Regional Energy Planning Research Articles

Optimizing biomass energy production at the municipal level to move to low-carbon energy

In this article, we seek to analyze the regional energy policy in the West Pomeranian Voivodeship, with a particular focus on the potential for developing renewable energy from biomass. The article aims to build a mathematical model of the regional energy system, related to the strategy of sustainable development in the region. Taking into account the potential for biomass development and the sustainability criteria, this paper presents a case study of sustainable regional energy planning and implementation in the selected region in Poland. An example of optimizing biomass for renewable use at the municipal level is valuable, as the use of biomass energy requires knowledge of landscapes, energy options, and different stakeholder perspectives. Thus, “energyscapes,” a complex spatial and temporary combination of energy supply, demand, and infrastructure within the landscape, can be very useful in this context. Ongoing research contributes to the development of knowledge on promoting renewable energy sources at the local level and supporting a fair transition to low-carbon energy through energy citizenship and the development of sustainable low-carbon communities at the regional level.

The derivation of sectoral and provincial implications from power sector scenarios using an integrated assessment model at Korean provincial level: GCAM-Korea

In South Korea, the 7th largest emitter in the world, many emissions reduction policies are implemented. The impact of the policies on the entire energy system at provincial level, however, has rarely been investigated. From this perspective, this paper provides geographically updated assessment of emissions reduction policies. This study adopts two opposite policies, a tax on coal-fired generation (Coal scenario) and a subsidy on PV generation (PV scenario). As an Integrated Assessment Model (IAM), GCAM-Korea, a version of GCAM with provincial level resolution of Korea, is applied in this study. GCAM-Korea can provide insights across provinces as well as sectors.Simulation results show that Coal scenario increases electricity price, while PV scenario decreases electricity price. With different conditions in each end-use sector, different responses are expected by this electricity price change. Industry sector, especially steel and iron manufacture industry, shows the most susceptible response to the electricity price change through substitution of electricity with coal. Under Coal scenario, higher electricity price causes larger coal consumption with smaller electricity consumption, while under PV scenario lower electricity price causes smaller coal consumption with larger electricity consumption. This inter sectoral impacts are directly transformed into inter provincial impacts. This transformation should be carefully handled, considering that the top five provinces accounted for 83 % of total industrial energy consumption in South Korea. Even though there is a large fraction of coal consumed in industry sector, the tax on coal has been imposed only on thermal coal under current energy price policy in Korea. A tax on industrial coal use as a whole could possibly buffer the negative impacts from non-taxed coal consumption in iron and steel industry. Further empirical examination is required to check the validity of this prediction from the model. Finally, the positive impact of emissions reduction by tax on coal fired generation, in turn, triggers negative externality on other provinces by causing more consumption of coal in industry sector. Even if this simulation results can not be quantified in terms of total amounts of benefit compared with total amounts of damages caused by this negative externality, the existence of distributional issue of emissions reduction at provincial level has been successfully demonstrated. GCAM-Korea is shown to capture the provincial level characteristics of energy system and it can be applied for the analysis of regional energy plan being conducted every 5 years by the Ministry of Trade, Industry and Energy, Korea.

A progressive alternative of energy planning for West Sumatera province

To ensure energy security for people, the Government develops energy planning, a plan that contains the baseline condition and projected energy consumption and energy supply in specific years. In West Sumatera Province’s Regional Energy Plan (RUED), The Local Government targeted 70.9% renewable energy share in its primary energy mix in 2050. The alternative scenario of power plant generation in West Sumatera base on the Regional Energy Plan Document for 2050 is developed in this paper. The share of renewable energy in the alternative scenario in 2050 is 100%. The alternative energy planning we design meet the expected electricity consumption each year. The Levelized Cost of energy for the alternative scenario cheaper than the RUED scenario in present value. With the rapid development of renewable energy technology, West Sumatera can achieve 100% renewable energy electricity in 2050 and give reasonable energy security confidence.

Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization

Wind-farm planning optimization is important for decision-making concerning regional energy planning in developing countries. This process is governed by restrictions on site selection based on land suitability metric variables, wind turbine technology variables, and land-use governing criteria. This study aims to create a framework for land appropriation strategies for locating optimum sites suitable for wind farms. It is using Jordan as an Area of Interest (AOI), where the scope is to illustrate how this framework will employ wind turbine energy to positively enhance the national Gross Domestic Product (GDP). The methodology employs thirteen GIS thematic layers with a 250-m spatial resolution to substantiate how site-specific criteria, turbine type, and turbine hub height variables are determining factors in the optimal solution. This method involves selecting relevant factors, database construction, data layer generation and preparation, numerical ranking and weighting of each factor, and computation of the potential wind farm locations map by overlaying all the thematic GIS layers. The results showed that the establishment of wind farms would not only meet the AOI’s growing energy needs, rather exceed them to generating income for the developing nation. The results of the feasibility study will boost the national GDP by 3.4%; where, for example, one governorate alone could produce 274.3% of the total required national consumption at a turbine hub height of 50 m. The study attests to a valuable framework that can be implemented elsewhere to establish regional power sustainability and feasibility for other nations. The results show that an added land-use layer indicating the potential value of land in terms of its suitability for establishing wind farms should be considered in future sustainable regional planning studies when considering networks for smart cities, industrial cities, smart agriculture, and new agglomerations.

Nearshore wave energy resource characterization along the East Coast of the United States

A feasibility level nearshore wave energy resource characterization is conducted for the East Coast of the United States using a 32-year (1979–2010) hindcast from a high-resolution unstructured-grid Simulating Waves Nearshore (SWAN) model with a spatial resolution of 200 m along the coastline. Wave energy resource attributes including wave energy potentials, seasonal variability, frequency and directional spreading, and extreme sea states are characterized using a broad range of resource parameters from which opportunities, risks, and constraints for wave energy conversion (WEC) projects are assessed. Cross-shore and alongshore variations of these parameters due to varying wave energy climate and coastline orientation relative to the dominant wave systems are examined. The present study also introduces a zero-crossing method for delineating wave energy climate regions based on a broad range of resource attributes beyond just wave power. Applying this method, eight nearshore wave energy climate regions are delineated for the East Coast; each region with a unique set of resource attributes to inform regional energy planning, WEC project development, conceptual WEC design, and the operation and maintenance of WEC projects.

Global Wave Energy Resource Classification System for Regional Energy Planning and Project Development

Global Wave Energy Resource Classification System for Regional Energy Planning and Project Development

상업·공공용 건물에너지의 지역별 소비 특성을 반영한 GCAM-Korea 모형 개선

Information on provincial level energy consumption pattern of commercial and public buildings, which account for about 49% of domestic building energy as of 2016, is not available yet. In this study, the analysis of provincial level energy consumption characteristics of overall commercial and public buildings is conducted, including small and medium-sized commercial and public buildings. Provincial level building energy consumption pattern is derived, utilizing 2017 Energy Consumption Survey for Commercial and public buildings conducted by KEEI (Korea Energy Economics Institute), presented in aggregated form by sector, fuel, and energy use type, without regional information, and 2017 population census on building establishments conducted by National Statistics Office, Korea. This disaggregated information resulting from this analysis is applied to GCAM-Korea (Global Change Assessment Model-Korea) for the better representation of the details of commercial and public buildings energy characteristics. As the result, the data show different energy consumption characteristics at provincial level. It is found that existing GCAM-Korea underestimates cooling and heating electricity energy while it overestimates other use types of electricity for commercial and public buildings at all regions. The results of this study shed light on regional energy plan for commercial and public buildings.

A framework for regional smart energy planning using volunteered geographic information

Abstract. This study presents a framework for regional smart energy planning for the optimal location and sizing of small hybrid systems. By using an optimization model – in combination with weather data – various local energy systems are simulated using the Calliope and PyPSA energy system simulation tools. The optimization and simulation models are fed with GIS data from different volunteered geographic information projects, including OpenStreetMap. These allow automatic allocation of specific demand profiles to diverse OpenStreetMap building categories. Moreover, based on the characteristics of the OpenStreetMap data, a set of possible distributed energy resources, including renewables and fossil-fueled generators, is defined for each building category. The optimization model can be applied for a set of scenarios based on different assumptions on electricity prices and technologies. Moreover, to assess the impact of the scenarios on the current distribution infrastructure, a simulation model of the low- and medium-voltage network is conducted. Finally, to facilitate their dissemination, the results of the simulation are stored in a PostgreSQL database, before they are delivered by a RESTful Laravel Server and displayed in an angular web application.

