Microgrids constitute an attractive solution for the electrification of areas where grid extension is not technically feasible or prohibitively expensive. In recent years, national governments have implemented various support policies to encourage the deployment of renewable energy systems (RES) and microgrid hybrid-powered systems. A fundamental aspect during the design and disposition of these types of units is the determination of the optimal configuration and sizing of each power generation component. Furthermore, the optimal design of microgrids is strongly dependent on technological parameters, local meteorological conditions, among other factors. In this context, this paper investigates the effects of different policy measures on the optimal configuration of microgrids functioning in islanded mode. A computable model is employed to carry out a set of sensitivity analyses and assess the impact of capital and fuel subsidies on the levelized cost of electricity of various systems. The model employed for this study minimizes the total life cycle costs (TLCC) over the 20-year lifetime of the microgrid project. Besides, as meteorological conditions are crucial parameters to consider while designing microgrids, a sensitivity analysis is conducted to examine the effect of wind speed and solar irradiation on the capacities of each distributed generation units. Our results indicate that capital subsidies, as well as fuel price variations, have a substantial effect on the final design of microgrid systems for rural electrification.

Electric vehicles (EVs) can have massive benefits in energy sector especially for a small island country like the Maldives that imports oil with high transportation costs while power could have been generated from abundantly available local renewable resources. However, EV charging may also impose significant investment requirement for the power system that needs to be analyzed carefully including the capacity of the existing distribution network system, investments needed in solar PV together with battery storage and additional diesel capacity to meet the incremental demand from EVs. We explore an EV adoption scenario for Maldives for 2030 with 30% of all vehicles including two-wheelers that dominate the transport on the island under two different charging regimes: uncoordinated and optimized coordinated mode. The latter is achieved through a system wide optimization using a modified version of the World Bank Electricity Planning Model (EPM) that optimizes charging load subject to a range of constraints on allowable timing for different categories of vehicles. If charging from the fleet is uncoordinated, a relatively small increase in energy requirement of 3.1% due to EV may lead to a 26.1% increase in generation capacity requirement and hence 15.7% additional investment. While the optimized charging regime helps to drastically cut down on generation capacity requirements to just 1.8% increase and also considerably eases feeder loading, it may also lead to higher emissions as more EV load during off-peak hours lead to an increase in diesel-based generation. We have therefore explored an additional scenario wherein the annual emissions from the power sector are constrained to the baseline (“No EV”) scenario. The analysis shows the importance of focused modeling analysis to understand the ramifications of EV load impact on the power system including significant increase in generation capacity and potential increase in power sector emissions in a fossil-fuel dominated system.

Hybrid energy systems (HESs) generate electricity from multiple energy sources that complement each other. Recently, due to the reduction in costs of photovoltaic (PV) modules and wind turbines, these types of systems have become economically competitive. In this study, a mathematical programming model is applied to evaluate the techno-economic feasibility of autonomous units located in two isolated areas of Ecuador: first, the province of Galapagos (subtropical island) and second, the province of Morona Santiago (Amazonian tropical forest). The two case studies suggest that HESs are potential solutions to reduce the dependence of rural villages on fossil fuels and viable mechanisms to bring electrical power to isolated communities in Ecuador. Our results reveal that not only from the economic but also from the environmental point of view, for the case of the Galapagos province, a hybrid energy system with a PV–wind–battery configuration and a levelized cost of energy (LCOE) equal to 0.36 $/kWh is the optimal energy supply system. For the case of Morona Santiago, a hybrid energy system with a PV–diesel–battery configuration and an LCOE equal to 0.37 $/kWh is the most suitable configuration to meet the load of a typical isolated community in Ecuador. The proposed optimization model can be used as a decision-support tool for evaluating the viability of autonomous HES projects at any other location.

In this paper, we develop a long-term capacity expansion analysis model that considers strategic bidding behavior by dominant generation companies together with new entry decisions, including renewables, to meet a long-term carbon reduction constraint. We deploy a centralized quadratic programming formulation of the Nash-Cournot game to analyze day-ahead electricity market prices. In our model, strategic producers simultaneously make investment and production decisions, deploying an open-loop Cournot game. We have implemented the model for Ukraine's day-ahead electricity market, which has been highly prone to market power issues. The case study results show significant inefficiencies in peak prices and explore scenarios of alternative mitigation options and their efficacies. Finally, the case study is extended to also explore implications of a low carbon future through emission-constrained runs, evaluation of the performance-based emission policy, and sensitivity on different portfolios of new renewable investors.

This paper develops a Nash-Cournot model of multicommodity electricity market, co-optimizing energy and ancillary services, including a strategically behaving storage operator participating in both markets. The model is formulated as a centralized optimization problem and applied to the Ukraine day-ahead market. The impact of battery storage on the prices of energy and ancillary services products under various storage capacities and strategic storage operations is evaluated. It is shown that battery storage could significantly increase competition within the ancillary services market (primarily frequency containment reserves) and reduce prices. Storage with an installed capacity of 1000 MW could cut original frequency containment reserve prices by a third and provide part of its capacity to other ancillary services products.

Wholesale market design choices continue to be debated after four decades, especially as they are being scrutinized in light of the decarbonization goals. This paper shows how a Nash-Cournot equilibrium model can combine capacity, energy, and ancillary services. The model integrates multi-year capacity expansion with dispatch decisions to capture the gaming behavior of generators in the long term, including entry and short-term capacity withdrawal decisions with and without carbon constraints. The model is deployed for Georgia, a hydrodominated system in Eastern Europe where a new market will be introduced in 2024. The modeling analysis examines how alternative design options perform to support the country's power sector decarbonization. The results show that, in such a system, the proposed energy-only (EO) market design performs well, yielding the lowest prices without exacerbating volatility both with and without emission constraints. Although the EO design brings in less capacity, leading to higher expected unserved energy (EUE), it does not breach the incumbent reliability standard, albeit we show that it does expose the system to power shortage in extreme low hydro availability scenarios. On the contrary, the options with a capacity market may lead to significant excess capacity, albeit curbing price volatility as well as EUE. While these findings are specific to Georgia, the modeling framework can be deployed in other systems/countries to evaluate market design proposals.