Mapping concentrated solar power site suitability in Algeria

The investment in solar thermal power technologies has become increasingly attractive, despite their still perceived high costs. Algeria presented an ambitious plan for increasing the participation of renewable energy sources (RES) in the power system, with significant investments foreseen for solar power technologies. To achieve this objective, it is necessary to identify optimal sites for the implementation of these plants, as well as others where implementation is highly inadvisable from the economic, social, or environmental points of view. The main goal of this study is to present and apply a methodology to identify adequate locations for the installation of solar power plants in Algeria. The study addressed the particular case of concentrated solar power (CSP) and proposed a hybrid approach combining multi criteria decision making and Geographic Information System. The approach allowed mapping and visualizing unfeasible areas and ranking the feasible sites. The results showed that more than 51% of the territory of the country is unfeasible for the implementation of CSP, mainly due to criteria related to topographic aspects, water availability, and distance to the grid. The results demonstrated that relying only on Direct Normal Irradiation (DNI) values may result in a reductionist vision for energy planning and thus other criteria can play a fundamental role in the decision process. The model allowed also to identify the best regions for CSP investment and opens routes for more detailed studies for the exact site selection.The authors would like to thank all open source data providers and ESRI Maps for provide the background maps. Also authors thank J. R. Oakleaf et al. for make available spatial data linked to global potential for renewable energy. The authors are also thankful to experts of the research center CDER and the engineering experts who participated in the AHP for their assistance

Distributed Energy Infrastructure Development: Geospatial & Economic Feasibility in Rural West Virginia

Energy transition from conventional to centralized power plants, including coal-fired units, is critical for West Virginia’s long-term energy and economic future. The socioeconomic downturn in West Virginia was deeply connected with the dependence on the centralized coal industry and the coal economy. Most traditional coal communities in rural West Virginia struggle to maintain economic viability, potentially leading to outmigrations and poor energy resilience. I investigated the possibility of introducing community-sized distributed energy systems in these rural communities to improve energy resilience and accommodate the future transition from centralized coal-generated energy. My goal was to identify rural regions where distributed energy can be utilized at an optimal cost, thus improving energy resiliency within these communities and positively impacting the economy. This study provided a geospatial modeling approach with Multi-Criteria Decision Analysis (MCDA) and Geographic Information System (GIS) suitability assessment to identify the feasible locations of small-scale distributed generation for wind, solar, and hydropower energies. The net value comparison analysis was conducted utilizing the levelized cost of energy (LCOE) and levelized avoided cost of energy (LACE) to determine the differences in investment costs for each distributed generation type compared with traditional coal-generated electricity. I expected the spatial analysis results to reveal optimal sites for the specific distributed energy types. I found that wind and solar distributed generation have stronger presences in southern and eastern West Virginia counties, while suitable small hydropower development locations are spread across the state. This study provided insight into future distributed energy and its infrastructure development possibilities in rural West Virginia

Identification of Outer Continental Shelf Renewable Energy Space-Use Conflicts and Analysis of Potential Mitigation Measures

The ocean accommodates a wide variety of uses that are separated by time of day, season, location, and zones. Conflict can and does occur, however, when two or more groups wish to use the same space at the same time in an exclusive manner. The potential for conflict is well known and the management of ocean space and resources has been, and is being, addressed by a number of State, regional, and Federal organizations, including, among others, coastal zone management agencies, state task forces, and regional fisheries management councils. However, with new and emerging uses of the ocean, such as aquaculture and offshore renewable energy, comes the potential for new types of space-use conflicts in ocean waters. In recent years, the Bureau of Ocean Energy Management (BOEM) (formerly the Minerals Management Service [MMS]) has examined ocean space-use conflicts and mitigation strategies in the context of offshore oil and gas exploration and production and sand and gravel dredging, activities that are both subject to BOEM regulation and oversight. BOEM now has authority to issue leases on the Outer Continental Shelf (OCS) for renewable energy projects, but seeks additional information on potential conflicts between existing uses of the ocean environment and this new form of activity. The broad purpose of this study was to begin to fill this gap by (1) identifying potential spaceuse conflicts between OCS renewable energy development and other uses of the ocean environment, and (2) recommending measures that BOEM can implement in order to promote avoidance or mitigation of such conflicts, thereby facilitating responsible and efficient development of OCS renewable energy resources. The result is a document intended to serve as a desktop resource that BOEM can use to inform its decision making as the agency carries out its statutory and regulatory responsibilities