Contribution of the Basilicata region to decarbonisation of the energy system: results of a scenario analysis

This paper investigates the energy system of the Basilicata region (southern Italy) to highlight, through a scenario analysis, its possible future development in compliance with the European Commission's long-term vision. The IEA-ETSAP methodology was utilized to model and analyse the Basilicata energy system in a business-as-usual scenario, based on the assumptions of the 2010 Regional Energy and Environmental Policy Plan, and in two low-carbon scenarios, decarbonisation and high energy efficiency, which, in line with the long-term European strategy, foresee an 85% carbon dioxide emission reduction and a 20% energy efficiency increase in 2050. The results highlight that electricity production from renewable energy sources (in particular wind energy), strongly supported by the regional policy, goes beyond the Basilicata Regional Energy-Environmental Plan forecast, with a further increase in the decarbonisation scenarios. In addition, solar thermal and highly efficient technologies are adopted in commercial and residential end-use sectors. An additional 9% reduction in energy consumption is achieved in the high energy efficiency scenario by passive houses. The proposed approach shows the usefulness of a modelling framework typically used for national and supranational analyses to support regional authorities in their decision-making process to obtain results in line with the European and national strategies. Application to the Basilicata region shows the usefulness of a consolidated framework for policy assessment at a local scale to assess regional contribution to the achievement of national climate mitigation targets that tend towards climate neutrality.

Sub-national Energy Access Planning Model for Sustainable Development Goals: A Case Study of Barpak

As most nations have adopted the Sustainable Development agenda to achieve the 17 Sustainable Development Goals (SDGs) by 2030, it is vital that planning of energy systems at local, regional and national levels also align with the agenda in order to achieve the goals. This study explores the sustainability of primary energy resources of a rural community to meet growing demands of the community, in order to achieve SDGs for energy access Goal no. 7 (SDG7) at local level. Using a linear back-casting techno-economic energy access model that informs the expected change in energy demand in order to reach SDG7 targets, this study examined whether local energy resources would be enough to achieve the targets for Barpak VDC (named such at the time of data collection before Nepal’s administrative restructuring), and explored the possibility of importing electricity from national grid to attain SDG7 targets. By analyzing the outputs of the model for Barpak, we found that currently assessed local energy resources are insufficient to meet the energy access targets. Importing electricity from national grid, in addition to the mini-hydropower plant currently in operation at Barpak is needed to achieve the targets. Huge cost investment and timely expansion of transmission and distribution infrastructure is crucial. By 2030, total energy demand is expected to grow up to 50,000 Gigajoules per year. Electricity import from national grid grows steadily, reaching up to 45,000 Gigajoules in 2030. The social costs of energy will continue to be dominated by household sector till 2030, reaching up to 30 million Nepali Rupees per year in total. Use of wood as fuel, the only significant source of emission in the model is modeled to decrease linearly and stop by 2030, as required by SDGs. Emission of 17 Metric Tonnes of Carbon-dioxide and 4.5 million kg Methane equivalent is reduced to zero at 2030. This model serves as an innovative approach to integrate SDG targets to local and regional energy planning process, and can be adopted for energy systems and policy planning for various regions in Nepal.

Sustainable regional energy planning: The case of hydro

AbstractThe study is dedicated to analysis of sustainable regional energy planning challenge's in order to reach carbon‐free economy in 2050. The case study of hydropower development in selected region of Poland provides good example how to deal practically with identified sustainable regional energy planning problems to address restrictions of environmental requirements and natural conditions on the least costs hydropower generation planning in a given region. The aim of the article is to develop a model for optimizing hydropower production and to apply this model for selected region. The West Pomeranian region was selected for this case study, and the time range for planning is from 2019 to 2030. The selected region is particularly predestined for the production of renewable energy sources. Constructed model and obtained results for optimization of hydropower development in selected region is useful for fostering usage of renewable energy sources in Poland and moving forward towards carbon‐free economy target set by European Union for 2050.

