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Heat demand dominates the final energy use in northern cities. This study examines how changes in heat demand may affect solutions for zero-emission energy systems, energy system flexibility with variable renewable electricity production, and the use of existing energy systems for deep decarbonization. Helsinki city (60 °N) in the year 2050 is used as a case for the analysis. The future district heating demand is estimated considering activity-driven factors such as population increase, raising the ambient temperature, and building energy efficiency improvements. The effect of the heat demand on energy system transition is investigated through two scenarios. The BIO-GAS scenario employs emission-free gas technologies, bio-boilers and heat pumps. The WIND scenario is based on large-scale wind power with power-to-heat conversion, heat pumps, and bio-boilers. The BIO-GAS scenario combined with a low heat demand profile (−12% from 2018 level) yields 16% lower yearly costs compared to a business-as-usual higher heat demand. In the WIND-scenario, improving the lower heat demand in 2050 could save the annual system 6–13% in terms of cost, depending on the scale of wind power.
Vahid Arabzadeh; Peter D. Lund. Effect of Heat Demand on Integration of Urban Large-Scale Renewable Schemes—Case of Helsinki City (60 °N). Energies 2020, 13, 2164 .
AMA StyleVahid Arabzadeh, Peter D. Lund. Effect of Heat Demand on Integration of Urban Large-Scale Renewable Schemes—Case of Helsinki City (60 °N). Energies. 2020; 13 (9):2164.
Chicago/Turabian StyleVahid Arabzadeh; Peter D. Lund. 2020. "Effect of Heat Demand on Integration of Urban Large-Scale Renewable Schemes—Case of Helsinki City (60 °N)." Energies 13, no. 9: 2164.
This paper presents deep decarbonization strategies for city-level energy systems. Helsinki city is used as a case in the analysis. The strategies are mainly based on extensive electrification employing renewable electricity, storage, and sector-coupling strategies. We perform energy, economic, and resilience analyses for the different cases. An energy balance model with 1-h resolution is used to optimize the energy system on macro-scale, while a MILP-algorithm is used for micro-level optimization of operation of individual plants against different criteria. The results indicate that a zero-carbon energy system is feasible by 2050, but it would also require coupling to the exogenous energy system (national electricity market) to balance mismatches. Power-to-heat coupling, or storage alone would not be adequate. As an example of system dynamics limitations, with a wind power capacity of 1.5 GW corresponding to 56% of the annual electricity demand in Helsinki, 90% of the wind electricity can be used locally in the different sectors, but the rest needs coupling to the exogenous market due to mismatch and plant limitations. The decarbonization strategies with increasing variable renewable energy production generally improve the resilience of the energy system, but with some concerns to adequacy of peak production and electricity dependency of heating.
Vahid Arabzadeh; Jani Mikkola; Justinas Jasiūnas; Peter D. Lund. Deep decarbonization of urban energy systems through renewable energy and sector-coupling flexibility strategies. Journal of Environmental Management 2020, 260, 110090 .
AMA StyleVahid Arabzadeh, Jani Mikkola, Justinas Jasiūnas, Peter D. Lund. Deep decarbonization of urban energy systems through renewable energy and sector-coupling flexibility strategies. Journal of Environmental Management. 2020; 260 ():110090.
Chicago/Turabian StyleVahid Arabzadeh; Jani Mikkola; Justinas Jasiūnas; Peter D. Lund. 2020. "Deep decarbonization of urban energy systems through renewable energy and sector-coupling flexibility strategies." Journal of Environmental Management 260, no. : 110090.
The Paris Climate Accord calls for urgent CO2 reductions. Here we investigate low and zero carbon pathways based on clean electricity and sector coupling. Effects from different spatialities are considered through city and national cases (Helsinki and Finland). The methodology employs techno-economic energy system optimization, including resilience aspects. In the Finnish case, wind, nuclear, and biomass coupled to power-to-heat and other flexibility measures could provide a cost-effective carbon-neutral pathway (annual costs −18%), but nuclear and wind are, to some extent, exclusionary. A (near) carbon-neutral energy system seems possible even without nuclear (−94% CO2). Zero-carbon energy production benefits from a stronger link to the broader electricity market albeit flexibility measures. On the city level, wind would not easily replace local combined heat and power (CHP), but may increase electricity export. In the Helsinki case, a business-as-usual approach could halve emissions and annual costs, while in a comprehensive zero-emission approach, the operating costs (OPEX) could decrease by 87%. Generally, electrification of heat production could be effective to reduce CO2. Low or zero carbon solutions have a positive impact on resilience, but in the heating sector this is more problematic, e.g., power outage and adequacy of supply during peak demand will require more attention when planning future carbon-free energy systems.
