Requirements to Testing of Power System Services Provided by DER Units

The present report forms the Project Deliverable ‘D 2.2’ of the DERlab NoE project, supported by the EC under Contract No. SES6-CT-518299 NoE DERlab. The present document discuss the power system services that may be provided from DER units and the related methods to test the services actually provided, both at component level and at system level

Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method

Microgrid energy management is a challenging and important problem in modern power systems. Several deterministic and stochastic models have been proposed in the literature for the microgrid energy management problem. However, more accurate models are required to enhance flexibility of the microgrids when accounting for renewable energy and load uncertainties. This thesis proposes key contributions to solve the energy management problem for smart building (or small-scale microgrid). In Chapter 3, a deterministic energy management model is presented taking into account system flexibility requirements. Energy storage systems are deployed to enhance the grid flexibility and ramping capability. The objective function of the formulated optimization is to minimize the operation cost. Combined heat and power (CHP) units, which interconnect heat and electricity, are modeled. Thus, electricity and thermal generation and load constraints are formulated. To account for uncertainties of load and renewable energy resources (e.g., solar generation), a stochastic energy management model is proposed in Chapter 4. A data-driven chance-constrained optimization is based method is formulated. The proposed model is nonparametric that imposes no assumption on probability distribution functions (PDFs) of the random variables (i.e., load and renewable generation). Adaptive kernel density estimation is deployed to estimate a nonparametric PDF for each random variable. Confidence levels (risk levels) of the chance constraints are modified according to estimation errors. Several cases are simulated to analyze the deterministic and stochastic optimization models. The simulation results show that the proposed data-driven chance-constrained optimization with the flexibility constraints enhance reliability, resiliency, and economics of the microgrid energy systems. Note that these flexibility constraints avoid propagating solar and load fluctuations to the distribution feeder. That is smart building (microgrid) is capable of capturing fluctuations locally

Control Architecture Modeling for Future Power Systems

Uncontrollable power generation, distributed energy resources, controllable demand, etc. are fundamental aspects of energy systems largely based on renewable energy supply. These technologies have in common that they contradict the conventional categories of electric power system operation. As their introduction has proceeded incrementally in the past, operation strategies of the power system could be adapted. For example much more wind power could be integrated than originally anticipated, largely due to the flexibility reserves already present in the power system, and the possibility of interregional electricity exchange. However, at the same time, it seems that the overall system design cannot keep up by simply adapting in response to changes, but that also new strategies have to be designed in anticipation. Changes to the electricity markets have been suggested to adapt to the limited predictability of wind power, and several new control strategies have been proposed, in particular to enable the control of distributed energy resources, including for example, distributed generation or electric vehicles. Market designs addressing the procurement of balancing resources are highly dependent on the operation strategies specifying the resource requirements. How should one decide which control strategy and market configuration is best for a future power system? Most research up to this point has addressed single isolated aspects of this design problem. Those of the ideas that fit with current markets and operation concepts are lucky; they can be evaluated on the present design. But how could they be evaluated on a potential future power system? Approaches are required that support the design and evaluation of power system operation and control in context of future energy scenarios. This work addresses this challenge, not by providing a universal solution, but by providing basic modeling methodology that enables better problem formulation and by suggesting an approach to addressing the general chicken/egg problem of planning and re-design of system operation and control. The dissertation first focuses on the development of models, diagrams, that support the conceptual design of control and operation strategies, where a central theme is the focus on modeling system goals and functions rather than system structure. The perspective is then shifted toward long-term energy scenarios and adaptation of power system operation, considering the integration of energy scenario models with the re-design of operation strategies. The main contributions in the first part are, firstly, by adaptation of an existing functional modeling approach called Multilevel Flow Modeling (MFM) to the power systems domain, identifying the means-ends composition of control levels and development of principles for the consistent modeling of control structures, a formalization of control-as-a-service; secondly, the formal mapping of fluctuating and controllable resources to a multi-scale and multi-stage representation of control and operation structures; and finally the application to some concrete study cases, including a present system balancing, and proposed control structures such as Microgrids and Cells. In the second part, the main contributions are the outline of a formation strategy, integrating the design and model-based evaluation of future power system operation concepts with iterative energy scenario development. Finally, a new modeling framework for development and evaluation of power system operation in context of energy-storage based power system balancing is introduced.<br/