Facility Planning Optimization Platform, GGOD, for Expandable Cluster-type Micro-grid Installations and Operations

This paper describes the architecture and the utilization for a facility planning optimization platform called GGOD, “Grid of Grids Optimal Designer” and applies it to expandable cluster-type micro-grid installations and operations. The expandable cluster-type micro-grid is defined as a group of micro-grids that are connected by bi-directional power transfer networks. Furthermore, power sources are also networked. Especially, by networking among power sources, powers necessary for social activities in-demand areas are secured. The proposed architecture is based on service-oriented architecture, meaning that optimization functions are executed as services. For flexibility, these services are executed by requests based on extensible mark-up language texts. The available optimizations are written in meta-data, which are accessible to end-users from the meta-data database system called clearinghouse. The meta-data are of two types, one for single optimization and the other for combined optimization. The processes in GGOD are conducted by the management function which interprets descriptions in meta-data. In meta-data, the names of optimization functions and activation orders are written. The basic executions follow sequential, branch, or loop flow processes, which execute combined optimizations, compare more than two kinds of optimization processes, and perform iterative simulations, respectively. As an application of the proposed architecture, the power generation sites and transmission networks are optimized in a geospatial integrated-resource planning scenario. In this application, a structure and a method for the combination of component functions in GGOD are exemplified. Moreover, GGOD suggests promotions of a lot of applications by effective combinations of basic optimization functions

Spatially-resolved and temporally-explicit global wind energy potentials as inputs to assessment models

Several decarbonisation scenarios indicate that renewable energy will be a key supply route to mitigate carbon emissions this century. To better represent the implications of such an energy transition, it is important that energy systems models (ESMs) can realistically characterise the technical and economic potential of renewable energy resources. This thesis presents a temporally-explicit and geospatially-resolved methodology for estimating the global wind energy potential, i.e. the annual terawatt-hour (TWh/yr) production potential of wind farms, assuming that capacity could be built across the viable onshore and offshore areas of each country, globally. Further, a geospatially-resolved levelised cost of electricity (LCOE) model is developed to characterise the offshore cost potential, accounting for non-resource related cost factors. Capacity potential is produced in tranches according to the average annual capacity factor and the capacity factor in each time slice. For offshore wind, capacity potential is also disaggregated by the distance to shore and water depth, which are the main cost drivers. A technology-rich description of fixed and floating foundation types allows LCOEs to be calculated for each grid cell across the globe, relative to location-specific annual energy production (AEP). Results show that the global wind energy potential is vast, but severely diminished if areas far from electricity infrastructure are discounted. Nevertheless, for onshore wind the capacity potential for capacity factors above 15% is 267 TW, with a generation potential of 580,000 TWh/yr. The offshore potential is 329,600 TWh/yr with a relatively smaller deployment capacity of 85.6 TW, reflecting the access to higher capacity factors in offshore areas. Deployment potential is favourable for countries with large shallow water areas. However, recent cost developments have made access to transitional and deep water locations much more feasible as long as turbine size increases continue to offset the relatively higher foundation costs.Open Acces

A multi-criteria, long-term energy planning optimisation model with integrated on-grid and off-grid electrification – The case of Uganda

