Robust Economic Dispatch of Microgrid With Highly Penetrated Renewables and Energy Storage System

Economic dispatch (ED) of a grid-connected and renewable integrated microgrid is considered in this article. Here, the renewable energy sources (RES) taken into consideration are wind farms. A parameter worst-case-transaction-cost which arises due to the stochastic availability and uncontrollable nature of wind farms is also emphasised and efforts have been taken to minimize it too. Hence, the article focuses on separately optimizing the generation costs and the worst-case transaction costs. It also optimises the net microgrid cost as a whole, which is the summation of generation costs and the worst-case transaction costs. Two different cases with highly varying transaction prices are studied. Various types of loads, ramp rates of generators, charging and discharging limits of the batteries are taken into consideration while minimizing the microgrid cost. Four meta-heuristic soft computing algorithms are applied for optimization and a comparative analysis among them is studied. Numerical results are tabulated to justify the effectiveness of the novel approach.

Thermo-economic analysis of the potential for electricity generation by integrating a Rankine cycle with municipal solid waste incineration

Municipal Solid Wastes generated by human activities increase as the population grows; in Ocaña city, Norte de Santander, Colombia, these wastes reach a monthly production of about 2660 tons, made up of 65.6% waste food, 15.3% plastics, 9.9% toilet paper, 3.6% paperboard, 2.6% textile residues, 1.6% paper, 0.8% wood wastes, and 0.1% rubber. This work estimates the energy potential from municipal solid wastes for electricity generation and their production costs. A multicriteria decision analysis allowed selecting the best technology for the wastes processing based on their energy content. For the evaluated criteria, the incineration process showed priority. A model developed in the engineering equation solver software allowed calculating the electrical energy potential by integrating the incineration process with a Rankine cycle. By implementing a thermo-economic assessment, the electricity generation costs were determined, where the inversion, installation, operation, and maintenance costs were considered. 1974 KW of electrical power with generation costs of $300/KWh and a payback period of 2.5 years show the feasibility of this process.

Monetising Air Pollution Benefits of Clean Energy Requires Locally Specific Information

Meeting the Paris Agreement on climate change requires substantial investments in low-emissions energy and significant improvements in end-use energy efficiency. These measures can also deliver improved air quality and there is broad recognition of the health benefits of decarbonising energy. Monetising these health benefits is an important part of a robust assessment of the costs and benefits of renewable energy and energy efficiency programs (clean energy programs (CEP)) and a variety of methods have been used to estimate health benefits at national, regional, continental and global scales. Approaches, such as unit damage cost estimates and impact pathways, differ in complexity and spatial coverage and can deliver different estimates for air pollution costs/benefits. To date, the monetised health benefits of CEP in Australia have applied international and global estimates that can range from 2–229USD/tCO2 (USD 2016). Here, we calculate the current health damage costs of coal-fired power in New South Wales (NSW), Australia’s most populous state, and the health benefits of CEP. Focusing on PM2.5 pollution, we estimate the current health impacts of coal-fired power at 3.20USD/MWh, approximately 10% of the generation costs, and much lower than previous estimates. We demonstrate the need for locally specific assessment of the air pollution benefits of CEP and illustrate that without locally specific information, the relative costs/benefits of CEP may be significantly over- or understated. We estimate that, for NSW, the health benefits from CEP are 1.80USD/MWh and that the current air pollution health costs of coal-fired power in NSW represent a significant unpriced externality.

Review of Data and Data Sources for the Assessment of the Potential of Utility-Scale Hybrid Wind–Solar PV Power Plants Deployment, under a Microgrid Scope

Utility-scale hybrid wind–solar PV power plants (which might include some storage as well) are an attractive option for the transition of conventional grids to incorporate high renewable energy (RE) shares. Along with lower generation costs, they offer increased dispatch capabilities and flexible operation. However, when assessing their potential, they present higher needs in terms of input data, as they are forced to consider both spatial and temporal variations to evaluate their techno-economic viability, as well as other common inputs such as economic, social or environmental data. The availability of the different data influences the type of analysis to be implemented. The microgrid approach of segmenting the information into layers will be adopted for the classification of data. Three different levels of analysis are sought: long-term energy scenarios, geo-spatial planning, and production cost estimation. The analysis of necessary data for each planning stage, and the available data sources for the assessment of utility-scale hybrid power plants, under this microgrid approach, is the main focus of this review.