Modeling a cooperation environment for flexibility enhancement in smart multi-energy industrial systems

Environmental aspects have been highlighted in architecting future energy systems where sustainable development plays a key role. Sustainable development in the energy sector has been defined as a potential solution for enhancing the energy system to meet the future energy requirements without interfering with the environment and energy provision. In this regard, studying the cross-impact of various energy vectors and releasing their inherent operational flexibility is main topic. Thecoordinationofvariousenergyvectorsundertheconceptofmulti-energysystem (MES)hasintroducednewsourcesofoperationalflexibilitytothesystemmanagers. MES considers both interactions among the energy carriers and the decision makers in an interdependent environment to increase the total efficiency of the system and reveal the hidden synergy among energy carriers. This thesis addresses a framework for modeling multi-energy players (MEP) that are coupled based on price signal in multi-energy system (MES) in a competitive environment. MEP is defined as an energy player who can consume or deliver more than one type of energy carriers. At first, the course of evolution for the energy system from today independent energy systems to a fully integrated MES is presented and the fractal structure is described for of MES architecture. Moreover, the operational behavior of plug-in electric vehicles’ parking lots and multi-energy demands’ external dependency are modeled in MES framework to enhance the operational flexibility of local energy systems (LES). In the fractal environment, there exist conflicts among MEPs’ decision making in a same layer and other layers. Realizing the inherent flexibility of MES is the main key for modeling the conflicts in this multi-layer structure. The conflict between two layers of players is modeled based on a bi-level approach. In this problem, the first level is the MEP level where the player maximizes its profit while satisfying LES energy exchange. The LES’s exchange energy price is the output of this level. In the lower level, the LESs schedule their energy balance, based on the upper level input price signal. The problem is transformed into a mathematical program with equilibrium constraint (MPEC) through duality theory. In the next step, high penetration of multi-energy players in the electricity market is modeled and their impacts on electricity market equilibrium are investigated. In such a model, MEP participates in the local energy and wholesale electricity markets simultaneously. MEP and the other players’ objectives in these two markets conflict with each other. Each of these conflicts is modeled based on bi-level programming. The bi-level problems are transformed into a single level mixed-integer linear problem by applying duality theory

Power-to-X in Energy Hubs: Operations and Policies Supporting the Scale-Up of Renewable Fuel Production

Power-to-X (P2X) needs to scale up rapidly to provide the fuels required in the hard-to-decarbonize industrial and heavy transport sector. Only recently, the European Commission proposed requirements for \textit{renewable} fuels. P2X energy hubs enable efficient synergies between energy infrastructures, production facilities, and storage options. In this study, we explore the optimal operation of an energy hub by leveraging the flexibility of P2X including hydrogen, methanol, and ammonia synthesizers, and analyze potential revenue streams such as the day-ahead and ancillary service markets. We propose EnerHub2X, a mixed-integer linear program that maximizes the hub's profit based on current market prices, considering technical constraints of P2X such as unit commitment and non-linear efficiencies. We model a representative Danish energy hub and find that without price incentives, it mainly produces liquid hydrogen and sells renewable electricity. Only by adding a price premium of about 50\% (0.16 \euro{}/kg) to the conventional fuel prices, sufficient amounts of renewable ammonia and methanol are produced. To utilize production efficiently, on-site renewable capacity and P2X must be carefully aligned. We show that renewable power purchase agreements can provide flexibility while complying with the rules set by the European Commission

Whole-system assessment of the benefits of integrated electricity and heat system

The interaction between electricity and heat systems will play an important role in facilitating the cost effective transition to a low carbon energy system with high penetration of renewable generation. This paper presents a novel integrated electricity and heat system model in which, for the first time, operation and investment timescales are considered while covering both the local district and national level infrastructures. This model is applied to optimize decarbonization strategies of the UK integrated electricity and heat system, while quantifying the benefits of the interactions across the whole multi-energy system, and revealing the trade-offs between portfolios of (a) low carbon generation technologies (renewable energy, nuclear, CCS) and (b) district heating systems based on heat networks (HN) and distributed heating based on end-use heating technologies. Overall, the proposed modeling demonstrates that the integration of the heat and electricity system (when compared with the decoupled approach) can bring significant benefits by increasing the investment in the heating infrastructure in order to enhance the system flexibility that in turn can deliver larger cost savings in the electricity system, thus meeting the carbon target at a lower whole-system cost