While electricity access is lowest in developing countries, the academic literature on generation expansion planning (GEP) has been informed almost exclusively by challenges in industrialised countries. This paper presents the first multi-objective, long-term energy planning optimisation model tailored towards national power systems with little existing power infrastructure. It determines the location, type, capacity and timing of power system infrastructure additions. Specifically, three novel generalisations of standard generation planning are introduced: (1) an expansion of the demand constraints to allow for industrial and household electrification rates below 100%, (2) a minimisation of sub-national energy access inequality in conjunction with minimising system costs considering environmental constraints, and (3) an integration of distribution infrastructure, explicitly including both on-grid and off-grid electrification. Using a specifically designed solution algorithm based on the ε-constraint method, the model was successfully applied to the previously unexplored Ugandan national power system case. The results suggest that while it is cost-optimal to maintain highly unequal sub-national access patterns to meet Uganda's official 80% electrification target in 2040, equal access rates across all districts can be achieved by increasing discounted system cost by only 3%. High optimal shares of locationally flexible on-grid and off-grid solar energy enable cheap sub-national shifts of generation capapcity. This paper strongly challenges the Ugandan government's nuclear energy and largely grid-based electrification expansion plans. Instead, it calls for solar concentrated power as a baseload option in the future and a focus on off-grid electrification which the model selects for the majority of household connections in 2040, even in a high-demand scenario.</p

How Black Sea offshore wind power can deliver a green deal for this EU region. CEPS Policy Contribution 09 Oct 2020.

An EU low-carbon economy, with a fully decarbonised power sector at its core, will require very large volumes of low-carbon electricity. To date, offshore wind holds the most promise for the necessary volumes to be realised. While the North Sea offers the best prospects by far, there is significant potential in other waters, including the Baltic Sea, the southern European waters and the Black Sea. Given past and expected cost reductions, Black Sea offshore wind is a major economic opportunity for EU and non-EU countries in the region under the European Green Deal. From an energy perspective it offers a way to substitute increasingly uneconomic coal, without increasing dependence on imported Russian gas, including for landlocked countries. Offshore wind can rejuvenate harbour areas and attract new investment in future-proof technologies more generally, thereby creating jobs, many of them well paid. Low-carbon energy will become a precondition for attracting future investment, not just for low-carbon industries. The Next Generation EU recovery fund is an opportunity for the region to take the next step; first plans are emerging. Given its historic size, good plans and projects will be supported. Member states and their regions must quickly develop comprehensive plans. The experience shows that offshore wind requires a dedicated governance framework. With the Central and South Eastern Europe energy connectivity initiative (CESEC), the framework exists; it can be adapted to meet the needs of offshore wind. A successful EU Black Sea strategy may radiate beyond the EU and the Energy Community. There is interest in renewable energy and offshore wind, especially in Turkey, but also in Azerbaijan, Russia, and the Caspian region

A framework for the selection of optimum offshore wind farm locations for deployment

This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts’ input in order to support investment decisions. Further, techno-economic evaluation, life cycle costing (LCC) and physical aspects for each location are considered along with experts’ opinions to provide deeper insight into the decision-making process. A process on the criteria selection is also presented and seven conflicting criteria are being considered for implementation in the technique for the order of preference by similarity to the ideal solution (TOPSIS) method in order to suggest the optimum location that was produced by the nondominated sorting genetic algorithm (NSGAII). For the given inputs, Seagreen Alpha, near the Isle of May, was found to be the most probable solution, followed by Moray Firth Eastern Development Area 1, near Wick, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make better informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK

The future scope of large-scale solar in the UK: site suitability and target analysis

This paper uses site suitability analysis to identify locations for solar farms in the UK to help meet climate change targets. A set of maps, each representing a given suitability criterion, is created with geographical information systems (GIS) software. These are combined to give a Boolean map of areas which are appropriate for large-scale solar farm installation. Several scenarios are investigated by varying the criteria, which include geographical (land use) factors, solar energy resource and electrical distribution network constraints. Some are dictated by the physical and technical requirements of large-scale solar construction, and some by government or distribution network operator (DNO) policy. It is found that any suitability map which does not heed planning permission and grid constraints will overstate potential solar farm area by up to 97%. This research finds sufficient suitable land to meet Future Energy Scenarios (UK National Grid outlines for the coming energy landscape)