Power Generation Shortage in Developing Countries: Causes, Challenges and Solutions

Electricity consumers in developing countries are seeking reliable electricity services to subsidize the economy and assist the rising population. Underprivileged electricity services are major concerns for these consumers because of power generation shortage. Electricity consumers will be disconnected from the grid as a mean of reducing the total load connected to the distribution grid. In many developing countries, the problem is considered to be severe due to population growth. It is also recognized that electricity shortage negatively affects the quality of life of the residential consumers in these countries. This thesis proposes ways to reduce the severe effect of power generation shortage on developing countries’ consumers and these ways are appropriate for application in remote communities in Canada. These reductions are targeted to utility and residential electricity consumers to address the power generation shortage problem in developing countries. The current status of electricity demand restricts grid expansion due to the limited available power generation. With population growth, there is a demand for a system reinforcement. This reinforcement is either by controlling the behavior of electricity consumers or accommodating new electricity supply resources. Since the behavior of electricity consumers is a major factor contributing to high electricity demand compared to the available power generation, this thesis will focus on optimally scheduling residential demand to minimize the negative gap between the current supply and the future expected demand by proposing two approaches based on scheduling the supply of electricity to either houses or devices within them. These approaches account for the uncertainty in many factors governing consumers’ perception to utilize electricity. From the utility aspect, this thesis proposes improving the grid efficiency by considering investments in alternative sources of supply, such as renewable energy sources to support the current generation to accommodate population growth. The economical aspects to select the best distribution generation sources are shown in this thesis. The thesis will also investigate how current policies can be modified to encourage investors in the power sector to build these resources. It is well known that developing countries do not have the adequate financial resources to build these resource systems. The thesis will also target finding the proper sizes of such energy systems by considering the uncertainty in the generation from these resources to address the power generation shortage. This solution is further expanded by considering the cooperation between the utility and the residential consumers to reduce the size of renewable energy systems while considering residential consumers’ demand scheduling. The thesis sets recommendations targeting electricity services improvement to facilitate not only consumers’ lives, but also countries’ economies

Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO2 Emissions

According to the European Union Emissions Trading Scheme, energy system planners are encouraged to consider the effects of greenhouse gases such as CO 2 in their short-term and long-term planning. A decrease in the carbon emissions produced by the power plant will result in a tax decrease. In view of this, the Dynamic carbon-constrained Equilibrium programming equilibrium constraints (DCC-EPEC) Framework is suggested to explore the effects of distinct market models on generation development planning (GEP) on electricity markets over a multi-period horizon. The investment incentives included in our model are the firm contract and capacity payment. The investment issue, which is regarded as a set of dominant producers in the oligopolistic market, is developed as an EPEC optimization problem to reduce carbon emissions. In the suggested DCC-EPEC model, the sum of the carbon emission tax and true social welfare are assumed as the objective function. Investment decisions and the strategic behavior of producers are included at the first level so as to maximize the overall profit of the investor over the scheduling period. The second-level issue is market-clearing, which is resolved by an independent system operator (ISO) to maximize social welfare. A real power network, as a case study, is provided to assess the suggested carbon-constrained EPEC framework. Simulations indicate that firm contracts and capacity payments can initiate the capacity expansion of different technologies to improve the long-term stability of the electricity market

Coalition Formation of Microgrids with Distributed Energy Resources and Energy Storage in Energy Market

Power grids include entities such as home-microgrids (H-MGs), consumers, and retailers, each of which has a unique and sometimes contradictory objective compared with others while exchanging electricity and heat with other H-MGs. Therefore, there is the need for a smart structure to handle the new situation. This paper proposes a bilevel hierarchical structure for designing and planning distributed energy resources (DERs) and energy storage in H-MGs by considering the demand response (DR). In general, the upper-level structure is based on H-MG generation competition to maximize their individual and/or group income in the process of forming a coalition with other H-MGs. The upper-level problem is decomposed into a set of low-level market clearing problems. Both electricity and heat markets are simultaneously modeled in this paper. DERs, including wind turbines (WTs), combined heat and power (CHP) systems, electric boilers (EBs), electric heat pumps (EHPs), and electric energy storage systems, participate in the electricity markets. In addition, CHP systems, gas boilers (GBs), EBs, EHPs, solar thermal panels, and thermal energy storage systems participate in the heat market. Results show that the formation of a coalition among H-MGs present in one grid will not only have a significant effect on programming and regulating the value of the power generated by the generation resources, but also impact the demand consumption and behavior of consumers participating in the DR program with a cheaper market clearing price

