The flexibility of the end-users in the electricity markets is becoming more pertinent with the evolution of market mechanisms allowing consumers to participate actively. The advent of Distributed Energy Resources (DERs) and energy storage systems is gradually and continuously changing the roles of market operators. In the emerging consumer-centric markets, the consumers are equipped with DERs and can participate actively as prosumers, trading their energy resources with neighbours. The other community agents are mainly consumers without DERs and producers without load demands. The impact of the uncertainty of DERs and load demands on community-based electricity market (CBEM) structures has not been fully investigated. In this thesis, we propose a robust solution to CBEM operations under uncertainty and compare the optimal decisions on energy trades with deterministic, and opportunistic models. Also, we employ Taguchi's orthogonal array testing (TOAT) to generate proficient scenarios from uncertain parameters of prosumers', producers', and consumers' resources.
While the optimality of the solution provided by the CBEM mechanisms has been analyzed extensively, the ability to address the individual user preferences that would maximize their utility has been hard to incorporate. We also, extend the traditional, community-based, centralized electricity market to incorporate the consumer and producer preferences relating to economic aspects rather than technical constraints. This is achieved with the use of indifference curves for standard utility functions used in exchange economy (such as Cobb-Douglas utility, perfect substitutes, perfect complements, etc.)
This thesis further proposes a single-stage robust formulation of the traditional, community-based, centralized electricity market incorporating the agents' preferences relating to economic aspects rather than technical constraints. A single-stage robust optimization model of the CBEM with utility maximization is formulated by integrating uncertainty constraints defined within polyhedral uncertainty sets representing variations in agents' resources from forecasted/expected values. The proposed approach ensures the robustness of the market with the uncertainty of agents' generation and load resources. It allows community agents the ability to adjust their budgets to the given robust scenario. Thereafter the proposed methodology can control the degree of robustness as regards the uncertainty parameters of agents' resources.
With consideration to the emerging consumer-centric markets, the possibilities of the offer of ancillary services besides demand-side responses, energy management, and peak shaving/shifting/leveling functions are being explored in providing flexibility and scalability in the market mechanism. The offer of these services within several market mechanisms and entities has been researched widely in literature, in our work we propose the formulation of the CBEM in a joint day ahead market model offering ancillary services of reserve and regulation while minimizing the total traded costs of agents' and the community manager and also maximizing the individual utility functions of agents.
Finally, a single-stage robust mixed-integer linear problem is presented which models the joint market over the worst-case realisations of uncertain parameters of agents' resources and reserve/regulation prices represented within polyhedral uncertainty sets.
In this work, the performance of the proposed CBEM market is implemented in three case studies with consideration to different market participants the prosumers, producers, and consumers to analyse the impact of uncertainty in CBEM with and without agent utility maximization and also in a joint day-ahead market offering ancillary services. The first case study presents 7 prosumers equipped with PV generation and load consumption, the second case study presents 15 agents with 7 producers equipped with PV generation and 8 consumers and the third case study presents 5 prosumers equipped with PV generation, 20 consumers, and three producers one with a wind production and the other two with conventional generation. Simulation results demonstrate the costs of robustness as a result of the impact of uncertainty, the agents' preference relations and utility maximization, and the total profits in the offer of ancillary services.
