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This study evaluates the potential benefit of retrofitting existing conventional cascade hydropower stations (CCHSs) with reversible turbines so as to operate them as pumped hydro energy storage (PHES) systems. We examine the energy generation and storage problem for a CCHS with two connected reservoirs that can be transformed into a PHES system in a market setting where the electricity price can be negative. We formulate this problem as a stochastic dynamic program (SDP) under uncertainty in the streamflow rate and electricity price. We analytically derive an upper bound on the profit improvement that can be obtained from the PHES transformation. We conduct numerical experiments with data-calibrated time series models and observe that the PHES system provides a greater benefit under more limited streamflow conditions or more frequently observed negative prices.

We study the energy generation and storage problem for various types of two-reservoir pumped hydro energy storage facilities: open-loop facilities with the upper or lower reservoir fed by a natural inflow and closed-loop facilities. We formulate this problem as a stochastic dynamic program under uncertainty in the streamflow rate and electricity price. We include the streamflow rate and electricity price as exogenous state variables in our formulation. We compare the short-term total cash flows obtained by running different pumped hydro energy storage configurations in a market setting where the electricity price can be negative. We first derive theoretical bounds on the revenue gains and losses from switching from one configuration to another. We then conduct numerical experiments by employing time-series models to formulate the evolution of our exogenous state variables. We consider three distinct seasons with different streamflow rates, different negative price occurrence frequencies, and different reservoir capacities. Our results show that: (1) The open-loop facility with the upstream flow can yield cash flows that are up to four times as large as those of the closed-loop facility; (2) The cash flow from operating a large closed-loop facility can be achieved by operating an open-loop facility with 10 times smaller reservoirs; and (3) The open-loop facility with the downstream flow can be more advantageous than the open-loop facility with the upstream flow (with an improvement of more than 10% in the cash flow) if the negative electricity price occurs more than 30% of the time.

We propose a scalable computational framework to examine the effects of settlement patterns on the electrification of an entire country. We first propose a data processing strategy to convert structure locations, identified from satellite imagery, to estimated household locations using census data. Then, we present a computational framework that involves a two-level network design algorithm to find an abstract representation of the power distribution system at a national scale involving low voltage (LV) wires, medium voltage (MV) wires, and the transformers between the two levels of the system. Given the system components, we introduce three metrics for per-household connectivity requirements of LV and MV wires, and transformers to interpret our results at the administrative and the sub-administrative unit levels. With our administrative level analysis provided for 9.2 million structures in Kenya, we show that traditional rural/urban classification based on population density may not be enough and is often deceiving in estimating the cost of electrification and a new categorization based on our metrics provides more relevant estimates on the total cost. Moreover, our metrics can help determine the least-cost electrification option (e.g.,grid, mini-grid, or stand-alone systems) for expanding access in the sub-administrative unit level and create a platform to perform sensitivity analysis based on different cost components. Our work demonstrates the potential for improvements in universal electrification combining new and more detailed data sources with a scalable planning framework and helps governments achieve Sustainable Development Goal 7 (SDG7) more quickly and at lower cost.

The lack of access to electricity in developing countries necessitates spatial electricity planning for guiding sustainable electrification projects that evaluate the costs of centralized systems vis-a-vis decentralized systems. Heuristic approaches have been widely used in such electrification problems to find feasible, cost effective solutions; however, most of the time global optimality of these solutions is not guaranteed. Our paper through its modeling approach provides a new methodology to find the least cost solution to this electrification problem. We model the spatial network planning problem as Prize Collecting Steiner Tree problem, which would be a base for a decision support tool for rural electrification. This new method is systematically assessed using both randomly generated data and real data from rural regions across Sub-Saharan Africa. Comparative results for the proposed approach and a widely used heuristic method are presented based on computational experiments.