Day-Ahead Offering Strategy In The Market For Concentrating Solar Power Considering Thermoelectric Decoupling By A Compressed Air Energy Storage

Due to limited fossil fuel resources, a growing increase in energy demand and the need to maintain positive environmental effects, concentrating solar power (CSP) plant as a promising technology has driven the world to find new sustainable and competitive methods for energy production. The scheduling capability of a CSP plant equipped with thermal energy storage (TES) surpasses a photovoltaic (PV) unit and augments the sustainability of energy system performance. However, restricting CSP plant application compared to a PV plant due to its high investment is a challenging issue. This paper presents a model to assemble a combined heat and power (CHP) with a CSP plant for enhancing heat utilization and reduce the overall cost of the plant, thus, the CSP benefits proved by researches can be implemented more economically. Moreover, the compressed air energy storage (CAES) is used with a CSP-TES-CHP plant in order that the thermoelectric decoupling of the CHP be facilitated. Therefore, the virtual power plant (VPP) created is a suitable design for large power grids, which can trade heat and electricity in response to the market without restraint by thermoelectric constraint. Furthermore, the day-ahead offering strategy of the VPP is modeled as a mixed integer linear programming (MILP) problem with the goal of maximizing the profit in the market. The simulation results prove the efficiency of the proposed model. The proposed VPP has a 2% increase in profit and a maximum 6% increase in the market electricity price per day compared to the system without CAES

Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates

The United Arab Emirates is moving towards the use of renewable energy for many reasons, including the country’s high energy consumption, unstable oil prices, and increasing carbon dioxide emissions. The usage of electric vehicles can improve public health and reduce emissions that contribute to climate change. Thus, the usage of renewable energy resources to meet the demands of electric vehicles is the major challenge influencing the development of an optimal smart system that can satisfy energy requirements, enhance sustainability and reduce negative environmental impacts. The objective of this study was to examine different configurations of hybrid renewable energy systems for electric vehicle charging in Abu Dhabi city, UAE. A comprehensive study was conducted to investigate previous electric vehicle charging approaches and formulate the problem accordingly. Subsequently, methods for acquiring data with respect to the energy input and load profiles were determined, and a techno-economic analysis was performed using Hybrid Optimization of Multiple Energy Resources (HOMER) software. The results demonstrated that the optimal electric vehicle charging model comprising solar photovoltaics, wind turbines, batteries and a distribution grid was superior to the other studied configurations from the technical, economic and environmental perspectives. An optimal model could produce excess electricity of 22,006 kWh/year with an energy cost of 0.06743 USD/kWh. Furthermore, the proposed battery–grid–solar photovoltaics–wind turbine system had the highest renewable penetration and thus reduced carbon dioxide emissions by 384 tons/year. The results also indicated that the carbon credits associated with this system could result in savings of 8786.8 USD/year. This study provides new guidelines and identifies the best indicators for electric vehicle charging systems that will positively influence the trend in carbon dioxide emissions and achieve sustainable electricity generation. This study also provides a valid financial assessment for investors looking to encourage the use of renewable energy

Cloud Energy Storage Based Embedded Battery Technology Architecture for Residential Users Cost Minimization

This paper presents a cloud energy storage (CES) architecture for reducing energy costs for residential microgrid users. The former of this article concentrates on identifying an appropriate battery technology from various battery technologies with the aid of a simulation study. The later part addresses the economic feasibility of the storage architecture with three different scenarios namely grid connected energy storage, distributed energy storage (DES) and CES. The performance of the proposed architecture has been evaluated by considering five residential users with suitable battery technology identified from the former part of the study. For the purpose of the analysis, PV and load profiles including seasonal effects and grid price were taken from IIT Mumbai, India and IEX portal, respectively. In addition, this article also examines the impact of increased number of users with CES. The value of this study is that the proposed CES architecture is capable of reducing the cost of electricity experienced by the user by 11.37% as compared to DES. With this, CES operator’s revenue can be increased by 6.70% in summer and 16.97% in winter in the case of fixed number of users. Finally, based on the analysis and simulation results, this paper recommends CES with Li-ion battery technology for residential application