Sustainable distribution network planning considering multi-energy systems and plug-in electric vehicles parking lots

Entre todos os recursos associados à evolução das redes elétricas para o conceito de smart grid, os sistemas de multi-energia e os veículos eléctricos do tipo plug-in (PEV) são dois dos principais tópicos de investigação hoje em dia. Embora estes recursos possam acarretar uma maior incerteza para o sistema de energia, as suas capacidades de demanda/armazenamento flexível de energia podem melhorar a operacionalidade do sistema como um todo. Quando o conceito de sistemas de multi-energia e os parques de estacionamento com estações de carregamento para os PEVs são combinados no sistema de distribuição, a demanda pode variar significativamente. Sendo a demanda de energia uma importante informação no processo de planeamento, é essencial estimar de precisa essa demanda. Deste modo, três níveis padrão de carga podem ser extraídos tendo em conta a substituição da procura entre carriers de energia, a demanda associada ao carregamento dos PEVs, e presença de parques de estacionamento com estações de carregamento no sistema. A presença de PEVs num sistema multi-energia obriga a outros requisitos (por exemplo, um sistema de alimentação) que devem ser fornecidos pelo sistema, incluindo as estações de carregamento. A componente elétrica dos PEVs dificulta a tarefa ao operador do sistema na tentativa de encontrar a melhor solução para fornecer os serviços necessários e utilizar o potencial dos PEVs num sistema multi-energia. Contudo, o comportamento sociotécnico dos utilizadores de PEVs torna difícil ao operador do sistema a potencial gestão das fontes de energia associada às baterias. Desta forma, este estudo visa providenciar uma solução para os novos problemas que irão ocorrer no planeamento do sistema. Nesta tese, vários aspetos da integração de PEVs num sistema multi-energia são estudados. Primeiro, um programa de resposta à demanda é proposto para o sistema multi-energia com tecnologias do lado da procura que possibilitem alternar entre fornecedores de serviços. Em seguida, é realizado um estudo abrangente sobre as questões relativas à modelação dos PEVs no sistema, incluindo a modelação das incertezas, as preferências dos proprietários dos veículos, o nível de carregamento dos PEV e a sua interação com a rede. Posteriormente é proposta a melhor estratégia para a participação no mercado de energia e reserva. A alocação na rede e os possíveis efeitos subjacentes são também estudados nesta tese, incluindo o modelo dos PEVs e dos parques de estacionamento com estações de carregamento nesse sistema de multi-energia.Among all resources introduced by the evolution of smart grid, multi-energy systems and plugin electric vehicles are the two main challenges in research topics. Although, these resources bring new levels of uncertainties to the system, their capabilities as flexible demand or stochastic generation can enhance the operability of system. When the concept of multienergy systems and plug-in electric vehicles (PEV) parking lots are merged in a distribution system, the demand estimation may vary significantly. As the main feed of planning process, it is critical to estimate the most accurate amount of required demand. Therefore, three stages of load pattern should be extracted taking into account the demand substitution between energy carriers, demand affected by home-charging PEVs, and parking lot presence in system. The presence of PEVs in a multi-energy system oblige other requirements (i.e. fueling system) that should be provided in the system, including charging stations. However, the electric base of PEVs adds to the responsibilities of the system operator to think about the best solution to provide the required services for PEVs and utilize their potentials in a multi-energy concept. However, the socio-technical behavior of PEV users makes it difficult for the system operator to be able to manage the potential sources of PEV batteries. As a result, this study tries to raise the solution to new problems that will occur for the system planners and operators by the future components of the system. In this thesis, various aspects of integrating PEVs in a multi-energy system is studied.Firstly, a carrier-based demand response program is proposed for the multi-energy system with the technologies on the demand side to switch between the carriers for providing their services. Then, a comprehensive study on the issues regarding the modeling of the PEVs in the system are conducted including modeling their uncertain traffic behavior, modeling the preferences of vehicle owners on the required charging, modeling the PEV parking lot behavior and its interactions with the network. After that the best strategy and framework for participating the PEVs energy in the energy and reserve market is proposed. The allocation of the parking lot in the network and the possible effects it will have on the network constraints is studied. Finally, the derived model of the PEVs and the parking lot is added to the multi-energy system model with multi-energy demand