Pumping of water for agriculture can be a flexible component of electric demand. In this study, a framework that involves scenario based stochastic programming models is developed to examine the effect of load shifting on the renewable energy system sizing for agricultural load. With the help of this framework, alternative load shifting policies are evaluated to observe how the intrinsic flexibility of agricultural load reduces the amount of investments while designing a renewable system. Using real data from India’s Gujarat region, solar and wind cases are evaluated separately to understand the coherency between these sources and the agricultural demand. The value of using a dispatchable source to help with the intermittency of the renewable sources in the systems is discussed. It is also shown that energy storage can be a convenient control mechanism for the integration of renewables; however, is an expensive substitute for demand response programs for agricultural load. Benchmarks for the incentive amounts that can be provided for alternative load shifting policies are presented.

Traditionally, the main focus of evaluation in universal electricity access problems has been cost. However, additional criteria such as increasing renewable penetration due to environmental concerns or grid penetration due to reliability concerns, have become increasingly important. We acknowledge the importance of additional criteria and propose a bi-objective framework so as to help decision makers investigate the trade-offs between potentially conflicting criteria in rural electrification. We consider two objective space based exact approaches using the Prize Collecting Steiner Tree (PCST) formulation and two metaheuristic algorithms to find Pareto solutions, and investigate their performances on real life problem instances. This study is expected to be an important decision support tool for the electrification of underdeveloped communities, having the potential of contributing to their socio-economic development.

Probabilistic realizations of outages and their effects on the operational costs are highly overlooked aspects in power system expansion planning. Since the effect of randomness in contingencies can be more prominent especially when transmission switching is considered, in this paper we introduce contingency-dependent transmission switching concept to ensure N-1 criterion. To include randomness of outages and the outputs (i.e. flow on the lines/generation amounts) during the outages, we represent each contingency by a single scenario. Status of transmission lines, generation amounts and power flow decisions are defined as recourse actions of our two-stage stochastic model, therefore, expected operational cost during the contingencies are taken into account in a more accurate manner. A solution methodology with a filtering technique is also proposed to overcome the computational burden. The model and the solution methodology are tested on the IEEE Reliability Test System and IEEE 118-bus power system and the results show that the solution method finds the solutions for these power systems in significantly shorter solution times. The solution method is also tested on a new data set for the 380-kV Turkish transmission network. Suggestions for possible extensions of the problem and the modifications of the solution approach to handle these extensions are also discussed.

Increasing the share of renewable energy sources in electricity generation helps address concerns about carbon emissions, global warming and energy security (i.e. dependence on fossil fuels). However, integrating intermittent and variable energy sources into the grid imposes new challenges for power system reliability and stability. To use these clean sources in electricity generation without endangering power systems, utilities can implement various control mechanisms, such as energy storage systems, demand side management, renewable energy curtailment and transmission switching. This paper introduces a two-stage stochastic programming model that co-optimizes transmission switching operations, and transmission and storage investments subject to limitations on load shedding and curtailment amounts. We discuss the effect of transmission switching on the total investment and operational costs, siting and sizing decisions of energy storage systems, and load shedding and renewable energy curtailment in a power system with high renewable penetration. An extensive computational study on the IEEE 24-bus power system with wind and solar as available renewable sources demonstrates that the total cost and total capacity of energy storage systems can be decreased up to 17% and 50%, respectively, when transmission switching is incorporated into the power system.

In efforts to achieve universal electricity access, geospatial factors, particularly the distribution of populated places and other electricity demands, are fundamentally important in determining the relative costs of competing grid, mini-grid or home system electrification options. Research presented here goes beyond broad metrics such as population density to instead consider patterns of aggregation and distances between communities to produce geographically specific cost estimates for medium and low voltage line. This analysis considers these factors at two geographic scales. First, it presents localized investigations of several rural locations in sub-Saharan Africa, at the scale of tens of kilometers, using household-level location data from GPS surveying and high-resolution satellite imagery. This work resulted in broad classification of village landscapes and suggested cost-effective electrification with different technologies depending upon inter-community and inter-household distances as proxies for medium and low voltage line lengths. Second, the analysis draws upon larger scale planning studies and data, at the scale of thousands of kilometers, in developing countries targeting electricity access for millions or tens of millions of unserved households, relying on coarser geospatial population datasets. A key observation of this analysis relates to the manner in which electrification planning can respond to cost tradeoffs between grid and non-grid electrification options in areas with different settlement patterns.