Economic Assessment of Distributed Generation Technologies: A Feasibility Study and Comparison with the Literature

With the negative climate impact of fossil fuel power generation and the requirement of global policy to shift towards a green mix of energy production, the investment in renewable energy is an opportunity in developing countries. However, poor economy associated with limited income, funds availability, and regulations governing project funding and development are key factors that challenge investors in the energy sector. Given the various power generation resources, including renewables, it is necessary to evaluate the possible power generation investment options from an economic perspective. To realize this objective, solar PV, wind and diesel power generations are economically compared, considering the incremental rate of return and incremental benefit to cost ratio techniques. The alternative investment options of distributed generation technologies are evaluated for Maharashtra, India under different depreciation methods, and the effect of the latter on selecting the best investment candidate is investigated. The paper also conducts sensitivity analysis to examine the impact of capital cost, operation and maintenance cost, and fuel cost variations on the selection decision considering a comparison of the different general projects’ cash flow structures discussed in the literature. The economic aspects of selecting a project among possible alternatives for an investment in the power sector are analyzed, and the presented review provides comprehensive comparisons with respect to the literature approaches. The results reveal that, in the benchmark case study, the PV project is rejected and disregarded from further comparisons with other candidate projects since its equity internal rate of return (10.25%) is less than the minimum accepted rate of return, leaving the selection between wind and diesel energy projects. The study reveals that the incremental rates of return under such a comparison are 37.88%, 45.94% and 37.50% when MACRS, declining balance and straight line depreciations techniques are applied, respectively. Thus, the wind energy project is the favored option in this case. For the economic assessment of other case studies, the application of both sensitivity analysis on the capital cost and operation and maintenance cost and literature approaches to structure the projects reveal that wind energy for Maharashtra, India is a more attractive and feasible option compared to other distribution generation projects, while diesel is only considered to be a good option when its fuel cost is reduced by 5%. Finally, the paper highlights policy implications that can influence the decision to move towards investment in distributed generation technologies as a future research direction

Reconsidering insulation coordination and simulation under the effect of pollution due to climate change

Climate change and air pollution have a direct impact on the performance and lifetime of insulating materials. In recent years, Mazandaran and Golestan provinces in Iran have witnessed a climate change and an increase in air pollution. This problem increases outages and losses in transmission and overhead distribution network. Moreover, traditional and empirical methods have been used for insulation coordination in past decades. As a result, research is needed on the regional power line isolation, revision of insulated surface design, and the number of insulators used. In this paper, a specialized software was used for checking existing lines in Mazandaran and Golestan Regional Power. Insulation computations and isolation studies using MATLAB software were used to present solutions for transmission and overhead distribution networks. This specialized software has the ability to calculate the required minimum air gap and the minimum creepage distance and the number of insulators with due attention to regional pollution, overvoltage due to switching and lightning, and power frequency

Energy vehicles as means of energy storage: impacts on energy markets and infrastructure

By increasing number of electric vehicles (EVs), which are charged in electric vehicle charging stations (EVCSs) in a distribution network, an optimal charging and discharging strategy that considers the distribution network constraints should be developed to guarantee economically and technically rewards of EVs and EVCSs. This study aims to develop a scheduling scheme to meet benefits of EVs and EVCSs in charging/discharging operation. Each EV plans its charging and discharging operation for 24 h ahead. The benefits of all agents in EV charging/discharging are taken into account by formulating a bilevel optimization problem that the upper level belongs to EVCSs and the inner level belongs to EVs. A scheduling system is responsible to collect the data from EVs and EVCSs and run the bilevel optimization problem and sends the results to EVs and EVCSs. For simulation purposes, a case study based on San Diego, USA, is presented to visualize and validate the modeling results. Six EVCSs are considered for charging and discharging of 400 EVs during 24 h