• Energy Research

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

Power-to-gas (P2G) technology has been suggested as one way to balance the variability of renewable power generation and decarbonize the transport sector. This paper studies the application of P2G plant in a real Finnish municipal district heating system in a future situation where the European power and district heating sectors have been decarbonized. From the point of view of the district heating company, the P2G plant can act as fuel producer, CO2 sink and heat source. The district heating unit commitment (DHUC) model was used to optimize the full-year hourly resolved operation of a CHP CCS plant, heat boilers, heat pumps, P2G plant and heat storages. Capacity optimization of most plants was also done. The hourly power price variability was obtained from regional unit commitment and economic dispatch simulation of the North European region. We find that a P2G plant may be profitable in the system, starting with SNG value of 70 €/MWh and depending on the specific investment. The regional simulations show that the market value of SNG is greater than this, and we conclude that P2G is a viable option.

Power-to-gas technology has been proposed as one component for future energy systems facing decarbonization targets. This paper presents a power-to-gas focused open optimization model for studying cost efficient design and operation of future urban energy system. The model is able to distinguish the benefits of different configurations of power-to-gas by modelling several energy vectors, including electricity, heating, and cooling alongside with different plant components.The usefulness of the built multi-vector model is illustrated by a case study where the benefits of power-to-gas are studied in the context of a medium-sized Nordic city. The results show that the city is able to reach carbon neutrality with the help of power-to-gas. Power-to-gas provides cost savings by reducing the need of heat storages and transmission capacity. The savings are greatest when the emission reduction goal is high and transmission capacity expansion is expensive. Direct air capture appears as the superior carbon dioxide source when compared to post combustion capture from flue gases due to costs and annual availability. The case study shows no economic benefit for distributed power-to-gas.

When identifying and comparing forecasting models, there may be a risk that poorly selected criteria could lead to wrong conclusions. Thus, it is important to know how sensitive the results are to the selection of criteria. This contribution aims to study the sensitivity of the identification and comparison results to the choice of criteria. It compares typically applied criteria for tuning and performance assessment of load forecasting methods with estimated costs caused by the forecasting errors. The focus is on short-term forecasting of the loads of energy systems. The estimated costs comprise electricity market costs and network costs. We estimate the electricity market costs by assuming that the forecasting errors cause balancing errors and consequently balancing costs to the market actors. The forecasting errors cause network costs by overloading network components thus increasing losses and reducing the component lifetime or alternatively increase operational margins to avoid those overloads. The lifetime loss of insulators, and thus also the components, is caused by heating according to the law of Arrhenius. We also study consumer costs. The results support the assumption that there is a need to develop and use additional and case-specific performance criteria for electricity load forecasting.

The evolving nature of electricity production, transmission, and consumption necessitates an update to the IEEE's Reliability Test System (RTS), which was last modernized in 1996. The update presented here introduces a generation mix more representative of modern power systems, with the removal of several nuclear and oil-generating units and the addition of natural gas, wind, solar photovoltaics, concentrating solar power, and energy storage. The update includes assigning the test system a geographic location in the southwestern United States to enable the integration of spatio-temporally consistent wind, solar, and load data with forecasts. Additional updates include common RTS transmission modifications in published literature, definitions for reserve product requirements, and market simulation descriptions to enable benchmarking of multi-period power system scheduling problems. The final section presents example results from a production cost modeling simulation on the updated RTS system data.

Power-to-gas and other chemicals-based storages are often suggested for energy systems with high shares of variable renewable energy. Here we study the North European power and district heat system with alternative long-term storage, the power-to-ammonia (P2A) technology. Assuming fully renewable power and heat sectors and large-scale electrification of road transport, we perform simultaneous optimization of capacity investments and dispatch scheduling of wind, solar, hydro and thermal power, energy storages as well as transmission, focusing on year 2050. We find that P2A has three major roles: it provides renewable feedstock to fertilizer industry and it contributes significantly to system balancing over both time (energy storage) and space (energy transfer). The marginal cost of power-based ammonia production in the studied scenarios varied between 431 and 528 €/t, which is in the range of recent ammonia prices. Costs of P2A plants were dominated by electrolysis. In the power and heat sector, with our cost assumptions, P2A becomes competitive compared to fossil natural gas only if gas price or CO2 emission price rises above 70 €/MWh or 200 €/tCO2.