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Industry is a large electricity user. China’s chemical industry (globally the largest based on sales) contributes 7% to China’s GDP, while it consumes 11% of the total electricity consumption in industry and is responsible for 40% of total CO2eq, 40% of SO2, 59% of NOx and 18% of PM-emissions of the chemical industry emissions. The heterogeneity of GHG and air pollutant emissions across electricity grids (within a country) is rarely included in analyses. In this paper, electricity conservation supply curves are developed (distinguishing the grids) to estimate the cost-effective and technical potentials of electricity conservation in China’s chemical industry. The emission factors per grid for GHG (i.e. CO2, CH4 and N2O) and air pollutants (i.e. SO2, NOx and PM2.5) are calculated and used to quantify the emissions mitigation achieved by electricity saving technologies in the chemical industry for the period 2012–2035. Results show that significant multiple benefits can be obtained by implementing electricity efficiency measures. There are large differences among the six grids in terms electricity savings and emissions abatement of GHG and air pollutants. 83% of the total electricity saving potential is contributed by the North, Northwest and Central grids, equal to 32% of baseline electricity consumption in 2035. In 2035, 129 Mt of CO2, 33 kt CO2eq of CH4, 571 kt CO2eq of N2O, 235 kt of SO2, 275 kt of NOx and 52 kt of PM2.5 in these three grids can be avoided as a result of electricity savings (a reduction of 31–33% compared to baseline emissions). When decision-makers set targets for energy saving and emission reduction, the multiple benefits and grid heterogeneity should not be ignored.

In 2015, industrial sector installations included in the European emission trading system (EU ETS) emitted 574 Mt CO2-equivalent Greenhouse gas (GHG) emissions. Among them are production of clinker, lime and ammonia, blast furnace operations, refineries and others. The emission intensity of these installations is closely tied to the fuel type used. Global warming scenarios of 1.5 °C recently presented by the IPCC require fast emission reduction in all sectors until 2030, followed by deep reductions, reaching carbon neutrality around 2050. In this paper, the technical potential to use biomass and electricity with existing or available technologies in important industrial processes is reviewed. The investigated industries account for 95% of the total verified emissions in the EU ETS industrial sector 2015 and 64% of total industrial emissions of the EU28. We find that 34% (184 Mt) of these emissions could be avoided from a technical perspective until 2030 with fuel switch measures towards biomass and electricity. This reduction is in line with 1.5 °C global warming scenarios until 2030, but further effort is required beyond that. We also find that available options lack economic competitiveness under present conditions, e.g. due to high electricity prices. We conclude that, although considerable fast emission saving potential by switching to biomass and electricity are possible, deep decarbonisation in line with climate targets requires innovative production processes only available in the long term.

Wind power is an important technology in the transition towards a low carbon economy. This paper covers the regional impacts of wind power developments in a small German region. Wind power developments with a cumulative capacity of 63.1 MW which have been installed in 2017 in the Aachen region, generating 3901 GWh electricity from 2017 to 2037 lead to a regional value added of €50.8 million (or €805/kW). The avoided greenhouse gas emissions are 132,770 tCO2-equivalents in 2017 and the total economic impacts of value added, avoided greenhouse gases and air pollution ranging from €20.9 to €24.6 million (€332–389 per kW or €107–126 per MWh electricity generated) in 2017. From an environmental economic view, the generation of wind power is the most beneficial electricity generation technology in comparison to PV and lignite.

Residential and commercial photovoltaic (PV) battery systems are increasingly being deployed for local storage of excess produced PV energy. However, battery systems aimed at increasing self-consumption are not constantly put to use. Additional battery storage capacity is available for a second application to improve the profitability of an energy storage system. One of these options is the provision of frequency restoration reserves (FRR) to the electricity balancing market. This provision can be either negative to compensate for excess power supply, or positive to compensate for excess demand on the power market. This study assesses the benefits for residential and commercial PV-battery systems by combining PV energy storage for higher self-consumption with provision of FRR. Six battery storage dispatch strategies were developed and assessed on the technical and economic performance of 48 residential and 42 commercial PV-battery systems. These systems were modelled over their economic lifetime with a time resolution of 5 min and with historical energy consumption measurements and market prices. FRR provision results in a small drop in the self-consumption rate of 0.5%. However annual revenues are significantly increased. Using battery storage systems only for self-consumption is not profitable with the assumptions used in this study. Provision of negative FRR substantially reduces the electricity bought with the consumption tariff and increases investment attractiveness substantially. Prioritizing the provision of FRR over self-consumption enhancement results in even higher revenues, but significantly reduces self-consumption. We recommend FRR provision to economically investment in residential battery storage systems. Commercial systems need prioritization of both positive and negative FRR provision over self-consumption for a cost-effective investment. In conclusion, combining enhancement of PV self-consumption with the provision of frequency restoration reserves leads to profitable investments.