Design of Maximum Power Tracking System for Photovoltaic Power Generation

Solar power generation is related to climatic conditions, and its high cost and low power generation efficiency have become the main factors restricting its development. Realizing the maximum power tracking of solar photovoltaic power generation through power electronic technology and control technology is an effective measure to increase the power generation of photovoltaic power generation systems, reduce power generation costs, improve solar energy conversion efficiency, and widely promote photovoltaic power generation technology. According to the illumination characteristics of solar cells, using a single-chip microcomputer to control the DC-DC converter and conductance increment method as the control algorithm, a solar maximum power tracking system is designed.

Efeito do Incremento da Produção de Energias Renováveis Intermitentes nos Preços da Eletricidade

Despite increasing deployment of intermittent renewable energies at lower generation costs, wholesale electricity price has been falling while retail electricity prices go up. This has triggered the debate on the cost-effectiveness of this source of energy. Therefore, the aim of this paper is to present a literature survey on the effect of intermittent renewable energy generation on electricity prices. Researches have used different methodological approaches, different periods and countries to examine the impacts of intermittent renewable energy on electricity prices. Most of the studies found evidence of the merit-order effect, which means that an increase in intermittent source generation would reduce the spot electricity market price. Finally, the few studies that address the retail market found that retail electricity could either increase or decrease.

OPF of Modern Power Systems Comprising Renewable Energy Sources Using Improved CHGS Optimization Algorithm

This article introduces an application of the recently developed hunger games search (HGS) optimization algorithm. The HGS is combined with chaotic maps to propose a new Chaotic Hunger Games search (CHGS). It is applied to solve the optimal power flow (OPF) problem. The OPF is solved to minimize the generation costs while satisfying the systems’ constraints. Moreover, the article presents optimal siting for mixed renewable energy sources, photovoltaics, and wind farms. Furthermore, the effect of adding renewable energy sources on the overall generation costs value is investigated. The exploration field of the optimization problem is the active output power of each generator in each studied system. The CHGS also obtains the best candidate design variables, which corresponds to the minimum possible cost function value. The robustness of the introduced CHGS algorithm is verified by performing the simulation 20 independent times for two standard IEEE systems—IEEE 57-bus and 118-bus systems. The results obtained are presented and analyzed. The CHGS-based OPF was found to be competitive and superior to other optimization algorithms applied to solve the same optimization problem in the literature. The contribution of this article is to test the improvement done to the proposed method when applied to the OPF problem, as well as the study of the addition of renewable energy sources on the introduced objective function.

Integration of deterministic and game-based energy consumption scheduling for demand side management in isolated microgrids

In this work, a group Autonomous Demand-Side Management (ADSM) program for day-ahead scheduling of energy consumption profiles in an isolated microgrid is proposed, aiming to reduce the overall energy generation cost. The proposed program is applied to a Multiple-Sources Multiple-Customers (MSMC) system, consisting of a shared centralized energy source, distributed Renewable Energy Sources (RESs) and Distributed Storage Elements (DSEs). The proposed program integrates a Deterministic Energy Management (DEM) strategy with a Tabu Search (TS)-based scheduling game to reduce the computational complexity while acknowledging the intermittent nature of RESs as well as the level of customers’ comfort. Moreover, an equitable billing mechanism for charging customers based on their energy consumption and adherence to their assigned schedules is implemented. Simulations of the proposed program reveal that the TS-based algorithm offers similar energy generation costs and peak-to-average energy ratio (PAER) to those obtained with a benchmark Branch and Bound (BB) algorithm, with a significantly lower computational complexity, while being superior in computational complexity, energy costs and PAER to an algorithm based on Parallel Monte Carlo Tree Search (P-MCTS). Furthermore, the proposed integrated DEM and TS-based scheduling strategy in an MSMC system is demonstrated to offer 48% reduction in the one-day energy generation costs, compared to a SSMC system managed using a TS-based scheduling game alone.

Critical peak rebate strategy and application to demand response

Time-of-use (TOU) pricing strategy is an important component of demand-side management (DSM), but the cost of supplying power during critical peak periods remains high under TOU prices. This affects power system reliability. In addition, TOU prices are usually applicable to medium- and long-term load control but cannot effectively regulate short-term loads. Therefore, this paper proposes an optimization method for TOU pricing and changes the electricity consumption patterns during the critical peak periods through a critical peak rebate (CPR). This reduces generation costs and improves power system reliability. An optimization model for peak-flat-valley (PFV) period partition is established based on fuzzy clustering and an enumeration iterative technique. A TOU pricing optimization model including grid-side and customer-side benefits is then proposed, and a simulated annealing particle swarm optimization (SAPSO) algorithm is used to solve the problem. Finally, a CPR decision model is developed to further reduce critical peak loads. The effectiveness of the proposed model and algorithm is illustrated through different case studies of the Roy Billinton Test System (RBTS).