Fosil yakitlarin elektrik uretimindeki payini azaltmak icin yenilenebilir enerji kaynaklari iceren enerji modellerine ihtiyac duyulmaktadir. Ancak, yenilenebilir enerji kaynaklari genellikle duzenli olmayan ve aralikli enerji kaynaklaridir ve kesin olarak tahmin edilemezler. Alternatif kaynaklarin ortak kullanimini mumkun kilan hibrid sistemler tasarlamak ve enerji deposu kullanmak, bu kaynaklarin kullanimiyla ilgili guclukleri azaltmak ve hem maliyet hem de guvenilirlik acisindan etkin sistemler tasarlamak icin kullanilan yontemlerdendir. Dunyada ozellikle buyuk olcekli sistemlerde en yaygin olarak kullanilan depolama bicimi, enerjinin pompaj depolamali hidroelektrik santrallerde (PHES) suyun potansiyel enerjisi formunda depolanmasidir. PHES’ler, sisteme disaridan su girisi olmasi durumunda karisik, olmamasi durumunda ise saf sistemler olarak tasarlanabilirler. Bu calisma, her iki tip PHES sisteminin kaynaklardaki ve talepteki belirsizlikleri de goz onune alacak seklide iki-asamali stokastik programlama modelini sunmaktadir. Bu calisma ile literaturde ilk kez, belirli bir elektrik talebini karsilamak icin kurulabilecek gunes enerjisi uretim tesisinin ayri ayri saf PHES ve karisik PHES ile desteklendigi hibrid sistemler ele alinmis ve sonuclar su an hic PHES sistemi olmayan ve yenilenebilir enerji kaynaklarinin yuksek potansiyeline ragmen enerji uretimi yuksek oranda fosil yakitlara dayanan Turkiye icin bir vaka analizi seklinde sunulmustur.

This paper analyzes the optimal options for supplying electricity to national economies from both domestic and distant energy resources using high voltage lines to transmit the substantial renewable energy resources of Africa. To meet the growing demand, Africa will need to provide 5.2 GW of new generation per year through 2025. This figure represents an increase of 65% from the 2010 level and will assist in connecting more than 11 million new customers per year through the development of a transmission network. The total discounted system cost is approximately 8% of the continent's GDP. Approximately two-thirds of the discounted system cost is associated with new generation, and the remaining one-third is associated with the development of the transmission network. From 2010 to 2025, trade expansion reduces the total system cost by 21% relative to the business as usual (BAU).

We introduce a new continuous location-allocation problem where the facilities have both a fixed opening cost and a coverage distance limitation. The problem has wide applications especially in the spatial planning of water and/or energy access networks where the coverage distance might be associated with the physical loss constraints. We formulate a mixed integer quadratically constrained problem (MIQCP) under the Euclidean distance setting and present a three-stage heuristic algorithm for its solution: In the first stage, we solve a planar set covering problem (PSCP) under the distance limitation. In the second stage, we solve a discrete version of the proposed problem where the set of candidate locations for the facilities is formed by the union of the set of demand points and the set of locations in the PSCP solution. Finally, in the third stage, we apply a modified Weiszfeld’s algorithm with projections that we propose to incorporate the coverage distance component of our problem for fine-tuning the discrete space solutions in the continuous space. We perform numerical experiments on three example data sets from the literature to demonstrate the performance of the suggested heuristic method.