Sannamari Pilpola; Vahid Arabzadeh; Jani Mikkola; Peter D. Lund. Analyzing National and Local Pathways to Carbon-Neutrality from Technology, Emissions, and Resilience Perspectives—Case of Finland. Energies 2019, 12, 949 .
AMA StyleSannamari Pilpola, Vahid Arabzadeh, Jani Mikkola, Peter D. Lund. Analyzing National and Local Pathways to Carbon-Neutrality from Technology, Emissions, and Resilience Perspectives—Case of Finland. Energies. 2019; 12 (5):949.
Chicago/Turabian StyleSannamari Pilpola; Vahid Arabzadeh; Jani Mikkola; Peter D. Lund. 2019. "Analyzing National and Local Pathways to Carbon-Neutrality from Technology, Emissions, and Resilience Perspectives—Case of Finland." Energies 12, no. 5: 949.
Finding the global optimal combination of the main components for a solar thermal energy system is an important topic in utilising solar radiation in a cost-effective way. However, selecting an optimal solar thermal system in a cold climate condition is a challenging task due to the dependency on the heat demand and the limited availability of solar radiation. This research presents several sets of optimum combinations of a solar thermal collector and a hot water storage tank regarding energy efficiency and the life cycle cost. Since domestic hot water consumption forms the significant part of the heat demand in new energy efficient apartment buildings, the applied consumption information were extracted precisely according to measured data. The solar thermal system with cost-optimal component sizes was able to save district heat energy consumption up 24% to 34% and made 4 €/m^2 to 23 €/m^2 in financial profit.
Vahid Arabzadeh; Juha Jokisalo; Risto Kosonen. A cost-optimal solar thermal system for apartment buildings with district heating in a cold climate. International Journal of Sustainable Energy 2018, 38, 141 -162.
AMA StyleVahid Arabzadeh, Juha Jokisalo, Risto Kosonen. A cost-optimal solar thermal system for apartment buildings with district heating in a cold climate. International Journal of Sustainable Energy. 2018; 38 (2):141-162.
Chicago/Turabian StyleVahid Arabzadeh; Juha Jokisalo; Risto Kosonen. 2018. "A cost-optimal solar thermal system for apartment buildings with district heating in a cold climate." International Journal of Sustainable Energy 38, no. 2: 141-162.
The present article describes the integration of a data-driven predictive demand response control for residential buildings with heat pump and on-site energy generation. The data driven control approach schedules the heating system of the building. In each day, the next 24 hours heating demand of buildings, including space heating and domestic hot water consumption, are predicted by means of a hybrid wavelet transformation and a dynamic neural network. Linear programming is implemented to define a cost-optimal schedule for the heat pump operation. Moreover, the study discusses the impact of heat demand prediction error on performance of demand response control. In addition, the option of energy trading with the electrical grid is considered in order to evaluate the possibility of increasing the profit for private householders through on-site energy generation. The results highlight that the application of the proposed predictive control could reduce the heating energy cost up to 12% in the cold Finnish climate. Furthermore, on-site energy generation declines the total energy cost and consumption about 43% and 24% respectively. The application of a data-driven control for the demand prediction brings efficiency to demand response control.
Vahid Arabzadeh; Behrang Alimohammadisagvand; Juha Jokisalo; Kai Siren. A novel cost-optimizing demand response control for a heat pump heated residential building. Building Simulation 2017, 11, 533 -547.
AMA StyleVahid Arabzadeh, Behrang Alimohammadisagvand, Juha Jokisalo, Kai Siren. A novel cost-optimizing demand response control for a heat pump heated residential building. Building Simulation. 2017; 11 (3):533-547.
Chicago/Turabian StyleVahid Arabzadeh; Behrang Alimohammadisagvand; Juha Jokisalo; Kai Siren. 2017. "A novel cost-optimizing demand response control for a heat pump heated residential building." Building Simulation 11, no. 3: 533-547.