Assessment of renewable energy-based strategies for net-zero energy communities: A planning model using multi-objective goal programming

Planning decentralised community-level hybrid energy systems has emerged as a solution to the various environmental and economic issues associated with conventional centralised energy supply systems. However, the optimal planning of community energy systems is a challenging issue due to the complexities, uncertainties, conflicting objectives, and high computational times in analysis. This study introduces a new multi-objective model based on weighted goal programming and grey pairwise comparison to assess renewable energy-based strategies in the case of net-zero energy communities. The problem was formulated to determine the optimal energy mix based on minimization of life cycle impacts and costs and maximization of renewable contributions and operational energy savings. To this end, binary integer and continues variables were applied on the code developed in a CPLEX environment. A pairwise comparison based on grey numbers was used to find the impacts of the goals in the objective function of the model under uncertainty. In addition to the grey-based weighting scenario, different weighting scenarios were employed to consider the importance of all goals on the system. These weighting scenarios were used to investigate the effects of changing decision priorities on the outcomes and on stakeholder interests at different levels. The developed goal-programming model was applied to the data of a case example and solved based on the weighting scenarios. Results indicated that the model is capable of finding the best possible strategies with the lowest total undesirable deviations from the desired levels of the goals compared to the literature of the decision-making techniques. The integration of maximum renewable energy (RE) supply in the energy mix with the locally available energy resources can deliver considerable benefits in terms of energy supply cost reduction as well as in mitigating life cycle environmental impacts. When environmental goals are prioritized, integrating low emissions RE as much as possible and excluding waste-to-energy technologies makes best sense, while under a pro-economic perspective, solar integration is comparatively discouraged. The findings of the study are expected to assist community developers and other decision makers involved in regional energy planning. The developed method will also be of use for those who are interested in the use of goal programming to solve complex planning issues involving numerous uncertain parameters.

Scenario Analysis of Renewable Energy–Biodiversity Nexuses Using a Forest Landscape Model

The introduction of renewable energy (RE) in harmony with nature is essential for building a sustainable society. However, the poorly designed introduction of RE can cause conflicts between energy production and biodiversity conservation. This study conducted a scenario analysis to evaluate potential conflicts in the nexuses between energy and biodiversity for a case study area, the Bekambeushi River watershed located in northeastern Japan. The increasing rate of pastureland abandonment resulting from a decreasing farmer population is a source of great uncertainty in this area. Two alternative sources of RE were selected to utilize these abandoned pasturelands, each taking a contrasting approach to meet targets stipulated by regional energy plans, thereby implying different ecological consequences at the landscape level. Thirty-one RE introduction cases were simulated, comprising a range of pastureland abandonment expansion speeds and ratios of solar photovoltaic (PV) plant installation to biomass energy use. These were superimposed using two IPCC representative concentration pathway (RCP) scenarios, 2.6 and 8.5, resulting in 62 cases that were summarized as three scenarios based on the RE supply–demand balance and the ecological impacts. The LANDIS-II model was used to simulate these scenarios from 2016 to 2100. The results indicate that both the rate of pastureland abandonment and the ratio of the two RE sources had a large impact on changes in tree species diversity and the habitat suitability of raptorial birds. Abandoned pastureland converted to tree biomass energy production shifted to pioneer species-dominated forest. The plant species composition of transitional forests varied between the climate scenarios. The higher temperature of the RCP 8.5 scenario toward 2100 prevented the establishment of Betula platyphylla and altered tree species diversity and the habitat suitability of Ketupa blakistoni blakistoni. Biomass energy utilization produced less energy than the demand but increased the three ecological indicators. Solar PV systems provided more energy than the regional demand, but the three ecological indicators decreased. However, an appropriate mixture of the two RE sources satisfied the regional energy demand and maintained ecological conditions. Our results suggest that land–energy planning should consider energy–biodiversity nexuses to a strike balance between decarbonization and biodiversity conservation.

