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Many energy policies set a goal of decreasing the carbon emissions of the energy sector by up to 100%, including the electricity grid. This is a long term and gradual process. Energy systems in cities will likely be the starting point for greenhouse gas emissions mitigation since they account for 80% of global carbon emissions. This paper analyses the impact on urban districts of decarbonizing the electric grid supply. A multi-objective optimization model has been developed that combines the optimal design and operation of distributed energy systems, the design of district heating (DH), electricity grid constraints based on linearized alternating current (AC) power flow and grid upgrade options. A number of scenarios were defined corresponding to different levels of renewable energy share in the electricity grid. For each scenario, we analyse the changes to the design and operation of the urban energy system, the impact on the district heating potential, and the impact on the operation of the distribution grid as well as the grid upgrade potential. The results showed that the renewable share of the grid has a large impact on the optimal solutions obtained. When the renewable share is below 55%, a lot of photovoltaic (PV) electricity has to be used to offset the carbon emissions from the grid. Conversely, when the renewable share is above 70%, the use of PV decreases and heating systems become electrified by producing heat with heat pumps (HP). District heating is used regardless of the renewable share in the grid, but as carbon emissions limits are tightened the potential of DH decreases. Only when the renewable share in the electricity grid is 100% it is possible to have a carbon-neutral district. In the carbon optimal solutions of each scenario there is no need for DH, but the grid has to be upgraded to enable electrification of the heating system.

Electricity and transport sectors have to be decarbonised in order to mitigate climate change effects leading to increased penetration of distributed energy systems (DES) and electric vehicles (EV) which can threaten the security of distribution grid operation. Proper design and operation of such systems are crucial if the adverse effects on the grid are to be avoided. Moreover, EVs represent a high load and should not be considered merely as passive assets since they can provide various flexibility services for maintaining the grid stable. This paper presents a multi-domain optimisation framework for minimising carbon emission in low-voltage distribution grids with high share of distributed energy resources and electric vehicles. The framework determines optimal EV flexibility usage (both active and reactive) while satisfying electric and thermal building demands, and maintaining the distribution grid in the stable operation. The model was applied to a real low-voltage Danish distribution grid where measurement data is available on hourly basis in order to determine EV flexibility impacts on carbon emissions, as well as the benefits of optimal DES design. The influence of EV reactive power control on the grid operation, in addition to coordinated charging, is analysed. Results showed that when the system can be optimally designed, emissions decrease by 64% and additionally 32% with proactive EV integration, whereas EV reactive power control enables integration of larger EV amounts and provides significant voltage support without affecting the user comfort.

Distributed and decentralised energy systems coupled with district heating networks are promising concepts for achieving less carbon-intensive urban energy systems. This paper investigates the optimal design and operation of distributed energy systems as well as optimal heating network layouts for different economic and environmental objectives. A mixed integer linear programming model was used for multi-objective optimisation to minimize total cost and carbon emissions. Improvements include the coupling of equipment and network modelling across many buildings, detailed CHP operational constraints, the inclusion of network heat losses, and improved modelling of thermal storage. The model was used on a case study consisting of eleven residential buildings and one commercial building for various design scenarios (available technologies, network layout limitations, operating constraints). Design results (capacities, network layouts) and operational results (energy supply breakdowns) are presented. The results show that district heating can deliver emissions savings of 23% over a standard solution for the same cost. The optimal number of heating network links increases as more stringent carbon emissions targets are implemented. Limits on possible network routes have significant impacts on the optimal technology capacities and on operational schedules. Also, commonly neglected constraints on CHP operation cause noticeably more reliance on district heating networks.

The transition to 100% renewable energy systems is an important factor in the transition to sustainable energy systems. A top-down approach is often used to study the design of such energy systems on a country or continental scale. Results of these studies are useful for developing energy roadmaps but they lack the details about how distributed multi energy systems should be designed and operated at local level. An optimisation model of distributed multi energy systems is applied in order to investigate how urban districts should be optimally designed in the (near) future when the goals of energy roadmaps are achieved. The impact of individual and microgrid approaches on distributed multi energy systems is analysed on an urban district level for scenarios with different levels of renewable energy in the electricity grid supply., Energy Procedia, 122, ISSN:1876-6102, CISBAT 2017 International Conference Future Buildings & Districts – Energy Efficiency from Nano to Urban Scale

Distributed Multi-Energy Systems (D-MES) can sustainably transform the energy supply of buildings, districts, and communities by integrating multiple energy efficient technologies, renewable energy sources, and electricity, gas, and thermal energy networks to provide heating, cooling and electricity services. However, D-MES typically exhibit high levels of technical complexity and encompass various economic, environmental, and policy-related aspects. Consequently, energy models are needed to optimally design and operate D-MES and to analyze their performance in detail. A multitude of aspects must be considered when developing a D-MES model. A first aspect, for instance, is whether an optimization or a simulation approach is more appropriate for the model's scope. Moreover, it is important to accurately represent all the relevant technical characteristics and performance constraints of the various energy generation, storage and distribution network technologies in the model. Additionally, in many cases, adopting approaches from other domains like urban and building energy simulation might be required to identify building requirements for heating, cooling, and electricity. Additional aspects, such as the uncertainty of a model's parameters, which complicates D-MES design and operation decisions, or the computational burdens imposed by extending these models towards the whole-city scale also need to be considered. Finally, methods that can bridge models that focus on specific sub-dimensions of D-MES and allow for more holistic D-MES modeling need to be developed. This paper aims to address these key challenges and to outline recent developments in the field of modeling of D-MES by answering ten questions about the most relevant D-MES modeling dimensions.

The aim of this paper is to analyse how electrical storage and grid upgrades influence the optimal design and operation of a microgrid. A multi-objective (cost versus carbon emissions) mixed integer linear programming model is developed and applied to a microgrid case study. The optimisation model is based on the coupling of an energy hub modelling approach for system design and operation, and a linearized electrical grid model for steady-state power flow calculation in order to optimize the overall design and operation of a microgrid. The trade-off between electrical storage (ES) and grid upgrade options is examined and performance is compared to a reference case. Additionally, the optimal locations, capacities and charging power of an electrical storage are determined. The results showed that the grid upgrade is only viable in the lowest carbon emissions after the installation of the electrical storage.

This paper focuses on modeling and simulation of controllable Photovoltaic Battery Power System (PV BPS) interconnected to the electrical utility. After elaboration of modeling principles for different components appearing in the system, simulations of two types of PV plants connected to one branch of distribution network have been carried out. First one is connected through a three-phase inverter with battery string connected to a DC-link and the second string is connected to the grid in single phase configuration. In this proposed configuration unpredictable variations of irradiation and temperature are taken into an account and PV BPS is able to inject the power to the grid in regulated manner using developed power control algorithm.