Cities have a significant potential to host residential photovoltaic systems (PV). The direct consumption of PV generated electricity reduces the need for electricity import, while excess PV electricity production can be stored for later usage or can be used directly to charge electric vehicles (EVs). In this way, more energy is locally consumed, greenhouse gas emissions are reduced, and self-sufficiency of cities can be increased. In this paper, we present a spatio-temporal framework to evaluate the electricity demand that can be fulfilled by PV energy. We assess the impact of penetration of EVs and the influence of battery energy storage. We demonstrate the usefulness of this framework for 88 neighbourhoods in the city of Utrecht, the Netherlands. Spatial mapping was used to identify areas with high potential for EVs and storage. Results shows that direct PV self-consumption ratios vary between 34% and 100%. When EVs charging is included in the neighbourhoods, then self-consumption is increased on average by 12%. Battery energy storage increases the self-consumption with an average of 25%. The self-sufficiencies due to direct PV energy consumption are between 6% and 40% in the neighbourhoods. These are decreased by EVs with an average of −0.6%, and increased by battery energy storage with an average of 14%. Avoided life cycle greenhouse gas emissions over a 30-year period are on average 12 tCO2-eq per address. The large variation in results between neighbourhoods indicates that area dependent investments and supporting policies could improve the PV power integration in cities. Our developed framework can be easily adapted and used for other cities. Moreover, our results are useful for local governments to guide and design effective policies to accelerate the transition to more sustainable cities.

Photovoltaic (PV) systems are increasingly deployed on buildings in urban areas, causing additional power flows and frequency fluctuation on the low voltage electricity grid. Control strategies for PV-battery energy storage systems (BESS) assist in reducing power flows to the grid and improve the self-consumption of PV generated electricity. Therefore, these control strategies require accurate forecasts of PV electricity production and electricity consumption. We developed and assessed relatively simple forecasting methods using 5 min resolution data, to predict the PV yield and to forecast electricity consumption for one year. We used these forecasts with a predictive control strategy to increase PV self-consumption, decrease curtailment losses and improve BESS revenues. Electricity demand patterns of 48 residential and 42 commercial Dutch buildings were used. PV yield forecast methods that uses predicted weather data shows the lowest forecast error. The best performing forecast method for predicting energy consumption of residential buildings requires historical energy consumption data of the previous seven days. Commercial systems require historical energy consumption of the previous weekday. Significant reduction in curtailment losses is achieved using predictive control strategies, especially in combination when clear-sky radiation data is used to forecast PV yield. Similar self-consumption rates were found for predictive control as for real-time control. This indicates that reduction of curtailment loss can be combined while maintaining the level of PV self-consumption. Revenues from battery storage are increased by forecast methods and are highly dependable on boundary condition of a PV-battery system, such as the feed-in limit (FIL) and the feed-in tariff. Therefore, we recommend customizing battery control strategies based on these system boundaries conditions to improve energy storage potential.

The industry sector is a major energy consumer and GHG emitter. Effective climate change mitigation strategies will require a significant reduction of industrial emissions. To better understand the variations in the projected industrial pathways for both baseline and mitigation scenarios, we compare key input and structure assumptions used in energy-models in relation to the modeled sectors' mitigation potential. It is shown that although all models show in the short term similar trends in a baseline scenario, where industrial energy demand increases steadily, after 2050 energy demand spans a wide range across the models (between 203 and 451 EJ/yr). In Non-OECD countries, the sectors energy intensity is projected to decline relatively rapidly but in the 2010–2050 period this is offset by economic growth. The ability to switch to alternative fuels to mitigate GHG emissions differs across models with technologically detailed models being less flexible in switching from fossil fuels to electricity. This highlights the importance of understanding economy-wide mitigation responses and costs and is therefore an area for improvements. By looking at the cement sector in more detail, we show that analyzing each industrial sub-sector separately can improve the interpretation and accuracy of outcomes, and provide insights in the feasibility of GHG abatement.

