Main conclusions and contributions

Ancillary Services (AS) are crucial to maintain and control the stability of power systems. Currently, and more in the future, AS markets will be influenced by a large set of different Distributed Energy Resources (DER). These new players can participate directly in the market or aggregated to some agents, such a Virtual Power Players. Due to the continuous increase of players with several kinds of DER, the development of new methodologies becomes necessary to provide flexible mechanisms to the energy and AS negotiation.

This dissertation focuses on the development and implementation of new market mechanisms for energy and AS, considering several players involved in the electricity market. A comprehensive work has been developed in order to address several objectives and different perspectives of AS management. In this way, the AS management from the Independent System Operator (ISO) and Virtual Power Player (VPP) standpoint were considered, taking into account the features of the players involved in each model.

The development of a model capable of simulating the joint market using a Alternate Current (AC) Optimal Power Flow (OPF) model for the simulation of technical constraints of the network; the introduction of an innovative method (Bialek topological factors) considering the ancillary services dispatch in the network congestion calculation, in order to prevent network congestion during the dispatch of all ancillary services considered in the market; and complex contracts implemented in order to enable the negotiation between players and VPPs, results in a complete and complex simulation model very close to current markets, as well as the main contribution of this dissertation.

The proposed models are based on California Independent System Operator (CAISO) market rules. CAISO is a nonprofit public entity subject to the FERC regulation, which operates the transmission facilities of all participants in power systems, and dispatches the generation units and the loads. The CAISO market includes several competitive and liberalized market mechanisms. An interesting market mechanism in the development of this dissertation is the energy and AS joint optimization. Therefore, in this work it was studied and adapted some of the innovative aspects of the CAISO market. The following CAISO rules were implemented and tested in joint energy and AS market:

Tiago André Teixeira Soares

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 The use of relaxation variables in optimization problem, which always ensures obtaining results of the AS dispatch, regardless of the operation context;

 AS cascading mechanism;

 Energy and AS joint optimization;

 AS bidding by operation network regions.

All the models developed include the Regulation Down (RD), Regulation Up (RU), Spinning reserve (SP) and Non-Spinning Reserve (NS). The models also include several market mechanisms with different objectives for improving the market model. The relaxation variables are used to obtain an economic dispatch regardless of the operation context. Other mechanism is the AS cascading process, which is used to improve the economic efficiency of AS management.

The establishment of AS bids by network regions is a market mechanism used by the ISO in order to mitigate/avoid network congestion. For each region, part of the AS requirements (about 50%) is provided exclusively by internal energy resources of that region. The main advantage of this market mechanism is to decrease the probability of having network congestion in regions tendentiously problematic, as well as to improve the reliability and quality of the energy service. However, this mechanism does not ensure the technical and economical best solution.

The energy and AS joint market model do not ensure the solution feasibility. The main problem is that the model does not consider the impact that the AS may have on the network congestion. In order to solve this issue, an innovative methodology was developed to solve the network congestion caused by the simultaneous market clearing process of the joint market.

This methodology is based on Bialek topological distribution factors. The major contribution of this methodology is to always ensure a feasible solution of the energy and AS dispatch in any operation context. In what concerns the model runtime, it suits the ISO operation requirements. This methodology allows finding a better solution than the traditional methodology, guaranteeing the feasibility of the system, avoiding any network congestion that may occur in the traditional methodology.

The effectiveness of the proposed methodology is reflected in the results, since the operation costs are lower when compared with the traditional market methodology which needs further network congestion analysis to solve the congestion that the AS can cause in the network.

Other important contribution proposed in this dissertation is the inclusion of DER in AS such as Regulation Down, Regulation Up, Spinning and Non-Spinning reserve. In this way, an aggregator agent was proposed in order to manage and interact with a wide variety of DER, like Distribution Generation (DG) (mainly based on renewable energy sources), Demand Response (DR), and storage systems. The VPP is an agent that aggregates all kind

of DER, and acts as network operator, providing AS to the system operator. The VPP has the ability to participate in the electricity market, taking into account the contracts established with the aggregated resources.

Based on these assumptions, a distribution network AS management methodology considering a large penetration of small players was developed. The methodology includes complex contracts between VPP and small players, so that the DER may participate in local AS management, as well as in AS market. The proposed contracts can consider features related to minimum limits of generation intended for the players, remuneration conditions, and the number of consecutive hours in generation, among others. The major advantage of this approach is the AS management by a VPP at the distribution network level with operation features related to the future of the power systems. On the other hand, the inclusion of DER allows easier on-site monitoring system stability. The establishment of complex contracts between the VPP and the players allows a careful and responsible management by power system entities.

The proposed methodology shows interesting results regarding the usefulness and ease of the DER participation in the AS procurement and dispatch. The results show that DER (especially storage systems) are indicated for the AS provision, due to their flexibility to participate in any AS addressed in the model. Furthermore, the results show that complex contracts cover a wide range of DER, providing greater capacity to the VPP to meet their internal needs and sell power in the market.

Several scenarios regarding the simulation of the developed AS models were implemented in each case study. These scenarios included several future power systems characteristics, such as the intensive use of DG, DR and storage resources, the consideration of the ISO/VPP management in liberalized environment, among other characteristics. The set of case studies included in this dissertation illustrates the use of the proposed methodologies, and demonstrates the applicability and advantages of the proposed models.

The analysis conducted from the ISOs and VPPs standpoints are included in the presented set of case studies. The submission of AS bids by regions of the network, especially by storage systems, is also presented. In this case, the use and usefulness of the ability of storage units to charge and discharge for each ancillary service type is illustrated.

Moreover, a set of complex contracts between DER and VPP are illustrated.

All the models simulated were developed using the General Algebraic Modeling System (GAMS) optimization tool, based on the model of deterministic optimization approach (Mixed-Integer Non-Linear Programming – MINLP). Based on this technique, the more complex model proposed in the development of this work reached 20 minutes of simulation. In this way, the proposed model fits the Day-Ahead Market (DAM) simulation.

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Lastly, all the methodologies proposed and implemented were included in the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM). MASCEM is a simulator which depicts the study of complex restructured electricity markets operation. In this way, the methodologies developed in this dissertation provide additional methodological bases to MASCEM, for the simulation of the present and future operation of the energy and AS market.