Is Bioenergy Truly Sustainable When Land-Use-Change (LUC) Emissions Are Accounted for? The Case-Study of Biogas from Agricultural Biomass in Emilia-Romagna Region, Italy

Bioenergies are considered sustainable alternatives to fossil energy sources in the European Union (EU) renewable energy targets for 2030. However, their performances in terms of greenhouse gases (GHG) savings may be affected by indirect emissions related to the required land-use-change (LUC) that should be taken into account when modelling their sustainability. The European Renewable Energy Directive (RED) introduced a number of GHG emission criteria, in comparison with fossil fuels, that bioenergy deriving from agricultural biomasses must comply with. The Emilia-Romagna region (North-Eastern Italy), the second largest Italian biogas producer, has recently issued its Regional Energy Plan (REP), which set an ambitious increase of about 40% of the current installed electric power from biogas up to 2030. The aim of this study is to assess the sustainability of Emilia-Romagna REP accounting for the required indirect land-use-change (ILUC), due to the bioenergy crop expansion, potentially needed to reach the targets. Based on regional data available on biogas production, the amount of land used for maize silage to be destined to biogas production (as a model agricultural feedstock) has been calculated for the actual state-of-the art and towards 2030 scenarios provided by the REP. Starting from average GHG emissions associated with biogas production from 100% maize silage of 35 gCO2 eq/MJ, a further contribution of 8–18.5 gCO2 eq/MJ due to LUC has been found. Our findings indicate that it is difficult to assess the global GHG savings from the bioenergy targets fixed by regional energy plans when LUC effects are considered. Careful analysis is necessary in each case to avoid creating negative impacts.

Wave energy resource characterization and assessment for coastal waters of the United States

The wave energy resource is characterized and assessed for coastal waters of the United States to evaluate regional opportunities and constraints for wave energy converter (WEC) projects. Partitioned wave parameters generated from a 30-year WaveWatch III model hindcast are used to estimate the total wave energy potential as an annual available energy (AAE), which is a theoretical annual energy production per unit energy capture length without considering energy conversion losses. The distribution of AAE by peak period, wave direction, month, and year is quantified using summary statistics, including peak period spread, AAE-weighted period, AAE-directionality coefficient, and inter-annual and seasonal temporal variability. Geographical distributions of the AAE and these five resource attributes delineate distinct wave energy resource regions within United States coastal waters, where different opportunities and constraints may influence regional energy planning, WEC project development, and WEC conceptual design.

The development of inexact dual-objective programming for regional energy systems planning in Guang-Fo-Zhao region, China

In this study, a chance-constrained fractional programming model is developed for energy systems in Guang-Fo-Zhao region, China. The developed model can tackle multiple uncertain parameters expressed as interval values, random variables presented as probability distributions in constraints, and provide optimized solutions under different fractional objectives. The proposed method is then applied for renewable energy system and air pollutant management in Guang-Fo-Zhao region. Two objectives are embedded in this strategic planning. One is to maximize renewable power generation per unit system cost, and the other one is to maximize gas air pollutant reduction per unit system cost. The result shows that, in the first objective, the increased rate of generating capacity from renewable energy per unit cost in Guang-Fo-Zhao region is much higher than that of a cost-efficient energy planning. In the second objective, the pollutant emission reduction per unit cost will be greatly improved in Guang-Fo-Zhao region. The proposed model can provide profound solutions and insights for decision makers regarding different energy-environmental considerations and targets. The proposed application in Guang-Fo-Zhao regional energy planning is particularly important for the extension to similar megalopolis under the severe situation of resource limitations, serious environmental pollution situations and ecosystem degradations.

Application of an Institutional Assessment and Design (IAD)-Enhanced Integrated Regional Energy Policy and Planning (IREPP) Framework to Island States

