even with high penalties, overselling ESS resources would result in higher revenues and therefore improved return of investment, which incites ESS owners to adopt such policies.