Transition from fossil fuels to renewable sources is inevitable. In this direction, variation and intermittency of renewables can be integrated into the grid by means of hybrid systems that operate as a combination of alternative resources, energy storage and long distance transmission lines. In this study, we propose a two-stage stochastic mixed-integer programming model for sizing an integrated hybrid energy system, in which intermittent solar generation in demand points is supported by pumped hydro storage (PHES) systems and diesel is used as an expensive back-up source. PHES systems work as a combination of pumped storage and conventional hydropower stations since there is also natural streamflow coming to the upper reservoirs that shows significant seasonal and inter-annual variability and uncertainty. With several case studies from India, we examine the role of high hydropower potential in the Himalaya Mountains to support solar energy generation in the form of pumped hydro or conventional hydro system while meeting the demand at various scales. We show that pumped hydro storage can keep the diesel contribution to meet the demand less than 10%, whereas this number can go up to more than 50% for conventional systems where the streamflow potential is limited compared to the demand. We also examine the role of pumped hydro systems in both isolated and connected systems (through inter-regional transmission lines) and show that the benefit of pumped hydro is more significant in isolated systems and resource-sharing in connected systems can substitute for energy storage. In addition, with the help of the proposed model, we show that the upper reservoir size of a pumped hydro system could be lower than the reservoir size of a conventional hydropower system depending on the demand scale and streamflow availability. This means that, most of the current conventional hydropower stations could be converted to pumped hydropower stations without needing to modify the upper reservoir, leading to a significantly reduced diesel contribution and lower system unit cost.

We describe the first heuristic algorithm that selects the locations and service areas of transformers without requiring candidate solutions and simultaneously builds two-level grid network in a green-field setting. The algorithm we propose minimizes overall cost of infrastructure costs; specifically the combined costs of transformers and the two-tiered network together by solving transformer location problem as well as network design problems in a single optimization framework. In addition, it allows one to specify different costs for the higher throughput lines upstream of the transformer as compared to downstream of the transformer. Simulations are carried out based on real-world spatial distributions of demand points from rural locations in Africa, specifically in places without any pre-existing infrastructure to test the algorithm and generalize the results.

Infrastructure planning for networked infrastructure such as grid electrification (or piped supply of water) has historically been a process of outward network expansion, either by utilities in response to immediate economic opportunity, or in response to a government mandate or subsidy intended to catalyze economic growth. While significant progress has been made in access to grid electricity in Asia, where population densities are greater and rural areas tend to have nucleated settlements, access to grid electricity in Sub-Saharan Africa remains low; a problem generally ascribed to differences in settlement patterns. The discussion, however, has remained qualitative, and hence it has been difficult for planners to understand the differing costs of carrying out grid expansion in one region as opposed to another. This paper describes a methodology to estimate the cost of local-level distribution systems for a least-cost network, and to compute additional information of interest to policymakers, such as the marginal cost of connecting additional households to a grid as a function of the penetration rate. We present several large datasets of household locations developed from satellite imagery, and examine them with our methodology, providing insight into the relationship between settlement pattern and the cost of rural electrification.

The current supply for electricity generation mostly relies on fossil fuels, which are finite and pose a great threat to the environment. Therefore, energy models that involve clean and renewable energy sources are necessary to ease the concerns about the electricity generation needed to meet the projected demand. Here, we mathematically model a hybrid energy generation and allocation system where the intermittent solar generation is supported by conventional hydropower stations and diesel generation and time variability of the sources are balanced using the water stored in the reservoirs. We develop a two-stage stochastic model to capture the effect of streamflows which present significant inter-annual variability and uncertainty. Using sample case studies from India, we determine the required hydropower generation capacity and storage along with the minimal diesel usage to support 1 GWpeak solar power generation. We compare isolated systems with the connected systems (through inter-regional transmission) to see the effects of geographic diversity on the infrastructure sizing and quantify the benefits of resource-sharing. We develop the optimal sizing relationship between solar and hydropower generation capacities given realistic cost parameters and real data and examine how this relationship would differ as the contribution of diesel is reduced. We also show that if the output of the solar power stations can be controlled (i.e. spill is allowed in our setting), operating them below their maximum energy generation levels may reduce the unit cost of the system. © 2015 Elsevier Ltd.