The integrated regional energy policy and planning (IREPP) framework was devised to evaluate the feasibility of energy policies in meeting declared national targets. While the framework advances the comprehensiveness of the feasibility assessment by bringing in concepts like environment economic equity, the muted way in which institutional factors and capacity are addressed remains weak and ineffective. Here, we corrected this weakness by presenting an IREPP framework that is enhanced by integrating principles of the institutional assessment and design (IAD) framework. The IAD framework emphasizes the careful consideration of contextual factors, it draws attention to the full range of transaction costs, and does not presume a priori that one type of institutional arrangement. This IREPP-IAD framework was used to evaluate the feasibility of energy policies in three different island jurisdictions—Taiwan, Mauritius, and Trinidad and Tobago. With ambitious national targets, these islands are good testing grounds for this updated approach. Through qualitative comparative case study analysis, several institutional factors were found to play an influence if national energy policies are likely to meet set targets. These factors included: government/policy decision makers and the decision/policymaking environment; governance structure and commitment for energy policy; existing policy instruments and tools that are in play and those planned; polycentricity; stakeholder participation and community building; market dynamics; information transparency; pilot programs and technology innovations/research; compliance or responsibilities under the Paris Accord; grid connectivity and monitoring of the policy implementation progress. This study contributes in two ways. First, by providing a more robust framework for assessing institutional arrangements that moderate how energy policies are implemented and second, providing insightful assessments of the energy policies in three island jurisdictions, thereby increasing our understanding of island energy policymaking and implementation in these understudied geographies.

Spatial Relationships of Water Resources with Energy Consumption at Coal Mining Operations in China

The spatial characterization and regional differences of water use in China’s coal mines were investigated based on a high spatial resolution mine site dataset, and their spatial synergic relationships with energy consumption were explored using a geographic weighted regression model. There were significant and obvious regional differences in water use in coal production. Most coal-related water withdrawal occurs in Shandong, Henan, Hebei, Anhui, Shanxi, Shaanxi, and Inner Mongolia provinces, accounting for ≈ 73% of the nation’s total energy-related water withdrawal. The cities of Erdos, HulunBuir, Yulin, Shuozhou, and Changzhi have the largest coal-related water consumption, ≈ 36% of the nation’s total, while large coal-related wastewater discharges are mostly concentrated in Shaanxi, Hebei, Shanxi, Henan, and Inner Mongolia provinces, and sporadically in Guizhou Province. There was a considerable positive correlation between consumptive water use and energy consumption in coal production. This study provides a spatially integrated technology to coordinate regional energy and water plans, identify regions suffering the most severe impacts, and can serve as a reference for the transition of coal resource-type cities.

The MATLAB Toolbox for EnergyPLAN: A tool to extend energy planning studies

EnergyPLAN is an energy system analysis tool used worldwide for scientific analyses of national and regional energy planning strategies and alternatives. This work describes the MATLAB Toolbox for EnergyPLAN (MaT4EnergyPLAN), a set of functions developed to manage the EnergyPLAN software using MATLAB. The tool allows the user to take advantage of the energy system analysis capabilities of EnergyPLAN in combination with the computational advantages of MATLAB. This allows the user to easily manage EnergyPLAN files and analyse a large number of EnergyPLAN simulations. • A new MATLAB Toolbox for improving energy planning studies is presented. • The toolbox increases the potentialities of EnergyPLAN analyses. • A method to develop smart renewable energy strategies on islands is presented. • A large number of EnergyPLAN simulations can be analysed and managed from MATLAB.

REGIONAL ENERGY SUPPLY PLANNING: CHANCE CONSTRAINT PROGRAMMING

Regional energy planning under uncertainty is an important concept in energy-economy models which makes the planning outcomes closer to reality and enables the decision maker to select the best decision. Reliability of local energy supply and the possibility of long-term access to resources and emissions reduction is an essential step. In this study, an urban energy demand which is supplied by electricity network is investigated with an optimal combination of alternative energy resources such as solar, wind and natural gas during the next 10 years. The optimal combination of fossil energy as well as renewable energies are determined by goal stochastic programming model. Isfahan province in Iran has been selected as a case study. Empirical results indicate that due to the importance of investment and operation costs, the dominant share of energy supply will belong to natural gas, while the shares of solar and wind energies remain constant in the next decade. In sum, the share of solar and wind energies increases by 8% in 10 years and therefore, it is not necessary to increase electricity supply by the network in order to meet annual increasing demand. CO2 and NOx emissions will decrease significantly.Keywords: Stochastic programming, Goal programming, Local energy planning, Iran.JEL Classifications: Q43, Q47DOI: https://doi.org/10.32479/ijeep.7870