Paper production is an energy-intensive process and accounted for about 9% of industrial energy demand in Germany in 2008. There have only been slow improvements in energy efficiency in the paper industry over the past twenty years. Policies can accelerate the progress made, but knowledge about the remaining efficiency potentials and their costs is a prerequisite for their success. We assess 17 process technologies to improve energy efficiency in the German pulp and paper industry up to 2035 using a techno-economic approach. These result in a saving potential of 34 TJ/a for fuels and 12 TJ/a for electricity, which equal 21% and 16% of fuel and electricity demand, respectively. The energy savings can be translated into mitigated CO2 emissions of 3 Mt. The larger part of this potential is found to be cost-effective from a firm's perspective. The most influential technologies are heat recovery in paper mills and the use of innovative paper drying technologies. In conclusion, significant saving potentials are still available, but are limited if we assume that current paper production processes will not change radically. Further savings would be available if the system boundaries of this study were extended to e.g. include cross-cutting technologies.

The cement sector is one of the fast growing economic sectors in Ethiopia. In 2010, it consumed 7 PJ of primary energy. We evaluate the potential for energy savings and CO2 emission reductions. We start by benchmarking the energy performance of 8 operating plants in 2010, and 12 plants under construction. The benchmarking shows that the energy intensity of local cement facilities is high, when compared to the international best practice, indicating a significant potential for energy efficiency improvement. The average electricity intensity and fuel intensity of the operating plants is 34% and 36% higher. For plants under construction, electricity use is 36% and fuel use 27% higher. We identified 26 energy efficiency measures. By constructing energy conservation supply curves, the energy-efficiency improvement potential is assessed. For the 8 operating plants in 2010, the cost-effective energy savings equal 11 GWh electricity and 1.2 PJ fuel, resulting in 0.1 Mt CO2 emissions reduction. For the 20 cement plants expected to be in operation by 2020, the cost-effective energy saving potentials is 159 GWh for electricity and 7.2 PJ for fuel, reducing CO2 emissions by about 0.6 Mt. We discuss key barriers and recommendations to realize energy savings.

Accurate knowledge on the technical potential for Building Integrated PhotoVoltaics (BIPV) in the various member states of the European Union is unavailable. To estimate the potential for BIPV we developed a method using readily available statistical data on buildings from European databases. Based on country-specific data on building characteristics and irradiation we estimate the BIPV technical potential in the EU-27 at 951 GWp. Installed it can deliver about 840 TWh of electricity, which is equivalent to more than 22% of the expected European 2030 annual electricity demand.

The chemical and petrochemical sector is by far the largest industrial energy user, accounting for 30% of the industry's total final energy use. However, due to its complexity its energy efficiency potential is not well understood. This article analyses the energy efficiency potential on a country level if Best Practice Technologies (BPT) were implemented in chemical processes. Two approaches are applied and an improved dataset referring to Europe has been developed for BPT energy use. This methodology has been applied to 66 products in fifteen countries that represent 70% of chemical and petrochemical sector's energy use worldwide. The results suggest a global energy efficiency potential of 16% for this sector, excluding savings in electricity use and by higher levels of process integration, combined heat and power (CHP) and post-consumer plastic waste treatment. The results are more accurate than previous estimates. The results suggest significant differences between countries, but a cross-check based on two different methods shows that important methodological and data issues remain to be resolved. Further refinement is needed for target setting, monitoring and informing energy and climate negotiation processes. For the short and medium term, a combination of benchmarking and country level analysis is recommended.

Moving to a sustainable industry and weaning electricity supply off coal are critical to mitigate ambient air pollution and climate change. This is particularly true in China which is globally the largest manufacturer and relies heavily on coal-fired electricity. Three key knowledge gaps are relevant in this thesis: 1) how much electricity can saved in China’s industries; 2) what is the potential impact of industrial electricity savings on the evolution of electricity supply systems among different power grids; and 3) what is the relationship between electricity use, energy efficiency investments, GHG and air pollution emissions, on various spatial scales. Given the identified knowledge gaps, the objective of this thesis is to conduct an in-depth analysis of electricity saving potentials and cost-benefits of emission mitigation due to scaling up energy efficiency in industries. Our research targets industrial electric efficiency improvements in China, where electricity supply heavily depends on a coal-fired power plant fleet and faces multiple challenges to a sustainable future. Our research presents that improving energy efficiency in industry can help reshape electricity systems to combat global warming and air pollution cost-effectively, not only in China but for the countries where electricity use is likewise dominated by industry and heavily dependent on coal-based electricity, such as India, Germany, Poland, The Netherlands, and South Africa. We suggest that national policymakers who aim to co-control air pollutants and carbon emissions through decreasing the dependency on coal-intensive electricity need to recognize the importance of concurrent efforts to improve demand-side electricity use efficiency.