Optimal planning for partially self-sufficient microgrid with limited annual electricity exchange with distribution grid

Existing research on on-grid microgrid planning is carried out with a free trading assumption and without considering the limitation of annual electricity exchange. Therefore, the existing planning and sizing scheme may be not viable for the application of partially self-sufficient microgrid (PSSMG) with a limited amount of electricity exchange. To address this issue, a new planning method for PSSMG is proposed in this paper considering the limited annual electricity exchanging amount (AEEA). The sizing model and energy management are linearized and simultaneously integrated into one model, which could be solved in polynomial time. In order to effectively reduce the number of variables of a full year horizon and to cope with the uncertainty both of DGs and loads, a data-driven method based on K-means algorithm is utilized to choose a set of typical days that are representative of historical data of one full year. Finally, the validity and effectiveness of the proposed model are verified by comparative numerical simulations, and the sensitivity of limited AEEA to the planning scheme is analyzed

OPTIMAL DESIGN OF ENERGY COMMUNITIES Multi-objective design of multi-vector energy hubs integrated with electric mobility charging systems and acting as an energy community

The present thesis has the aim to develop a tool based on prescriptive analytics to perform the optimal design of several multi-vector energy hubs, integrated with electric mobility charging infrastructures, jointly acting as a local energy community through a posteriori multi-objective function. In Chapter 1 after having introduced the scope of the study, the justification of its relevance, and the main objectives, a brief summary of the publications of the author and his main activities during the PhD program course is reported. In Chapter 2 the energy transition is introduced, underlining the EU environmental targets by 2030 and the main energy trends which the energy sector is facing. Then the main incentive policies which are used to reach the environmental targets are reported and briefly analysed. The focus is moved on the newly introduced concepts of energy communities and collective self-consumers at the EU and at the State Member level. The preliminary implementation of the EU directives in Italy and Spain are evaluated and commented. Finally, the concept of microgrid and nanogrid is reported, as an actual and real representation of integrated energy systems characterized by multiple energy demands and different technologies. Chapter 3 recalls the concept of traditional design and compare it with optimal design. After a brief introduction on the different analytics techniques (descriptive, predictive, prescriptive) the focus is moved to the MILP (Mixed-Integer Linear Programming) problem as a tool of prescriptive analytics which can be used to perform the optimal design. Finally, a review of the state of the art of optimal design algorithms and case studies are reported and the main contributions of the present work are underlined. Chapter 4 introduces the first step towards this thesis objective. At first a deterministic mathematical model capable of performing the optimal design of a single-vector (electricity) energy hub integrated with EVs (Electric Vehicles) infrastructure is reported and applied to the case of a single-family dwelling. The considered technologies are photovoltaic, electric storage systems and charging infrastructures. Later the complexity of the model is increased, by proposing a stochastic mathematical model capable of performing the optimal design of a single-vector energy hub integrated with EVs infrastructure. The model is applied to the Mensa building of the Savona Campus of the University of Genova. Several objective functions are considered and the results are reported and commented. Chapter 5 increases the complexity of the study by introducing a deterministic mathematical model to perform the optimal design of a multi-vector energy hub. Several energy demands are considered (electricity, space heating and cooling, domestic hot water) and the portfolio of technologies is significantly expanded involving electric and thermal RES (Renewable Energy Sources), micro cogeneration units, trigeneration units, conversion units (reversible heat pumps), electric and thermal storage systems and EVs charging infrastructures. A multi-objective function is implemented. The model is applied to the entirety of the Savona Campus of the University of Genova. Chapter 6 reports the final and complete version of the developed mathematical model. This model is able to perform the optimal design of several multi-vector energy hubs, integrated with EVs charging stations, jointly acting as an energy community. The model is then applied to the Opera Pia Engineering compound of the University of Genova through the analysis of two different cases. At first a purely virtual relationship between several hubs is considered similarly to the Italian implementation of the renewable energy community concept. Later, a physical relationship between hubs is investigated similarly to the Spanish implementation of the renewable energy community configuration. Finally, Chapter 7 reports the conclusions and possible future research activities

Optimal Scheduling of Energy Storage for Energy Shifting and Ancillary Services to the Grid

This thesis is mainly focused on developing optimization-based models for scheduling of energy storage units. At first, a real-time optimal scheduling algorithm is developed seeking to maximize the storage revenue by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices. The electricity price modulation is proposed as an approach to competitively offer incentive by the utility regulator to storage to fill the gap between current and a stable rate of return. Subsequently, the application of large-scale storage for congestion relief in transmission systems as an ancillary service to the grid is investigated. An algorithm is proposed for the following objectives: (i) to generate revenue primarily by exploiting electricity price arbitrage opportunities and (ii) to optimally prepare the storage to maximize its contribution to transmission congestion relief. In addition, an algorithm is proposed to enable independently operated, locally controlled storage to accept dispatch instructions issued by Independent System Operators (ISOs). While the operation of locally controlled storage is optimally scheduled at the owner’s end, using the proposed algorithm, storage is fully dispatchable at the ISO’s end. Finally, a model is proposed and analyzed to aggregate storage benefits for a large-scale load. The complete model for optimal operation of storage-based electrical loads considering both the capital and operating expenditures of storage is developed. The applications of the proposed algorithms and models are examined using real-world market data adopted from Ontario’s electricity market and actual load information from a large-scale institutional electricity consumer in Ontario

CINELDI Annual Report 2020

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Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication

Distributed Power Generation Scheduling, Modelling and Expansion Planning

Distributed generation is becoming more important in electrical power systems due to the decentralization of energy production. Within this new paradigm, new approaches for the operation and planning of distributed power generation are yet to be explored. This book deals with distributed energy resources, such as renewable-based distributed generators and energy storage units, among others, considering their operation, scheduling, and planning. Moreover, other interesting aspects such as demand response, electric vehicles, aggregators, and microgrid are also analyzed. All these aspects constitute a new paradigm that is explored in this Special Issue